Speed sensorless control is an efficient technique for providing reliable, cost-effective, and stable drive system in electric vehicle (EV). Yet, obtaining accurate sensor-less control across entire speed range poses a significant problem. This paper presents a modified disturbance observer (MDO) based speed sensor-less control of synchronous reluctance (Syn-Rel) motor. The presented technique utilizes active flux (AF) concept of Syn-Rel motor, which eliminates variations in the estimated flux from cross-coupling. Presented system’s robustness is enhanced by its insensitivity to DC bias and high-frequency noise. Speed and position are estimated with adaptive gain enhanced quadrature PLL (AG-eQPLL) technique. In comparison to conventional and other speed estimation techniques, presented technique is with minimal speed and position error. Presented system is integrated with solar PV array and grid for augmenting battery performance. The battery performance and range are improved utilizing roof mounted solar panel under running and at rest condition of vehicle. Moreover, performance is also improved with battery charging using installed voltage source converter (VSC) acting as an on-board charger under standstill condition. The system is analysed and validated using MATLAB software. A comprehensive depiction of EV dynamics with improved performance is also validated through experimental test bench.

Tripping of inverter-based resources (IBRs) powered by renewables poses a key challenge for reliable grid integration, especially at point of common coupling (PCC). Intermittency of solar and wind leads to power fluctuations, causing dynamic variations in PCC voltage amplitude and phase. As a result, voltage parameters sensed by incoming sources become time-varying functions of real-time power exchange. During IBR synchronization, rapid power shifts may induce fictitious frequency deviations estimated by phase-locked loops (PLLs), triggering false tripping during phase angle jumps (PAJs). This article tackles such synchronization and tripping issues for a microgrid comprising a wind-driven doubly fed induction generator (DFIG), solar photovoltaic array, and battery energy storage. A multifunctional control enables seamless operation across grid-tied and off-grid modes, even with or without DFIG stator-PCC connection. A multiple delay signal cancellation (MDSC115) prefilter and enhanced PLL (αβ-EPLLVI) ensure robust synchronization are validated as per the IEEE Std. 1547 via simulation and hardware results.

This article confers operation and control of grid interactive microgrid (MG), which is suitable for windy remote areas. This MG possess appreciative wind energy generation capability but erratic grid connection. This MG operable in grid-tied mode as well as in islanded mode (IM), consists of wind powered doubly fed induction generator (DFIG) battery energy storage. In IM, to ensure a self-sufficient MG for uninterrupted power flow to loads, diesel generator (DG) set is used. DFIG unit operates in peak power point tracking zone to take maximum benefit of renewable energy, whereas DG set operates in fuel economic zone to ensure optimal usage of conventional energy resources. Loads are continuously powered in all operating states, whereas synchronizations from one state to another are seamless. Synchronizations are executed by using three solid state power electronics switches. However, since such wind generator based microgrids are installed in remote areas, power quality issue is raised in the grid. Therefore, this work proposes an updated exponential hyperbolic cosine robust adaptive filter-based control, which is implemented for grid forming converter of MG. This ensures power interaction between MG and grid/DG with total harmonic distortion less than 2%. For reliable operation of MG, synchronizations between several states are crucial, which require proper estimation of frequency and phase, thereby type-2 forward compensation synchronous reference frame phase locked loop is utilized, which ensures fast tracking. The system is simulated in Simulink/MATLAB platform whereas obtained results are validated in OPAL-RT test bench.

Electronic loads significantly affect power quality in electrical distribution systems, creating challenges that must be addressed to ensure reliable operation. Integration of hybrid renewable energy systems further exacerbates these issues, particularly at grid interconnection points. This article proposes a robust control methodology to mitigate such disturbances in systems combining integration of solar photovoltaic, wind power, and batteries for storage solutions. Strategy employs a generalized fourth-order filter with a harmonic decoupling network to isolate positive-sequence fundamental and harmonic components from load currents and grid voltages, while also estimating frequency and phase angle for seamless grid synchronization. These extracted signals regulate voltage source converter currents to ensure compliance with IEEE 1547 standard. Comparative analysis shows that proposed approach outperforms conventional adaptive control in load balancing and harmonic suppression, while enabling smooth transitions between self-sustain mode and utility-tied mode. Effectiveness and reliability of method are validated through both simulation and hardware prototype experiments, confirming its ability to handle complex grid conditions with technical robustness and precision.

Four-wire configurations are commonly used in residential microgrids, where single-phase and nonlinear loads introduce harmonics, third-harmonic currents, and negative-sequence components. These harmonics often circulate within delta loops formed by line conductors, while negative-sequence currents cause power imbalance. In wind energy-based microgrids with transformers, such harmonic and unbalanced currents are often reflected into transformer or grid, leading to overheating, increased losses, reduced active power transfer ability, and possible failure. Processing these harmonic currents through transformers to prevent grid contamination demands a higher-rated neutral conductor, adding cost and thermal stress. To address these challenges, this work proposes a three-phase four-wire topology with an auxiliary converter at load point of common coupling (PCC), supported by a solar photovoltaic (SPV) array and battery energy storage (BES). Four-leg auxiliary converter compensates for load harmonics, neutral currents, negative-sequence components, and reactive power, while enabling power exchange from SPV array and BES units. It operates in both grid-forming and grid-following modes to support seamless transitions between islanded and grid-connected states. Integrated multi-mode control ensures coordinated source operation and compliance with IEEE Std. 1547 during mode transitions. Simulation results validate system effectiveness across various modes, demonstrating substantial improvements in power quality and operational reliability in residential microgrids.

This paper presents a hybrid microgrid system designed for rural areas, integrating small hydro and photovoltaic (PV) arrays with battery storage to ensure uninterrupted power supply to local loads in isolated regions. A self-excited induction generator (SEIG) is employed for small hydro power generation, while power quality issues caused by nonlinear loads are addressed using the Volterra Filtered-X Least Mean Square (VFXLMS) technique. This method effectively suppresses dominant harmonic components in load currents and accurately estimates the fundamental frequency of load currents. The PV array is interconnected at the DC link of a voltage source converter (VSC) through a boost converter, while a bidirectional converter manages battery operations, facilitating efficient power management. The bidirectional converter supports the export and import of power from/to the battery, optimizing energy utilization within the microgrid. Conventional proportional-integral (PI) control has limitations in DC voltage tracking and mitigating overshoot and undershoot. To address this, a nonlinear extended state observer (NESO) is employed to mitigate disturbances. The NESO, combined with a disturbance observer, enhances the operational reliability of the microgrid. An experimental setup has been developed to validate the system’s performance under conditions of unbalanced loads and varying PV insolation levels.

This article deals with an islanded three-phase four-wire battery-supported system with integration of solar and wind. Voltage and frequency of point of common coupling (PCC) are regulated by a battery-supported converter. On other side, voltage across stator of wind driven doubly fed induction generator (DFIG) is developed by stage-I rotor side converter control. After matching with grid code, the stator connects with PCC. Stage-II control is based on field-oriented control and it is used to activate power loop of controller. Moreover, this control offers required reactive power by DFIG and it also follows reference rotor speed. An improved three phase comb sliding mode control (CSM) regulates dc-link voltage of grid side converter and mitigates power quality issues. Dynamic performances during load variation and change in wind speed are handled by this advanced CSM controller. On other hand, double-stage photovoltaic (PV) power is fed to PCC via a voltage source converter. This VSC is controlled by dq-control, which regulates dc-link voltage of corresponding converter and also improves performance during solar dynamics. These results are displayed through system and controller behavior during wind variation, different insolation, load variation, and stator synchronization. Moreover, developed system is maintaining grid current total harmonic distortion (THD) below 2%.

This study presents a hybrid power conversion system comprising a doubly fed induction generator (DFIG) based wind generator, solar photovoltaic array, and battery energy storage, and a diesel generator (DG) set, designed to shield DFIG from grid voltage abnormalities. Key contribution in this work is to ensure uninterrupted power delivery across six operating modes and ten transitions, enabling seamless dynamic performance. This work also ensures operating each renewable energy at maximum power point, regardless of operational modes or transitions. Sinusoidal currents are maintained for DG set, DFIG stator, and grid, even under nonlinear and unbalanced loads, meeting power quality standards. DG set operates within its optimal fuel utilization zone, enhancing efficiency, and reducing costs. Hardware validations in steady-state and dynamic conditions demonstrate stable operation, seamless transitions, and uninterrupted power supply in grid-tied andoff-grid scenarios. Maximum utilization of wind and solar energy is achieved, with DG set ensuring adequacy during prolongedoff-grid conditions. Results confirm compliance with power quality standards and seamless operation under various dynamic conditions.

This article presents a new control for multirenewable energy sourced microgrid (MG) that performs operational mode change seamlessly with added power quality improvement features. This MG comprises of a wind turbine driven doubly fed induction generator and a solar photovoltaic array. This control presents an adaptive current control based on proportionate robust diffusion recursive least exponential hyperbolic cosine method utilized for fundamental weight extraction. This adaptive control offers a superior convergence rate and noise-free weight estimates, thereby providing significant harmonics reduction from injected grid currents. A change of MG operational mode is due to check imposed by islanding scheme, which functions reliably due to accurate calculation of phase angles provided by multiple delayed signal cancellation (MDSC) frequency-locked loop method. MDSC prefilter mitigates issues of harmonics distortion and dc-offset from input voltage signal, providing accurate estimates. This new control is tested on a developed prototype in the laboratory using a dSPACE MicroLabBox DS1202, under adverse operational conditions.

Integration of renewable energy sources into standalone microgrids is gaining significant attention due to increasing demand for sustainable and reliable power systems. Solar photovoltaic power plant (SPVP) and synchronous diesel generators (DG) are commonly used in these configurations to ensure a stable and continuous power supply. Presence of SPVP reduces rating of DG set to be used. However, integration of these sources presents challenges related to power quality leading to reduced system power transfer capability and increased losses with reduced life of DG. Ensuring reactive power compensation, harmonics mitigation, and balanced load conditions are critical for optimizing performance of DG set and maintaining stable system operation. Hence, this study presents an advanced control strategy that leverages voltage source converter of SPVP to achieve unity power factor operation for DG set, while also compensating for harmonics and unbalanced loads. By employing an improved variable step normalized adaptive filter, presented control enhances system power quality following the IEEE standard 1547–2018. Simulations and hardware validations are conducted to verify effectiveness of control, demonstrating its potential to improve fuel efficiency and reduce operating costs in standalone microgrid applications.

Community and residential loads connected to low voltage AC distribution networks require a neutral point connection. Neutral point forms return path for single-phase loads. Presence of neutral wire reduces effect of unbalanced loading of one phase to get reflected on other load phases. It helps during fault conditions to minimize effect of circulating current by providing low impedance path. However, in case of harmonically polluted load currents, rating of neutral conductor increases, leading to additional losses and unwanted heating effecting other components of network. Wind energy conversion systems (WECS) use transformer for connection to AC network to reduce requirement of higher rating and size of DC link capacitor. Neutral current and harmonic currents of load are processed through the transformer, which leads to additional heating of transformer ands which is detrimental for connected loads. Such conditions can lead to failure of WECS operation and damage transformer and connected sensitive loads due to flow of circulating currents. Hence, this work presents design and control of a novel four wire topology of a WECS comprising of a doubly fed induction generator (DFIG) and a battery energy storage (BES). A grid forming converter (GFC) is deployed to provide independent compensation for load neutral and harmonic currents without affecting the WECS transformer, reducing its failure and heating rate. WECS converters are controlled to improve power quality of stator current and point of common coupling (PCC) voltage as per the IEEE 519-2022 std. Simulation results present MPPT operation of WECS with neutral and harmonic compensation even during dynamic conditions.

Interleaved current fed dual active bridge (CFDAB) converter is a potential converter for low voltage battery charging applications. The output inductors, which are present on the low voltage side of CFDAB, provide ripple-free battery current and shoot through protection under fault conditions. The behavior of this converter slightly differs from the voltage fed dual active bridge (VFDAB) converter and is less studied in literature. This paper presents the study in two parts. Firstly, an improved Fourier domain model of CFDAB is presented which can seamlessly incorporate numerous harmonics for better large signal model accuracy unlike conventional generalized average modeling (GAM) technique. Furthermore, the small signal model is constructed for selective dominant harmonics in order to preserve simplicity. The presented Fourier domain model is based on Harmonic state space (HSS) model. Secondly, it discusses the presence of two resonances in the small signal model of CFDAB. One of them lies at switching frequency while other lies at converter natural frequency. The latter resonance either increases the steady state ripple or decreases the bandwidth of the conventional closed loop current controller. Hence, this paper also presents adaptive notch integrated PI controller in order to overcome above drawbacks of simple PI controller. Simulations are carried out in MATLAB/Simulink. Experimental investigations are carried out on a laboratory prototype. Simulation and experimental results confirm the plausibility of the model and controller.

The inherent tendency of single-phase grid-connected ac–dc converters is to produce double-line-frequency ripple at the dc link. A buck-based active power decoupling (APD) converter is employed to solve this issue of double-line-frequency ripple. By operating the APD converter with variable switching frequency, a critical condition mode (CRM) is achieved, which ensures soft switching of both the switches of APD converter. However, high-attenuation-based digital filters in both voltage and current loops are necessary in variable-switching-frequency-based control, which introduces new dynamics in the control loop. This limits the ability of the controller to rapidly adjust the decoupling capacitor voltage with change in output power. In this article, a novel control method is proposed for the APD converter, which entitles the design of a faster decoupling control, while ensuring the system stability and efficiency during dynamic periods. Although the proposed control results in higher robustness and improved transient response, the original dynamics of the system remain unaffected. The steady-state and dynamic performance improvement results with the proposed control of the CRM-operated APD converter are validated through simulation and experimental results.

During grid-outage, photovoltaic array and battery supported water pump system with grid connection is operated in an islanded-mode. It is necessary to facilitate synchronization of system with grid to realize on-demand water pumping and to increase utilization of system. Thus, a generalized delayed signal cancellation (GDSC) with frequency drift compensation (FDC) based phase locked loop (PLL) to realize grid synchronization is presented in this article. The developed GDSC-FDC-PLL removes all harmonic components till 15th order and dc-offset. The nonadaptive DSC blocks are used to implement the presented PLL to reduce computational load. Besides, a compensation is applied in the presented PLL due to use of nonadaptive DSC. Meanwhile, GDSC-QSG based current and voltage controls are realized in grid-connected and islanded modes. The merits of the presented PLL are demonstrated by performing its in-depth analysis. Test performances for different operating modes are acquired to validate the effectiveness of the developed PLL.

In this article, we present a modified least mean square (M-LMS) adaptive filter-based controlled grid-integrated photovoltaic system (GPVS) with the capability for islanded operation during power cuts. The system employs a two-stage configuration to regulate the voltage at dc link. Designed M-LMS is utilized to extract ripple-freedq-axis components of grid voltages and load currents. Thesedqcomponents of voltages are then processed through a phase-locked loop (PLL) to obtain angle and frequency information. Meanwhile, thedq-axis components of load currents contribute to integrate load compensation features within GPVS. Additionally, these components play a crucial role in decision-making processes for load shedding or automatic load control during islanded operation. In comparison to other algorithms, the M-LMS algorithm distinguishes itself by eliminating the need for a transformation matrix and uses angle as feedback instead of frequency to make the structure adaptive. It serves as a modified alternative to LMS, showcasing superior response compared to both LMS and second-order generalized integrator algorithms. Furthermore, the PLL structure is redesigned to address frequency variations resulting from phase changes during synchronization, contributing to achieving a seamless connection. To validate the designed control performance, simulations are conducted, and the system's effectiveness is verified through application on a test bench setup of the GPVS.

This article presents an adaptive current control for wind-fed microgrid (MG) based on doubly-fed induction generator (DFIG). Generally, such wind generation based microgrid is installed in remote locations, where power quality is a concern in the grid. In this aspect, this work proposes an adaptive current control for the stator-side converter of DFIG, which injects MG power with total harmonic distortion less than 5%, as prescribed by the IEEE-519 standard. The adaptive filtering scheme is based on Amari-Alpha least mean square method, which performs good for weight estimation under dynamic operating conditions for such MG. MG possess the ability to transfer between grid-tied and islanded mode based on an islanding scheme, which is grounded on the IEEE-1547 standard. The synchronization process to the grid is critical and requires accurate phase and frequency estimation, thereby forward compensated type-2 phase locked loop (FCT2PLL) is utilized, which is fast tracking due to the forward compensation provided. FCT2PLL is tested here in this scheme, which validates its utility in practical scenarios. Detailed performance is achieved with MATLAB simulation and tested in real-time scenario on a laboratory setup using dSPACE-DS1202 as the controller.

This article analyzes an application of a unified power quality conditioner (UPQC) for improving power quality (PQ) in a stand-alone hydro generating system that supplies electricity to nonlinear loads. In this scenario, a series power active filter (SEPAF) is employed to ensure a consistent and fundamental voltage magnitude across loads, irrespective of any voltage variations produced by the hydro generator [squirrel cage induction generator (SCIG)]. Moreover, a shunt power active filter (SHPAF) of the UPQC improves the PQ of source terminals by addressing several issues such as reactive power, current harmonics, currents unbalancing, and power factor. Furthermore, by running the SCIG at a voltage level that is 10–20% lower than its rated value, the need for excitation from a capacitor bank is minimized. This reduction in magnetizing current leads to a decrease in overall losses. To have a coordinated control between the SEPAF and the SHPAF, a control approach referred to as a damped ratio adaptive second-order generalized integrator is used for extracting fundamental components of load currents. The utilization of UPQC enhances voltage characteristics of critical loads and currents at the generation end, hence ensuring compliance with standards set by the IEEE . Hardware validations demonstrate the efficacy of the system.

This article presents a novel application of Fourier decomposition method in a double-stage grid-tied microgrid integrating a solar photovoltaic array (SPVA) and battery energy storage (BES). Due to intermittent nature of SPVA generation and the nonlinearity of local loads connected at point of common coupling, the grid is subject to harmonic distortions. The proposed control method decomposes nonlinear and nonstationary signals to extract fundamental components necessary for generating switching pulses for voltage source converter. To ensure reliable operation during grid outages, system incorporates a BES, managed using a bidirectional dc–dc converter. This configuration maintains high-quality power delivery, and facilitates a smooth transition between grid-connected mode and standalone mode. Simulation and hardware prototype results validate effective operation of proposed control strategy.

In this article, we present a dual control of interfacing converter connected between the dc subgrid and the ac utility grid. The primary objective of the microgrid is to supply consistent power to ac loads and dc loads when a system undergoes disruptions in loads and grid ends while maintaining overall power quality. Under grid abnormalities, an enhanced first-order filter with multiple prefilters frequency-locked loop is utilized for extraction of positive sequence fundamental component of grid voltages while eliminating the dominant (5th and 7th) harmonics components and operating at unity power factor. Moreover, the same quadrature signal generator is used to estimate the accurate active element of load current while suppressing the influence of noise and dc offset. The comparative approach of control is observed to justify its adaptability. However, during standalone mode, an artificial neural network (ANN) based controller action is implemented to enhance the tracking capability. The ANN executes via a rigorous training process of current trajectories in order to obtain the controller's satisfying response. A brushless direct current generator is used as a microhydro and wind generator, as it is independent of frequency and voltage variations at a point of common intersection, unlike other ac generators. The simulation of a microgrid in MATLAB Simulink platform is performed and validated using a hardware prototype in the laboratory undergoing various disruptions to evaluate the system's response in both operating modes.

An improved multicarrier modulation technique is presented for single-source cascaded H bridge based solar multilevel converter (SMLC). Main aim of this article is to improve harmonic profile at converter output voltage. New modulation is introduced, which is summation of pulse and triangular carrier functions to have a new modified level arranged carrier scheme (MLACS). In MLACS, frequency of pulse function isSftimes carrier wave. Comparative Fourier investigation of MLACS and LACS is discussed. It is implemented in closed loop for enhancing power quality of SMLC at grid end. Comparison of new scheme is done with level arranged carrier scheme, phase-shifted carrier scheme (PSCS), and parabolic level arranged carrier scheme in under and over modulation ranges. MLACS efficacy is investigated in terms of weighted total harmonic distortion for five level output. Presented results at laboratory level validate MLACS concept for improved harmonic performance of SMLC.

The nonlinear loads demean the system power quality leading to increased ohmic losses and shorter equipment lifespan. To mitigate power quality challenges, this work proposes a multiple delayed signal cancellation filter with 15 layers and unit delay factor (MDSC115) for improved power quality of a grid-tied solar power conversion system (SPCS) equipped with a battery energy storage (BES). The control attenuates all integral positive sequence harmonic components from 2ndto 30thharmonics excluding positive sequence 16thharmonic. It also eliminates integral negative sequence harmonic components from 1stto 28thharmonics excluding negative sequence 14th harmonic, including 0 Hz DC component, without the need of additional prefilters cascaded to the filter. A modified frequency locked loop (MFLL) is incorporated to make the MDSC115 adaptive to the varying grid frequency and make it immune to phase angle jump and frequency fluctuations in the grid voltages. The MDSC115-MFLL improves the power quality of SPCS during grid adversities and load current irregularities. Performance of MDSC115-MFLL is validated in MATLAB during several dynamic test cases and compared with other delay-based controls to ensure better performance and commitment to the IEEE std. 519 during operation of SPCS.

Many residential and commercial appliances utilize low-power motors. In this work, a low power switched reluctance motor (SRM) is used with front end converter to maintain the power quality at the grid side. It is preferred to operate a four-phase motor with the mid-point converter for a cost-effective solution. A dual output Zeta-Luo-based bridgeless (ZLBL) PFC converter is designed to feed SRM mid-point converter. The ZLBL converter's mode of operation and design are illustarted for a 450 W SRM. This converter operates as a Zeta converter in a positive supply cycle and as a Luo converter in a negative supply cycle. The low-cost and straightforward discontinuous conduction mode (DCM) control are used. The input inductors of both Zeta and Luo converter are in DCM for positive and negative grid supply, respectively. The speed of the low-power SRM drive is controlled by regulating the DC link voltage. For the validation of dual output bridgeless rectifier, an eight-stator and six-rotor pole configuration SRM is used. The flexibility of this dual output rectifier for a four-phase SRM in low-cost applications, is supported by simulation results.

This article introduces a power management scheme (PMS) for an integrated wind–solar renewable power generation system (RPGS). The PMS takes advantage of a time-of-use electricity pricing mechanism to manage the net power exchange between the grid and the RPGS. A battery energy storage is utilized for enabling the system price arbitrage functionality. Meanwhile, the system control is performed through a novel application of the adaptive kernel width maximum correntropy criterion strategy. Apart from utilizing the electricity price volatility to maximize returns, the RPGS is also equipped to offer ancillary services support to the utility grid in the form of 1) grid reactive current injection considering system constraints and 2) grid power quality conditioning through local compensation of load reactive power, harmonics and unbalance. Moreover, for reduced system losses and minimized ripples in the grid currents amidst variations in grid voltages, a self-adjustable dc voltage reference technique is accommodated in the control strategy. An RPGS, employing a solar photovoltaic array and a doubly-fed induction generator for wind power generation, is utilized to experimentally demonstrate the effective operation of the overall control strategy.

The standalone three phase system for power quality (PQ) improvement of both the load side voltages as well as the currents of the machine terminal is presented in this article. This standalone system consists of a three-phase permanent magnet synchronous generator (PMSG) driven by governor-less hydro turbine as a three-phase source feeding the sensitive/nonlinear/linear loads, connected via a unified power quality conditioner (UPQC). The UPQC consists of a back-to-back connected voltage source converters (VSCs) sharing a common dc bus. The series compensator of the UPQC is used to eliminate voltage PQ and to maintain the sinusoidal, balanced, and constant amplitude voltages at load terminals irrespective of any variation in the system. Moreover, the current quality, such as reactive power compensation, and harmonics elimination, are provided by the shunt compensator of the UPQC, simultaneously while improving voltage quality issues. In addition, the efficiency of the overall system is significantly improved by running the generator below its rated voltage and reduces the losses by operating at unity pf. The system frequency and the generated voltage magnitudes are maintained during any load fluctuation or imbalance loading. The model of the UPQC-based hydro turbine driven PMSG system is developed in the Simulink-MATLAB environment, and its results are presented for analysis. The validation of the system is also done on the hardware prototype, and it performs effectively for the voltage and current PQ enhancement simultaneously. It significantly improves the PQs at the generator terminals and ensures to adhere the IEC-61727 and the IEEE-519 standards even with either balanced or unbalanced loads.

This paper proposes an intelligent control scheme (ICS) for optimum efficiency and reduced emission operation in small marine transportation systems such as tugs, research vessels, and small scale cruiser ships. The diesel engines used in marine and other transport related applications are designed to provide optimum efficiency at a specific value of mechanical loading. Generally, these engines provide the best fuel efficiency near 80% of their rated load and also the break specific emission of CO (carbon mono oxide) and other harmful greenhouse gases are found to be lowest at this specific amount of mechanical loading. The proposed controller makes the diesel engine to operate continuously at 80% of loading in order to ensure an optimum efficiency operation even if the mechanical load is kept changing due to the variations and fluctuations in the ship propulsion load or electrical load. The intelligent control scheme (ICS) uses a battery bank as an energy balancing element to maintain a constant total mechanical loading on the engine shaft using a bidirectional power flow control through the battery bank thus changing effective mechanical loading on the engine for optimum efficiency operation of the marine transportation system. The output mechanical power (P) delivered by the engine on its shaft is sensed using a power sensor and compared with its optimum value in order to calculate the error. Thereafter, based on the information about the error in engine shaft power, the ICS regulates the power flow to the SPAG (single phase asynchronous generator) in such a manner that the mechanical load on the engine is restored to its optimum value immediately. The optimum efficiency operation is maintained under randomly varying mechanical power demanded by the ship propulsion system and it is also maintained under varying electrical loads in the marine transportation system. This ICS scheme has been implemented in the laboratory using a DSP controller. The detailed test results are presented to validate the claims.

In this work, the uninterrupted residential power supply is ensured by utilizing a resilient synchronization control for distributed generation based reconfigurable AC microgrid. The distributed generation from renewables such as photovoltaic array and wind power generation with energy storage is included. The power supply reliability is enhanced by utilizing a diesel generator (DG) as a back-up source for the instances of generation shortage from renewable resources and completely drained battery storage. The seamless operating modes namely current control and voltage control are enabled in accordance to the occurrence/clearance of the faults via the static transfer switches (STS-1/2) that isolate/reconnect the microgrid to the utility/DG. The high quality power is ensured by utilizing ε-normalized sign regressor least mean square (ε-NSRLMS) algorithm to evaluate the total current active component of loads. Modified notch filter based second order generalized integrator-frequency locked loop (MNF-SOGI-FLL) avoids frequency and phase oscillations and provides the effective frequency and phase synchronization. The output of the DG is controlled by the automatic voltage regulator (AVR) associated at the synchronous generator (SG) field terminals. The microgrid allows sensitive load operation, uninterrupted residential load supply and improved power quality and these are confirmed from simulation and experimental results obtained from the laboratory prototype.

This paper presents a method for the rotor position estimation of a switched reluctance motor (SRM) based on B-spline neural network to develop a position sensor-less drive. The neural network estimates the rotor position by measuring the phase voltage and current to calculate the flux-linkage. The neural-network can be trained online or by using the flux-linkage characteristics of the SRM. The efficacy of the model is validated by employing it to minimize the torque ripple in a 8/6 SRM by simulation in MATLAB/Simulink environment.

This paper deals with the power quality improvement in a solar photovoltaic (PV) array generation-based EV (Electrical Vehicle) charging station. This charging station is capable of operating in standalone mode and charging the EV battery with the power generated by a PV array. Moreover, it also interfaces with the utility and feeds it the remaining power. Another advantage of the charging station is the compensation of the reactive power for the improvement of the grid power quality. The charging station serves the following purposes (i) harmonics current compensation, (ii) EV battery charging/discharging control, (iii) simultaneous EV battery charging and harmonics current compensation and (iv) simultaneous discharging and harmonics current compensation. The charging station is controlled in such a manner that it operates satisfactorily even under the unbalance grid voltages and total harmonics distortion of the grid currents is reduced below 5% as suggested in the IEEE-519 standard. The control strategy is designed in such a manner that the charging station operates in grid connected mode. However, if the charging station loses the synchronism, then it operates in standalone mode and PV array charges the EV battery. A synchronization control is also developed to connect the system to the grid, when it is available.

The perturb & observe (P&O) algorithm is very popular for maximum power point tracking (MPPT) for solar photovoltaic (PV) systems. However, it has tracking problems during varying irradiations as well as the nuisance of oscillations around the maximum power point (MPP). This work introduces a circle center-line concept based P&O (CCCP&O) algorithm for MPPT, where, the concept of circle and its center are combined with the P&O algorithm. This algorithm tends to reduce the number of iterations taken to reach the MPP, which reduces settling time. Moreover, the problem of large oscillations around the MPP is eliminated by using the concept of flexible step size. The algorithm initializes with standard P&O, but utilizes a approach of diameter equivalence of a circle as a procedure to reach next operating point on the power-voltage plot. Therefore, the iterations required to get to the MPP are reduced substantially. The MPP changes with change in solar irradiance, therefore, a concept of artificial envelope around the P-V curve is used to improve tracking of the algorithm during varying irradiances. The overall performance of the algorithm is demonstrated and compared in simulation using SIMULINK MATLAB as well as also shown experimentally in a developed hardware prototype.

The direct matrix converter (DMC) offers a compact and robust solution over typical ac–dc–ac converter, by enabling direct ac–ac power conversion without any energy storage requirements. Moreover, it offers enhanced source current quality, innate bidirectionality and power factor correction capabilities. Its industrial suitability is further advocated by the elimination of common-mode voltage through the DMC topology. Space vector modulation and model predictive control based approach to common-mode voltage elimination in matrix converter, are previously proposed. This article proposes the delta-sigma modulation for common-mode voltage elimination in matrix converter, which is computationally less cumbersome and performs better as compared to previously documented methods. This method utilizes only six most optimum states of DMC that yield zero common-mode voltage, and performs load voltage and source current control by computing each error variable (delta), integrating it (sigma) and further minimizing it within a hysteresis band. Source current control necessitates load current estimation, which is done through predictive model of the load, hence eliminating load current sensors.

This article aims to develop a unique configuration of a solar-powered water pumping system (SPWPS), which ensures an uninterruptable water supply along with the earning possibility for the consumer. This water pumping system utilizing the switched reluctance motor drive, needs no current sensor on the motor side to run the system. The concept of integrating the grid to the SPWPS as an electrical energy storage device, provides assistance against the fluctuations in power, minimum electricity cost and earns from excess of photovoltaic power. An efficient control logic for grid-side voltage source converter is developed in this article. It has multiple intends like to regulate the desired dc-link voltage, to maintain the power quality and to improve the dynamic responses. This controller incorporates the second- and third-order generalized integrator-based filter for fundamental component extraction of grid voltage and has the benefits of both the filters. Moreover, the new control logic for dual output boost converter as a maximum power point tracking converter is also proposed in this article. It helps to simultaneously maximize the solar power as well as to nullify the voltage asymmetry across both dc-link split capacitors of a mid-point converter under all operating modes. The applicability of the developed arrangement with designed control logic is verified by experimental results.

In this article, a novel single-layer decoupled multiple-order generalized integral-based control algorithm is used for a single-stage solar energy grid integrator (SEGI) with maximum power extraction. The single-layer decoupled structure is used to extract the fundamental component of load current. Moreover, the online grid frequency estimation is carried out for an accurate band-pass filtering. The single-layer architecture of the control for the three-phase load current estimation, reduces the control complexity, and improves the response time. Moreover, the single-stage system is operated with the maximum power point tracking based on the residual incremental conductance algorithm. Hence, the cost of a new conversion stage and additional control are saved. This system is operated under three operating modes. In “normal-mode,” it feeds power to the load and the grid. Wherein the “sharing mode,” SEGI and grid supply the load power. During the night, SEGI functions as an active filter, which is termed as “filter-mode.” The steady-state and dynamic performances of SEGI during each operating mode and transition between the modes due to irradiation variation as well as load fluctuation are verified experimentally on a developed prototype. Moreover, test results under dynamic load variations such as nonlinear and unbalanced load conditions are presented to validate the theoretical claims.

In this paper, a microgrid based on solar photovoltaic (PV) array and a battery energy storage (BES) is presented, which operates in an islanded mode and the grid connected mode. It changes the mode of operation seamlessly, while supplying uninterrupted power to the load. A cascaded SOGI (Second-Order-Generalized-Integrator) based control is used in GCM. The cascaded SOGI is used to extract the fundamental component of the nonlinear load current. A PV array power feed-forward component is used for improving its system dynamics. An optimal power from the solar PV array is acquired by using an I&C (Incremental Conductance) technique. In IM, a voltage control scheme is utilized, which controls the frequency and voltage at point of common coupling (PCC). The efficacy of cascaded SOGI based technique is demonstrated through test results at various conditions such as vaying load, changing solar irradiance and transition between the modes of operation.

This paper presents a single-phase neutral point clamped (NPC) multilevel converter (MLC) configuration for grid-connected photovoltaic (PV) applications. A single-stage control is implemented to feed PV array power to the grid at unity power factor. The direct and quadrature components-based controller is designed to have independent control on active and reactive powers injection. A low computational DC component injection based neutral point voltage (NPV) balance regulator ensures equal charging and discharging of DC-link capacitors. Moreover, the pulse width modulation technique with unipolar pattern is applied at lower switching frequency to adhere with minimum switching losses and power quality standards. The system performance in terms of parameters such as NPV balancing, converter voltage harmonics, the grid current harmonics, and unity power factor operation is analysed at variable irradiances. Simulation results are obtained using MATLAB/Simulink are validated using OPALRT test bench.

The energy poverty in rural areas is due to the intermittent power supply from the existing utility. The proposed remotely located wind-solar photovoltaic array and battery energy storage (BES) supported microgrid, intends to overcome the uncertainty of the renewable power generation by compensating power quality (PQ) disturbances at the point of common coupling (PCC). Robust normalized mixed norm (RNMN) adaptive algorithm filters the load current component to remove the harmonics pertaining due to nonlinear load currents and improves the voltage profile at PCC. It allows the connection of sensitive loads without affecting their life and applicability at PCC. RNMN algorithm provides enhanced convergence rate as well as it reduces the steady-state error effectively. BES controlled by a bidirectional dc-dc converter ensures power supply to the critical loads during scarce generation by renewables resources. Proportional resonant controller provides superior performance over conventional proportional integral controller while dealing with the sinusoidal signals. Rejection of dc offset with effective harmonics elimination is provided by the improved second-order generalized integrator phase-locked loop. The speed regulation of the synchronous generator driven by a wind turbine is achieved by a sensorless field-oriented control technique. The maximum power point of each renewable resource is attained by individual implementation of perturb and observe scheme. The power sustainability is provided to the limited reach microgrid while overcoming the issues of load curtailment and PQ. Test results obtained on a developed prototype demonstrate the applicability of the control algorithms promising solution in controlling the intermittency and fluctuations related complex issues faced by the remotely located microgrid.

This article proposes an economic and power quality based control of distributed generation system in autonomous mode. The control strategy proposed here, feeds nonlinear load from photovoltaic and battery energy storage, with a diesel generator (DG) operated inon/offmode instead of continuous mode. The coordinated controls of voltage source converter and buck/boost dc/dc converter achieve the multiple objectives of harnessing maximum renewable power, maintaining battery state of charge, and continuous power supply to the critical loads, while maintaining the power quality within permissible limits as per the IEEE 519 standard. Furthermore, minimum fuel consumption and maximum fuel efficiency, are obtained while operating DG, along with maintaining its currents free from harmonics even in presence of nonlinear loads, using novel improved robust mixed norm based adaptive control technique. Simulation results and experimental validation of proposed strategy, prove its satisfactory performance under different scenarios.

The increasing renewable energy penetration has encouraged solar water pumping (SWP) as an effective solution to escalating water demand in remote areas. Despite receiving wide-spread popularity, such systems exhibit an unreliable operation due to intermittent weather conditions. As the utility grid integration enables the bidirectional power flow, it has emerged as a viable solution for uninterrupted pumping. However, since most of the SWP systems are remotely installed at radial ends of the distribution network, they encounter problems associated with abnormal grid conditions, which degrade their performance. A generalized integrator (GI) is used to deal with these issues. However, convention GI structures are incapable of effectively mitigating them. Therefore, a multiresonant cascaded second-order generalized integrator (MC-SOGI) based control approach is developed in this article to deal with these issues. The proposed MC-SOGI structure provides effective dc-offset rejection along with filtering of harmonics as well as subharmonics. Therefore, the proposed control approach is capable of effectively extracting the balanced fundamental positive sequence components even under unbalanced distorted grid voltages and maintaining unity displacement power factor under all conditions. An enhanced system efficiency is achieved by employing a permanent magnet synchronous motor (PMSM) for driving the pump. The well-known vector control technique and an incremental conductance algorithm are used for controlling the speed of PMSM and optimum power harvesting, respectively. The estimation of rotor speed and position is carried out by using voltage and current templates for eliminating the encoder thereby enhancing the system reliability and reducing the cost. The system performance is investigated experimentally and the acquired results validate the system feasibility.

This article presents an efficient method for control of a solar water pumping system consisting of an induction motor drive (IMD) with a model reference adaptive system (MRAS) based adaptive mechanism of speed estimation. An improved perturb and observe control technique is implemented to achieve maximum power point tracking. The gating signals are produced by utilizing a space vector pulsewidth modulation scheme for a three-phase inverter. An improved third order integrator (ITOI) is proposed for adaptation of flux for improvement in the performance of the drive. The MRAS is used for estimation of slip speed and synchronous speed two estimated speed signals are used to generate the motor speed. The proposed control methodology with the MRAS-based reactive power technique for the estimation of speed has improved the system stability for a wide range of drive speed. This system with a single-stage photovoltaic (PV) topology and switching logic obtained from space vector modulation operating three-phase voltage source inverter fed IMD with a pump as a load is designed and implemented in MATLAB/Simulink. The suitability of the developed system is validated through experimentation in the laboratory.

In this article, a normalized gradient adaptive regularization factor neural filter based control is presented for a three-phase grid interfaced solar photovoltaic (PV)-battery energy storage microgrid system. An incremental conductance (INC) technique is utilized for the peak power extraction of a solar PV array. A battery is connected through a bidirectional converter at dc-link of voltage-source converter (VSC), and it charges and discharges as per load variation and enhances the reliability of the system. This dc–dc converter also regulates the dc-link voltage for maximum power point tracking (MPPT). This neural filter based current controller improves the dynamic behavior of the proposed system and feeds active power to the utility grid by utilizing the feed-forward term of solar PV power under variable atmospheric scenarios. A power electronics switch is used for VSC mode shifting operation between current control in the grid-connected mode and voltage control in an islanded mode to ensure continuous and adequate power to the nonlinear load. The discrete proportional and resonant (PR) controller is used for the voltage control in an islanded mode to reduce the steady-state error between sensed and reference load voltages. The voltage controller also regulates the frequency. Simulations of the microgrid system are carried out by utilizing MATLAB/Simulink software to show the effectiveness of control technique. The performance of the system is found satisfactory for various operating conditions such as load variation, load unbalancing, and solar insolation change, and validated through test results on a developed laboratory prototype.

A serious concern regarding deterioration in power quality has emerged with the increasing integration of solar photovoltaic (PV) energy sources to the utility primarily in the scenario of a weak distribution grid. Therefore, power quality improvement of the grid-tied solar energy conversion system is paramount by implementation of a robust control technique. This paper deals with a delta-bar-delta neural network (NN) control for operating optimally by feeding active power to the loads and remaining power to the grid as a function of distribution static compensator capabilities, such as mitigating harmonics, balancing of load, and improving power factor. The control algorithm provides the ability to adjust weights adaptively in an independent manner, and hence, it offers alleviation in model complexity predominant during abnormal grid conditions along with reduction in computational time. Moreover, the NN-based control technique offers enhanced accuracy due to the combinational neural structure in the estimation process. In addition, the system performance according to the IEEE-519 standard has been verified; hence, it is proficient in maintaining the power quality. The solar-PV-array-efficient utilization is accomplished through an incremental-conductance-based maximum power point tracking technique. For validating the behavior of the proposed system, its performance is studied using simulation results. Moreover, a prototype is developed for validation, and experimental results corroborate reliable operation under nonideal grid conditions comprising of a wide range of load variations, voltage sag, and varying solar insolation conditions.

This article deals with a method for seamless transition of three-phase virtual synchronous generator, switched between off-grid and grid-interfaced modes and vice-versa. The proposed control strategy achieves two-fold advantages. First, it eliminates the need for synchronizing tools such as phase-locked-loops, and separate islanding detection techniques during unintentional islanding events; the controller is so formulated to adapt automatically during mode transitions, by inheriting synchronization and islanding detection tasks within itself. As a result, the controller does not require any control reconfiguration during mode transitions, unlike the conventional control methods. Second, it eliminates multiple feedback loops and the need for rigorous tuning of proportional-integral regulators in practical systems. In this method, only the inverter current and voltage sensors are used, and the control over grid-side static transfer switch is not mandatory. The mathematical formulation of the controller is depicted and the closed-loop stability of the system is analyzed using Eigen value stability analysis. The effectiveness of the control strategy is demonstrated through simulations and comparative analysis with the state-of-art control methods. Experimental results validate the performance of the system under different operating conditions.

This article proposes a predictive optimal switching vector controlled virtual synchronous machine (VSM) for three-phase microgrid applications, which inherits self-synchronization and islanding detection technique within the controller. A novel synchronization signal is introduced here, to modify the frequency reference in VSMs. This integrates the synchronization and islanding detection within the control loop, thereby resulting in smooth system responses without causing stability issues associated with phase-locked loops. Moreover, it totally eliminates proportional–integral (PI) regulators in the system. The traditional pulsewidth modulation controllers use cascaded internal control loops, and they demand multiple PI regulators and synchronous coordinate transformations. They are associated with finite dynamic response time by PI regulators and necessitate rigorous tuning for practical implementation purposes. The proposed controller, however, estimates the behavior of output voltages and uses a minimization criterion to produce optimal inverter switching sequences. The voltage vectors that cause the overcurrents in the inverter are inherently avoided by the minimization function within the controller. The effectiveness of the proposed control strategy is verified through simulations and experiments validate the performance under different operating conditions.

In this article, an adaptived-axis current control of a reluctance synchronous motor (RSyM) drive for a photovoltaic (PV) water pumping system has been presented, which incorporates impacts of the cross saturation in realtime to compensate the errors in the speed estimation. The response of the RSyM drive is optimized by adaptived-axis current estimation. A real-time assessment of thed-axis inductance is carried out to include the cross magnetization into consideration for improving the efficiency of the motor. Thed-axis current is varied for minimum value to provide the maximum output torque. Here, a two-stage solar energy conversion system is used to drive the centrifugal pump coupled to an RSyM drive. A boost converter is used to optimize the PV power using an incremental conductance based maximum power point tracking technique. The boost converter supplies power to a dc–ac, an insulated gate bipolar transistor based inverter through a capacitor connected across the dc link. The control of RSyM is implemented using the adaptiveid-based vector control algorithm. An adaptived-axis current is fed to the controller corresponding to the available solar irradiation, which aids in the maximization of drive efficiency and the minimization of stator copper losses. Moreover, this control improves the motor input terminal power factor. A speed/position sensorless control technique is utilized to reduce the complexity and to enhance the reliability of a water pumping system. The suitability of an implemented controller is verified through the experimental results taken on a 3.7 kW RSyM-driven PV energized water pumping system.

In this article, a new control methodology is implemented for a microgrid consisting of wind-battery and the grid, which operates both under grid-connected mode and standalone mode. A synchronous reluctance generator (SynRG) with a new mechanical sensorless field-oriented control is used in the wind energy generation system (WEGS). The major issues present in the sensorless control of SynRG, due to the use of conventional integrator or low-pass filter during the flux estimation, are addressed in this article by implementing a fourth-order flux estimator. To compensate for the intermittent nature of the power generated from the WEGS, and to improve the reliability of the system pertaining to power availability, energy storage is included in the system. Controlled operation of the battery is ensured by using a bidirectional dc-dc converter, to enhance the longevity of the battery. Voltage source converters (VSCs) connected in a back-to-back configuration with a common dc-link is selected here so that a complete decoupling is achieved between the grid and WEGS. Grid-side VSC (GSC) is controlled, so that power quality at the point of common coupling is improved. The positive sequence components of grid voltages are extracted using observers to implement GSC control to avoid the adverse effects of unbalance and harmonic content in grid voltages. Design, modeling, and simulation of the system are done in MATLAB/SIMULINK platform, and a prototype developed in the laboratory is used for real-time validation.

This paper proposes gaussian activation function based neural network control strategy of solar photovoltaic (PV) battery system assimilated to a distribution system. At the DC link of voltage source converter (VSC), the battery is incorporated through a bidirectional converter, which is charged and discharged during base load and high load demand. The active current constituent of nonlinear load current, is evaluated with neural network based control strategy, to make the grid current harmonic free and improves the power factor. The incremental conductance (I&C) method is utilized, for the extraction of maximum power point tracking (MPPT) of a solar PV array. The enhancement in dynamic performance of system in adaptable atmospheric conditions, is realized by utilizing the feed-forward constituent of solar PV power (FFSPV). The system with a neural filter control, operates successfully at solar insolation change and load perturbation. The operation of scheme under constant power mode and adaptable power mode, for steady state and dynamic states, is authenticated on a developed prototype with test results.

This paper presents sliding mode control (SMC) of switched reluctance motor (SRM) with application for light electric vehicle (LEV). A low voltage SRM is used for its application. SMC is used to deal with the non-linearity of the torque characteristics of SRM. The design of SMC for SRM is discussed in detail. The performance of switched reluctance motor drive (SRMD) using SMC is compared with that of the conventional proportional integral (PI) control technique. The SMC algorithm for speed control of SRM is analyzed, modeled and simulated using MATLAB®/Simulink platform. SMC gives better performance as the steady-state performance is achieved fast. A prototype for SRMD using a three-phase SRM is developed and test signals of the control for a change in the speed of SRMD are shown.

In pumping, the liquid discharge is directly related to the input of the pump shaft. At constant speed, the flow rate is influenced by the ripple in electromagnetic torque of the motor. This causes flow ripple in pump, which is responsible for noise in the hydraulic systems. In this paper, to improve the overall performance of switched reluctance motor based water pump drive, an investigation is made on the influence of stator pole surface parameters on output performance of the machine through finite element (FE) analysis. The analysis discloses that the stator poles other than circular pole surface, has better output performance. The bore and other dimensions are kept constant over the entire course of study. In this work, only stator pole surface is chosen since varying rotor pole surface results in uneven airgap and reduces the average torque. For the analysis, the stator pole-tip angle is varied such that the pole surface undergoes two regions i.e. from concave circular pole surface to flat-topped pole surface and from flat-topped surface to convex pole surface. The influence of the pole surface over these two regions is detailed with its effect on average output torque, torque ripple, efficiency and mechanical behavior of the motor.

In this paper, a vector-based synchronization technique is proposed for the synchronization of a solar photovoltaic (PV)-battery system to the grid. In this technique, the three-phase grid and point of common coupling voltages are transformed into two vectors in the α-β plane. Due to the absence of a phase-locked loop and feedback, the proposed technique is simple, and also instantaneous changes in the voltages are considered here. The grid-connected solar PV-battery system operates in the current control mode, while the islanded system operates in a voltage control. Experimental results are obtained on a grid-solar PV-battery system in grid-connected and islanded modes. The two transitions between these operating modes are also studied in detail. All these test results of harmonics in grid voltages and currents are found satisfactory and in accordance to the IEEE-519 and 1547 Standards.

A new topology comprising of wind-turbine-driven synchronous generator (SG) and solar photovoltaic (PV) array for renewable energy harvesting is proposed in this paper. The stochastic inputs for the proposed system are agitated using nonlinear time-dependent parameters such as varying wind speed and changing solar insolation. The speed variations are absorbed using back-to-back interfaced power electronic converters (PECs), namely, SG side converter (SGC) and utility grid side converter (UGC) with a common dc link where a solar PV array is tied directly. The power injection into the utility grid is leveled by the optimal utilization of the PECs. The SGC uses vector control (VC) for speed control of the SG and maintains unity power factor (UPF) at stator terminals. UGC acquires its switching pulses with proper application of least mean mixed-norm (LMMN) control technique. The new application of LMMN control scheme is used for the compensation of harmonics and for the extraction of fundamental load component. The dc-link voltage is regulated using a proportional integral controller. A prototype is developed and tested under different conditions of sudden changes in load, wind-velocity variations, and varying solar PV insolation. The power sharing scheme proves to be effective. The power quality issues are also addressed and mitigated effectively. The performance is exhibited for the validation of the proposed system and its control.

This paper presents a residential photovoltaic (PV) battery energy storage (BES) based three-phase grid synchronized microgrid. The objective of the proposed microgrid is to develop a fully autonomous power management scheme in utility-integrated and islanded modes. To control the PV-BES microgrid in grid-tied mode, the self-normalized estimator (SNE) control is used for power management. Besides, having seamless transfer capability, the proposed microgrid mitigates power quality disturbances caused by nonlinear loads tied at point of common coupling (PCC). Moreover, a PV feed-forward term is incorporated in SNE algorithm for the injection of active power to the utility as well as to improve the dynamic behavior of the PV-BES based microgrid. The controlled buck–boost converter enables the charging /discharging of the BES by importing or exporting the power into it. Here, the power fluctuations are suppressed by utilizing BES because of the characteristic of PV source at irradiance changes. The proposed control takes into account the extracted maximum PV power and BES conditions to supply the uninterruptible power to nonlinear loads. The efficacy of the SNE-based control for the microgrid is validated experimentally on a prototype developed in the laboratory at nonlinear load connected at the PCC.

In this paper, a novel power normalized kernel least mean fourth algorithm based neural network (NN) control (PNKLMF-NN) technique and learning-based hill climbing (L-HC) maximum power point tracking (MPPT) algorithm are proposed for grid-integrated solar photovoltaic (PV) system. Here three-phase single-stage topology of a grid-integrated PV system is used for feeding the nonlinear/linear load at the point of common coupling. A single layer neuron structure is used for active load component (ALC) extraction from distorted load current. During ALC extraction, PNKLMF-NN control very precisely attenuates harmonics components, noise, dc offset, bias, notches, and distortions from the nonlinear current, which improves the power quality under normal as well as under abnormal conditions. This single layer PNKLMF-NN control has a very simple architecture, which reduces the computational burden and complexity. Therefore, it is easy in implementation. Moreover, proposed L-HC is the improved form of hill climbing (HC) algorithm, where inherent problems of traditional HC algorithm, such as steady-state oscillation, slow dynamic responses, and fixed step size issues, are successfully mitigated. The prime objective of proposed PNKLMF-NN control is to meet the active power requirement of the loads from generated solar PV power and excess power fed into the grid. However, when generated PV power is less than the required load power, then PNKLMF-NN control meets the load by taking extra required power from the grid. During these processes, power quality is maintained at the grid. Moreover, when solar irradiation is zero, voltage source converter (VSC) acts as distribution static compensator (DSTATCOM), which enhances the utilization factor of the system. The proposed techniques are modeled and their performances are verified experimentally on a developed prototype in adverse conditions, which test results have satisfied the objectives of the proposed system and the IEEE-519 standard.

This paper deals with a quadrature oscillator (QO)-based demodulation technique algorithm to improve the power quality of a grid-tied solar photovoltaic (PV) system in the distribution network for power factor correction, load balancing, and harmonics mitigation. The QO algorithm rejects the second harmonic generated by the demodulated load current. The improved incremental conductance-based maximum power point tracking scheme is utilized to extract maximum power from a solar PV array. Simulation results illustrate the effectiveness of QO algorithm for steady state and dynamic conditions to verify the effectiveness of the proposed algorithm. Test results show reliable, robust performance, and accurate estimation under steady state, variable insolation, load unbalancing, PV to distribution static compensator (DSTATCOM) mode and DSTATCOM to PV mode. The total harmonic distortion of grid current and grid voltage lies within the limits of the IEEE 519 standard.

This paper proposes a solar photovoltaic (PV) array fed induction motor (IM) drive operated water pumping system with a speed adaptive estimator. It focuses on the implementation of a space vector modulation (SVM) of voltage source inverter (VSI) without current sensors. The motor phase currents are estimated from the dc-link current. The VSI is used for maximum power tracking and to drive an IM. A generalized integrator based flux adaptation approach is used to improve the drive performance. Moreover, a modified model reference adaptive system based speed estimation with rotor fluxes and stationary frame currents enhances its stability throughout the operating range. A modified algorithm based on incremental-conductance is proposed for maximum power point, which is used for peak power tracking at each insolation with a technique to control flow rate. The overall system incorporating a single-stage PV powered SVM based VSI fed IM driven water pump is modeled and its performance is simulated in MATLAB/Simulink environment. The appropriateness of proposed system is verified experimentally on a prototype developed in the laboratory under various operating conditions.

The renewable energy generation is the cornerstone component of the greener and cleaner ac microgrid. The high penetration of wind and solar photovoltaic energy sources in the distribution network causes unbalanced voltages, voltage rise, flicker, and internal and external uncertainties leading to disturbance and unreliable operation of the system. This paper presents the performance enhancement of the wind-solar integrated ac microgrid by implementing the adaptive frequency estimation observer (AFEO) aiming for disturbance rejection. The model uncertainties and unknown disturbances are taken care of by nonlinear active disturbance rejection controller based phase-locked loop in conjunction with the AFEO. No detailed mathematical model is required, instead the controller provides decent anti-interference and effortless parameter tuning. The fluctuations in power, interharmonics, current harmonics, and power quality (PQ) issues produced by wind and solar energy resource permeation into the grid, are addressed and mitigated by successful implementation of the AFEO for switching the grid side voltage source converter. The machine side converter obtains its switching pulses from vector control scheme. The encoderless speed and rotor position estimation of the synchronous generator (SG) driven by wind turbine is carried out by back electromotive force technique. The environmental variation of the wind and solar energy are overcome by utilizing perturb and observe scheme for optimal power extraction. Test results are obtained from the laboratory prototype under steady state and dynamic conditions including environmental changes, i.e., intermittent wind speed, solar insolation, and variable load conditions. PQ issues are addressed, investigated, and mitigated successfully.

The proposed standalone wind energy generating system (WEGS) aims to perform under variable wind speeds by utilizing two back to back connected voltage source converters (VSCs). An improved perturb and observe (P&O) maximum power point (MPP) tracking scheme for wind, a normalized fuzzy logic controller (NFLC) for intelligent control of speed of the generator and a new voltage control scheme for controlling the load voltage, are proposed in this work. A bidirectional converter maintains the DC link voltage by controlling the battery power. The improved P&O MPP reduces the oscillations near the MPP by introducing a dynamic perturbation along with the boundary conditions. The NFLC provides tracking of the reference speed at high overshoot transient conditions and narrow bandwidth. The voltage control removes the phase shift between the reference and the sensed voltages. The applicability of proposed control is validated on a developed prototype in the laboratory. Test results show the effectiveness of the proposed system.

This work presents a solar photovoltaic (PV) array fed permanent magnet synchronous motor (PMSM) driven single stage solar water pumping (SWP) system. A novel vector control scheme with reduced computational burden due to elimination of speed controller, is proposed here for speed control of PMSM. An adaptive step size perturb and observe maximum power point tracking technique is used to accelerate the response of the system. The back-electro-motive force based technique is used for encoder-less estimation of rotor position. This improves the reliability and reduces the cost of the SWP system. A single stage topology is utilized for reducing the losses and cost associated with intermediate stage DC-DC converter. The applicability of the overall system is validated through a developed laboratory prototype using digital signal processor (DS-1202). Performance of the system has been found to be quite satisfactory under both dynamic and steady state conditions.

This paper presents an economic operational control for solar photovoltaic (PV)-diesel generator (DG)-battery based microgrid, in standalone (SA) as well as grid connected (GC) modes. This system achieves multiple objectives of maintaining power quality at the grid and the DG currents free of harmonics inspite of the nonlinear loads, seamless synchronization of the grid and DG, maximizing the renewable power harnesssed, minimizing the fossil-fuel based DG power and maximizing its fuel efficiency by operating it on 80% to 100% of its rating. The total harmonics distortions (THDs) in grid current and load voltage are maintained as per the IEEE 519 standard. Moreover, the synchronization and load voltage interruption periods have been maintained within limits as per the IEEE 1547 standard. Furthermore, the battery energy management system (BEMS) is used to regulate battery current and maintain its state of charge (SOC). This system with proposed control is simulated in MATLAB/Simulink to demonstrate satisfactory performance in different scenerios.

This paper proposes a design of low cost and reliable solar powered switched reluctance motor (SRM) driven agriculture pump using a dual supply SE-CuCC (SEPIC-Cuk) converter suited for remote and rural areas. The proposed system is developed to minimize both cost and complexity, while synchronously guaranteeing optimal operation of the PV (Photovoltaic) array. A combination of SEPIC (Single Ended Primary Converter) and Cuk converter for dual output is utilized as a DC-DC power optimizing stage in between solar PV array and switched reluctance motor (SRM). Owing to an identical instantaneous duty cycle, the switching node is shared by both SEPIC and Cuk converters. In order to enhance the performance of system, the motor speed is adjusted by varying the DC-link voltage. A deviation free maximum power point tracking (MPPT) technique is used in proposed system to optimize the performance of PV array. Moreover, the proposed MPPT control has an additional advantage of regulating the flow rate of water pumping by adjusting the duty cycle of DC-to-DC converter. Overall, the proposed system provides a solution for a cost effective, efficient and maintenance free solar PV array energized agriculture pump.

This paper presents a grid coupled solar photovoltaic generation system (PVGS) which contains solar photovoltaic (PV) array, P&O (Perturb and Observe) based MPT (maximum power tracking), single-phase converters and its integration into the utility grid. A robust least mixed norm (RNMN) stochastic adaptive algorithm is used for grid tied solar photovoltaic generation system (PVGS) for improving the power quality, using on convex function of the error norms combined the least mean square (LMS) and sign-error LMS algorithms. The benefits of the PVGS are: reactive current and harmonic elimination, reactive power compensation and delivering PV power into the utility. The proposed PVSG system works in two modes, 1) PV-VSC, 2) VSC (Voltage Source Converter) is an active power filter (APF) (i.e. solar power is zero). The VSC feeds the existing MPT power from PV to nonlinear loads and the grid, with auxiliary services such as harmonics compensation with its high utilization factor. The proposed RLMN algorithm is used with reduced steady state error (SSE) and higher convergence rate. The effectiveness of the control algorithm of PVGS under different modes and environmental conditions is verified by using test results on an prototype of PVGS in the laboratory.

In this work, a novel technique based on adaptive filtering is proposed for the control of a three-phase universal active power filter with a solar photovoltaic array integrated into its dc bus. Two adaptive filters along with a zero crossing detection technique are used to extract the magnitude of a fundamental active component of distorted load currents, which is then used in estimation of a reference signal for the shunt active filter. This technique enables extraction of an active component of all three phases with reduced mathematical computation. The series active filter control is based on synchronous reference frame theory and it regulates load voltage and maintains it in-phase with voltage at point of common coupling under conditions of voltage sag and swell. The performance of the system is evaluated on an experimental prototype in the laboratory under various dynamic conditions such as sag and swell in voltage at point of common coupling, load unbalancing, and change in solar irradiation intensity.

In this paper, an adaptable dual-mode single-stage solar photovoltaic (PV) tied to a three-phase voltage-weak distribution network is proposed using a multilayer perceptron (MLP) neural network control structure. The system operates in dual modes: First, it performs as a PV supplying active power with distributed static compensator (DSTATCOM) capability thereby improving power quality simultaneously; and second, it works as a DSTATCOM alone during unavailability of the solar PV generation. The system is adaptable as it continues to operate satisfactorily for voltage-weak distribution grid that has frequent voltage fluctuations and flickers. A single-stage converter based system is utilized here, which incorporates an incremental conductance based approach for maximum power point tracking and MLP neural network structure for the extraction of fundamental components of load currents. The main advantages of MLP are its simplicity, generic nature, and ease of implementation. The system and the control algorithm are validated by using MATLAB-based simulation results and test results are achieved on a laboratory prototype.

This paper deals with a new version of an incremental conductance algorithm for maximum power harvesting (MPH) from the solar photovoltaic array, which has inherent decision taking and self-adaptive ability. The working principle of a self-adaptive incremental conductance (SAInC) algorithm is based on three consecutive operating points on the power–voltage characteristic. These points smartly detect the dynamic condition, as well as under normal condition, search the maximum power peak (MPP) zone. Moreover, using triangular analogy, it decides the optimum operating position for next iteration, which is responsible for quick MPP tracking as well as good dynamic performance. Here, in every new iteration, the step-size is reduced by 90% from the previous step-size, which provides an oscillation-free steady-state performance. The effectiveness of the proposed technique is validated by MATLAB simulation as well as tested on an experimental system. Moreover, performance of an SAInC algorithm is compared with the popular and recent state-of-the-art methods. The satisfactory dynamic and steady-state performances with low complexity as well as low computational burden of the SAInC algorithm show the superiority over state-of-the-art methods.

This paper presents an adaptive control approach based on a novel multilayer fifth-order generalized integrator (MFOGI) and single-input fuzzy-tuned proportional-integral (PI) controller for single-phase two-stage grid-connected partially shaded solar photovoltaic (PV) system, where the global maximum power point (GMPP) is tracked by using a novel human psychology optimization (HPO) algorithm. The MFOGI is used to extract the fundamental component from the grid voltage, even when the grid voltage is characterized by undervoltage, overvoltage, severe harmonics distortion, frequency variations, direct current (dc) offset, etc., on a wide range. Moreover, the single-input fuzzy-tuned PI controller is used for online PI controller gains tuning during different disturbances and dynamic conditions. To ensure a fast dynamic response, a PV feed-forward component is also included in the control algorithm as well as HPO is developed for quick GMPP tracking (GMPPT). The proposed control is modeled and simulated in MATLAB platform, as well as tested on a developed prototype in the laboratory. During simulation and testing, overvoltage, undervoltage, severe harmonics distortion, and dc offset in grid voltage, as well as insolation and temperature variations on PV array are considered. The total harmonic distortions in grid current, during the different complex disturbances and dynamic situations, are found very less, in comparison to the state-of-the-art techniques and IEEE-519 standard, as well as due to the HPO algorithm, the GMPPT time is very less, which shows the superiority over state-of-the-art techniques.

This paper deals with the design and implementation of a Luo converter operating in two different modes with an improved power quality (PQ) and flickerless operation over the universal ac mains for general purpose lighting applications. A cost-effective analog pilot-line dimming concept is incorporated and discussed in detail. The proposed dimming concept offers good PQ, even during dimming, with low cost for the energy efficient lighting solutions. The Bode plot analysis of this proposed Luo converter is presented using state-space analysis to ensure its stability with closed-loop control. The prototype is developed and tested in the laboratory for a 36-W light-emitting diode lamp load with rated current of 700 mA. The measured power factor in case of 30% dimming is 0.97 with total harmonic distortion of 8.7% only. The measured efficiency is 91% at rated ac mains voltage of 230 V.

This paper presents a fuzzy-logic-based fourth-order generalized integrator (FOGI) frequency locked loop (FLL) based control for optimal operation of solar energy conversion system (SECS) having distribution static compensator (DSTATCOM) capabilities along with supplying active power to the distribution network. The proposed SECS is multifunctional having capabilities of power factor correction, load balancing, and harmonics mitigation in a three-phase distribution system. The FOGI-FLL has higher order filtering capabilities compared to conventional algorithms. The frequency tracking capabilities of proposed control technique exhibit better performance as compared to a conventional algorithm. The comparative performance of harmonics filtering and frequency tracking capabilities is demonstrated between FOGI-FLL and various conventional algorithms. Simulation results demonstrate the behavior of the system at various conditions. To validate the proposed algorithm, a prototype is developed and test results demonstrate the reliable performance of the system at various conditions, such as load unbalancing, variable insolation, solar photovoltaic to DSTATCOM mode at abnormal grid conditions, such as distorted grid voltages, unbalanced grid voltages, voltage sag, and swell. The total harmonics distortions of grid voltages and currents are found well within limit of the IEEE 519 standard.

This paper proposes an application of a least mean-square (LMS)-based neural network (NN) structure for the power quality improvement of a three-phase power distribution network under abnormal conditions. It uses a single-layer neuron structure for the control in a distribution static compensator (DSTATCOM) to attenuate the harmonics such as noise, bias, notches, dc offset, and distortion, injected in the grid current due to connection of several nonlinear loads. This admittance LMS-based NN structure has a simple architecture which reduces the computational complexity and burden which makes it easy to implement. A DSTATCOM is a custom power device which performs various functionalities such as harmonics attenuation, reactive power compensation, load balancing, zero voltage regulation, and power factor correction. Other main contribution of this paper involves operation of the system under abnormal conditions of distribution network which means noise and distortion in voltage and imbalance in three-phase voltages at the point of interconnection. For substantiating and demonstrating the performance of proposed control approach, simulations are carried on MATLAB/Simulink software and corresponding experimental tests are conducted on a developed prototype in the laboratory.

This paper proposes a dual output Luo converter fed SRM (Switched Reluctance Motor) drive. The proposed converter generates two symmetrical output voltages. In order to obtain PFC (power factor correction) operation drive is operated in DCM (discontinuous conduction mode). The current through two output inductor is discontinuous in each switching period. The converter provides high efficiency, high power density and simple structure. The regulated output voltages of proposed converter are fed to SR motor. The SR motor here is selected for the drive due to its low cost and easy construction. The variable speed operation of proposed drive is obtained by varying DC link voltage. The proposed converter configuration has controlled DC link voltage with power quality improvement at supply. Simulation results shows the PFC operation with reduced input current THD below 5%, as per the given IEEE standard.

A three phase to five phase configured twenty pulse AC-DC converter fed 3-level modular multilevel inverter (MMLI) based vector controlled induction motor drive (VCIMD) is presented in this work. To limit the total harmonic distortion (THD) in the utility current as per IEEE-519 standard, a twenty pulse AC-DC converter is used at the input end of the proposed drive. A three phase system is converted into two sets of five phase AC voltages to achieve twenty pulses in each cycle of the supply current. At the drive end, a 3-level MMLI is used to improve the steady state, dynamic and power quality performance of the drive. An indirect vector control with sinusoidal pulse width modulation (SPWM) is used to control an induction motor and 3-level MMLI, respectively. A twenty pulse AC-DC converter fed 3-level inverter based VCIMD is modelled and its performance is simulated in Simulink/MATLAB environment to demonstrate its effectiveness for medium power application.

This paper proposes a frequency observer based control of a solar energy conversion system (SECS). The proposed control eliminates the DC offset and harmonics current and provides fundamental component of load current. The mathematical analysis of the control is corroborated and discussed in terms of filtering capabilities. Besides, capability of maximum power extraction, it integrates maximum extracted PV power to the utility by utilizing a PV feed-forward loop (PVFFL) and suppresses the load harmonics currents because of nonlinear loads connected at point of interconnection (PCI). Moreover, the incorporation of PVFFL improves the dynamic response of three phase SECS under variable climate conditions. The effectiveness of frequency observer based control are validated with numerous simulation results.

This work presents the design of an autonomous, cost-effective and efficient solar powered irrigation pump using a switched reluctance motor (SRM) drive. The proposed system utilizes a modified CSC (Canonical Switching Cell) converter for power optimization of photovoltaic (PV) array. The continuous inductor current mode (CICM) working of DC-DC converter significantly minimizes the stresses on its devices. The mid-point converter used to energize the SRM, is electronically commutated to minimize the semiconductor losses and enhances the performance of system. The selection of optimal value of turn-on and turn-off switching angles considerably reduces the torque ripple and increases the average torque of SRM drive. The speed control via variable DC link voltage helps to completely eliminate the voltage and current sensors from the motor side. The proposed water pump system is designed and modeled on MATLAB/Simulink platform and is implemented in the hardware. The adequate response of system under different environmental conditions, validates its appropriateness as a cost effective and reliable water pump system.

This study presents a robust estimation control technique of single stage grid connected solar PV (Photovoltaic) energy conversion system with distribution static synchronous compensator (DSTATCOM) capabilities. The estimated perturb and observe (EPO) based maximum power point tracking (MPPT) algorithm is used to obtain crest power from solar PV array under varying atmospheric conditions. The proposed topology is connected to the grid and also provides the power factor correction and harmonics elimination. This control algorithm contains of a DF (Differential Filter) and QSG-SOGI (Quadrature Signal generator-Second Order generalized Integrator) and it is used to extract the fundamental component of loads current for generating the reference currents. In this control algorithm, a frequency domain analysis is used for DF to extract the fundamental frequency from the instantaneous phase angle using the demodulation method. The main advantage of this control is no interdependent loop, frequency calculation, the tuning process is easy because of using demodulation method. To validate the control algorithm, tests are performed on a developed prototype in the laboratory for various operating conditions.

This paper presents an experimental implementation of a standalone microgrid topology based on a single voltage source converter (VSC) and brushless generators. The microgrid system is energised with different renewable energy sources namely wind and solar PV array. However, a diesel generator (DG) set and a battery energy storage system (BESS) are also used to maintain the reliability of the system. The proposed topology has the advantage of reduced switching devices and simple control. The implemented topology has DG set as an ac source. The wind generator and the solar PV array are dc sources which are connected to the dc link of the VSC. The BESS is also used at the dc link to facilitate the instantaneous power balance under dynamic conditions. Along with the system integration, the VSC also has the capability to mitigate the power quality problems such as harmonic currents, load balancing, and voltage regulation. A wide variety of test results are presented to demonstrate all the features of the proposed system.

In photovoltaic (PV) array, the output power and the power–voltage (P–V) characteristic of PV array are totally dependent on the temperature and solar insolation. Therefore, if these atmospheric parameters fluctuate rapidly, then the maximum power point (MPP) of theP–Vcurve of PV array also fluctuates very rapidly. This rapid fluctuation of the MPP may be in accordance with the uniform shading of the PV panel or may be in accordance to the partially shaded due to the clouds, tall building, trees, and raindrops. However, in both cases, the MPP tracking (MPPT) is not only a nonlinear problem, this becomes a highly nonlinear problem, which solution is time bounded. Because the highly fluctuating atmospheric conditions change theP–Vcharacteristic after every small time duration. This paper introduces a hybrid of “Jaya” and “differential evolution (DE)” (JayaDE) technique for MPPT in the highly fluctuating atmospheric conditions. This JayaDE algorithm is tested on MATLAB simulator and is verified on a developed hardware of the solar PV system, which consists of a single peak and many multiple peaks in the voltage–power curve. Moreover, the tracking ability is compared with the recent state of the art methods. The satisfactory steady-state and dynamic performances of this new hybrid technique under variable irradiance and temperature levels show the superiority over the state-of-the-art control methods.

In this paper, a high precision quadrature control for a single-stage solar energy conversion system (SECS) is presented with power quality improvement capabilities. The SECS uses a voltage source converter (VSC) which performs multifunctions. It harvests maximum energy from the solar photovoltaic (SPV) string and it integrates the extracted energy to the grid. In addition, it utilizes a SPV feed-forward loop to improve the dynamic response and reduces the burden on the proportional-integral controller by regulating dc bus voltage. To control the switching sequences of VSC, a high precision quadrature control is used which extracts the fundamental current from the contaminated load current. The mathematical formulation of quadrature control is corroborated by the experimental results of SECS under different operating conditions.

In this paper, a multifunctional three-phase grid-connected single-stage solar photovoltaic (SPV) system is presented using an intelligent adaptive control technique. The system configures a SPV array, VSC (Voltage Source Converter), interfacing inductors, ripple filter and three-phase grid connected nonlinear loads. The system is multifunctional as it provides functions of two different modes: 1) It acts as a SPV energy conversion system supplying active power to the loads and grid as well as a DSTATCOM (Distributed Static Compensator), and 2) It acts as a DSTATCOM alone, when SPV generation is unavailable and mitigates several power quality issues such as harmonics attenuation, voltage fluctuations and flickers, reactive power compensation, power factor correction (PFC) and load balancing. It uses a single-stage converter topology with variable step-size least mean fourth (VSS-LMF) derived adaptive control technique for VSC switching incorporating perturb and observe (P&O) method for MPPT (Maximum Power Point Tracking). The performance of the presented system is validated through experimental results obtained on the developed laboratory prototype.

This paper presents a switched reluctance motor (SRM) drive with power factor correction. Here SRM drive up to 1 kW rating fed with midpoint converter is considered. As per the requirement buck boost converter is modified to obtain two equal DC output voltages to feed mid-point converter. The speed control of proposed drive is obtained by regulated DC link voltage. Here a closed loop control based on voltage mode control is designed to obtain the reference DC link voltage. The high frequency inductors of buck boost converter are design to operate in discontinuous conduction mode, to reduce system size. The supply current THD (Total Harmonic Distortion) due to peaky nature of current in conventional configuration is brought down below 5% as per IEC 6100-3-2 standard.

This paper presents three phase single stage single source SPV (Solar Photovoltaic) grid tied system using asymmetric cascaded 27-level converter operating at fundamental switching frequency using pulse width modulation (PWM) scheme. An application of the asymmetric cascaded 27-level converter in comparison to symmetric cascaded 27-level converter have advantages viz. higher voltage levels, less distortion, low switching losses, simplicity of operation at high power that leads to the improvement of power quality of the system proposed herein. A simple decoupled current controller with incremental conductance maximum power point tracking method is used to control the proposed system. The simulated results in MATLAB validate the system under varying conditions such as solar insolations level.

This paper deals with a two stage solar photovoltaic (SPV) fed speed sensorless vector controlled induction motor drive (IMD) for water pumping system which is superior to conventional controlled motor as it is cheaper and reliable. One common practice is to estimate the flux from the terminal voltages and currents. The performance of the drive depends on the accuracy of the flux estimator. Usually the efficiency of the induction motor drive (IMD) is high around the rated load and deteriorates at partial loading. However, the efficiency can be enhanced by operating the motor at optimum flux by controlling the flux component of current. In this paper, a minimization technique is proposed to minimize the total losses to operate the drive at maximum efficiency. A modified perturb and observe (P&O) algorithm is used to track maximum power from SPV array. The smooth starting of the motor is attained by vector control of an induction motor. The system performance is simulated in MATLAB/Simulink environment and the results are compared with the conventional vector controlled IMD.

This paper proposes the real-time implementation of a three-phase distribution static compensator (DSTATCOM) using adaptive neurofuzzy inference system least-mean-square (ANFIS-LMS)-based control algorithm for compensation of current-related power quality problems. This algorithm is verified for various functions of DSTATCOM, such as harmonics compensation, power factor correction, load balancing, and voltage regulation. The ANFIS-LMS-based control algorithm is used for the extraction of fundamental active and reactive power components from nonsinusoidal load currents to estimate reference supply currents. Real-time validation of the proposed control algorithm is performed on a developed laboratory prototype of a shunt compensator. The real-time performance of shunt compensator with ANFIS-LMS-based control algorithm is found satisfactory under steady-state and dynamic load conditions. The performance of the proposed control algorithm is also compared with fixed-step LMS and variable-step LMS (VSLMS) to demonstrate its improved performance.

This paper deals with a single-phase standalone wind energy conversion system using a two winding self-excited induction generator (SEIG). The proposed controller consists of a two leg voltage source converter (VSC) and a battery energy storage system (BESS) connected at its dc bus. The VSC-BESS system is controlled using an intelligent neural network-based control (INNBC) algorithm with a dynamic learning rate, depending upon the rate of change of load current to achieve an excellent dynamic as well as steady-state response of the system. The proposed control algorithm is implemented in real time using a digital signal processor. Simulated and experimental steady state and dynamic performances of proposed SEIG are presented with the proposed controller using the INNBC algorithm. The system voltage and frequency are maintained constant in all types of steady-state and dynamic loading conditions.

This paper deals with brushless generators-based isolated wind-diesel microgrid for rural areas. Here, a permanent magnet brushless dc generator (PMBLDCG) is used to convert renewable wind power into electrical energy. A diesel engine-driven generator based on the squirrel-cage induction generator (SCIG) and a battery storage system (BSS) with a voltage source converter (VSC) deliver power to feed necessary loads. BSS provides load leveling during load variations and wind fluctuations. For such microgrid, control schemes must be accurate and robust to overcome any discrepancy, and able to provide voltage and frequency regulation to the microgrid. Here, voltage and frequency control at the point of common coupling (PCC) is achieved with affine projection-like (APL) algorithm by proper switching of a VSC. This control algorithm is also able to provide reactive power compensation, load balancing, and harmonics suppression, and therefore provides sinusoidal voltage supply. Performance of the algorithm is demonstrated with wide range of test results of developed prototype of proposed microgrid.

In this paper, a new algorithm is presented for maximum power point tracking (MPPT) of solar PV array. This method first forecasts the maximum power point (MPP) by using tangents to the power-voltage curve at two end points of an interval and then iteratively converges to the MPP by evaluating whether the true MPP lies on the left or right side of the estimated MPP. The proposed algorithm has the advantage that MPPT is achieved within an almost fixed and small number of iterations irrespective of the power level. The working of the control approach is first demonstrated through MATLAB/Simulink simulation and simulated results are then verified experimentally by the hardware implementation of a standalone photo-voltaic (PV) system.

This paper deals with control of hybrid standalone power generation using micro-hydro power turbine (MHP) coupled with a squirrel cage induction generator (SCIG) and a solar photovoltaic panel (PV), which is connected to the common DC bus of three-phase voltage source converter (VSC). The AC terminals of VSC are connected to point of common coupling (PCC) through interface inductors. A battery energy storage system (BESS) is also tied with the common DC bus through a buck-boost converter. The proposed system is mostly suitable to serve the power needs of any small size residential green building situated near a small river or cannel. Control algorithms are proposed for the three-phase VSC and the DC-DC buck-boost converter in order to extract the maximum power from PV array with single-stage conversion, to regulate the AC voltage and frequency at PCC and to improve the power quality. The effectiveness and the robustness of proposed controllers are validated by simulation using Matlab/Simulink at linear and nonlinear loads under different climate conditions.

This paper proposes a single-phase double-stage scheme for grid interfaced load compensating solar photovoltaic (PV) generating system. The scheme serves twofold objectives of alleviating power quality issues such as power factor correction and harmonics mitigation, while simultaneously extracting the maximum power generated by the PV unit. A simple notch-filtering control algorithm is designed to facilitate extraction of the real component of load current, exempting the services of a phase locked loop (PLL). The absence of a PLL reduces the system dependence on the proportional-integral (PI) controller tuning, which in turn improves the dynamic response and makes the system quite robust. The proposed solar PV generation system retains its ability of mitigating harmonics on cloudy days and also provides opportunity for night time utilization of available resources. The system has been analyzed under both linear and nonlinear varying loads using and an experimental verification of the results is carried out on a developed prototype of the system.

This paper deals with the operation of doubly fed induction generator (DFIG) with an integrated active filter capabilities using grid-side converter (GSC). The main contribution of this work lies in the control of GSC for supplying harmonics in addition to its slip power transfer. The rotor-side converter (RSC) is used for attaining maximum power extraction and to supply required reactive power to DFIG. This wind energy conversion system (WECS) works as a static compensator (STATCOM) for supplying harmonics even when the wind turbine is in shutdown condition. Control algorithms of both GSC and RSC are presented in detail. The proposed DFIG-based WECS is simulated using MATLAB/Simulink. A prototype of the proposed DFIG-based WECS is developed using a digital signal processor (DSP). Simulated results are validated with test results of the developed DFIG for different practical conditions, such as variable wind speed and unbalanced/single phase loads.

This paper presents a new topology of hybrid AC-DC standalone system based on solar photo-voltaic (PV) array and wind turbine (WT) feeding three-phase four-wire loads. The proposed hybrid system employs two back to back converters and dc-dc boost converter to achieve maximum power point tracking (MPPT). To balance the power at the PCC, the system is reinforced by BESS (Battery Energy Storage System) to keep constant frequency and voltage and to improve the power quality. The dump load is added to the system and is placed at the common dc bus to manage the extra power when the battery is fully charged. The capacitor bank is used to provide the reactive power to the doubly fed induction generator (DFIG). The proposed system is studied for various types of linear, nonlinear and dynamic loads and under varying climate conditions. The dynamic behavior of the proposed system is verified using MATLAB/Simulink.

For mitigation of power quality problems in a distribution system, it is important to estimate effecting factors which are responsible for their origin. Main objectives of neural network application in Distribution Static Compensator (DSTATCOM) are to enhance the efficiency, robustness, tracking capability according to requirements. A control algorithm based on load conductance estimation using the neural network is implemented for DSTATCOM in a four wire distribution system. The proposed control algorithm is used for extraction of load fundamental conductance and susceptance components of distorted load currents. It is implementated for mitigation of power quality problems such as reactive power compensation, harmonics elimination, load balancing and reduction of neutral current under linear/nonlinear loads. Test results on a developed DSTATCOM have shown the acceptable level of performance under balanced and unbalanced loads.

This paper presents a power factor correction (PFC)-based canonical switching cell (CSC) converter-fed brushless dc motor (BLDCM) drive for low-power household applications. The speed of BLDCM is controlled by varying the dc-bus voltage of voltage source inverter (VSI). The BLDCM is electronically commutated for reduced switching losses in VSI due to low-frequency switching. A front-end CSC converter operating in discontinuous inductor current mode (DICM) is used for dc-bus voltage control with unity power factor at ac mains. A single sensor for dc-bus voltage sensing is used for the development of the proposed drive, which makes it a cost-effective solution. A prototype of the proposed configuration is developed, and its performance is validated with test results for the control of speed over a wide range with a unity power factor at universal ac mains.

This paper presents a brushless dc (BLDC) motor drive with power factor correction (PFC) for low-power applications. In this work, the speed of the BLDC motor is controlled by adjusting the dc link voltage of the voltage source inverter (VSI) feeding a BLDC motor. Therefore, VSI is used for achieving only an electronic commutation of the BLDC motor and operates in a low frequency switching for reduced switching losses. A PFC-based isolated zeta converter operating in discontinuous conduction mode (DCM) is used for controlling the dc link voltage of the VSI with inherent PFC at ac mains using single voltage sensor. The proposed drive is implemented to achieve a unity power factor at ac mains for a wide range of speed control and supply voltage fluctuations. An improved power quality is achieved with power quality indices within limits of IEC 61000-3-2 standard.

A vibration analysis based interturn fault diagnosis of induction machines is proposed in this paper, using a neural-network-based scheme, constituting of two parts. The first part finds out the optimum network size of the probabilistic neural network (PNN) using the Orthogonal Least Squares Regression algorithm. This judges the size of the PNN, with an effort to reduce the computation. The feature extraction to model the PNN is made meaningful using dual tree complex wavelet transform (DTCWT), which is nearly shift invariant analytical wavelet transform, giving a true representation of the input space. In the second part, preprocessing using principal component analysis is suggested as an effective way to further reduce the dimension of the feature set and size of the PNN without compromising the performance. The sensitivity, specificity, and accuracy show that the vibration signatures capture the fault more effectively (especially by the axial and radial ones), under varying supply-frequency and load conditions. A comparison with traditional discrete wavelet transform proves the applicability of the proposed scheme. A comparative evaluation with feedforward neural network and naïve Bayes scheme brings out the advantage of the proposed optimized DTCWT-PNN based technique over other machine learning approaches.

The paper deals with the application of two empirical mode decomposition (EMD)-based de-noising techniques in power quality assessment. Distinct threshold parameters at a distinct level of decomposition are employed for noise exclusion. Each of the thresholded intrinsic mode functions (IMFs) are then combined together to yield a de-noised version of the signal. For enhanced performance, various noisy versions from the original signal are created and then de-noised using soft thresholds. The resultant de-noised signals are then averaged to obtain the de-noised version of the signal. In other procedures based on EMD, the signal is chopped into smaller portions each having equal length. Each signal portion is then separately subjected to EMD and then de-noised and later combined to obtain noise-free signal. These de-noised signals are then subjected to Hilbert transform for feature extraction. Fuzzy Product Aggregation Reasoning Rule-based intelligent classifier is used here for classification purpose. A comparative study is also made between S-transform-based and wavelet-transform-based de-noising techniques paper. Real-time implementation of the algorithm on a noisy harmonic signal is also given in this paper.

In this paper, different Distribution Static Compensators (DSTATCOMs) topologies, state of the art, their performance, design considerations, future developments, and potential applications are investigated for power quality improvement. These DSTATCOMs for three-phase three-wire systems and three-phase four-wire systems are developed and installed in the distribution system for many functions, such as reactive power compensation, harmonics elimination, load balancing, and neutral current compensation. This paper is aimed to explore a broad perspective on DSTATCOMs to researchers, engineers, and the community dealing with the power quality improvement. A classified list of some latest research publications is also provided for quick reference.

This paper deals with the voltage control and load leveling of permanent magnet synchronous generator (PMSG)-based diesel generator (DG) set for standalone supply system. The proposed system is composed of a PMSG and a prototype of diesel engine (DE), along with the distribution static compensator (DSTATCOM) and battery energy storage system (BESS). The DSTATCOM along with BESS is used for loads leveling and voltage control. It also provides balancing of loads, elimination of harmonics, and compensation of reactive power. The battery on dc link of voltage source converter (VSC) of DSTATCOM is used to supply the active power when the load is more than PMSG rating, and it stores the energy during light load periods. The PMSG is always loaded with an optimum load of 80%–100% of its rating. An optimum loading of DG set helps in improving the fuel efficiency of the DE and also helps in load leveling. The reference source currents are estimated using a hyperbolic tangent function-based least mean square (LMS) algorithm. This control algorithm has reduced computation and provides fast convergence rate to eliminate the effect of noise as compared with other LMS algorithms based on adaptive filtering. The voltage control, load compensation, and fuel efficiency improvement in PMSG-based DG set using BESS and DSTATCOM controlled by hyperbolic tangent function-based LMS algorithm are the main contributions of this paper.

This paper presents a new design and control for HWDBS (Hybrid Wind-Diesel-Battery System) feeding three-phase four-wire local loads. The proposed system consists of two energy sources connected to the dc bus; a WT (Wind Turbine) and a DE (Diesel Engine) based on variable speed generators. The system utilizes two back-to-back connected converters and uncontrolled three-phase converter connected in cascade with dc-dc SEPIC converter. The system uses BESS (Battery Energy Storage System) placed at the dc bus to manage the exchange of power between the energy sources and the loads. The VSC (Voltage Source Converter) of WT side is controlled in order to achieve maximum power tracking by varying the rotor speed of the SCIG (Squirrel Cage Induction Generator). In order to improve the control performance and to reduce the cost of SCIG, the MRAS (Model Reference Adaptive System) speed observer based on stator voltage and currents is adopted. The DE is controlled in order to balance the power of the system by changing its speed according to the load power demand and to minimise the fuel consumption. DE is switch off when the WT power is greater than the load power demand. The main objective of the interfacing load side VSC is to achieve a constant voltage and frequency and to compensate unbalance using symmetrical components of the load currents. The proposed system is studied for various types of linear, nonlinear and dynamic loads and under varying wind speed conditions. The dynamic behavior of the proposed system is verified using MATLAB/SIMULINK.

This paper deals with a PFC (Power Factor Corrected) Bridgeless Zeta converter based VSI (Voltage Source Inverter) fed BLDC (Brushless DC) motor drive. The speed control is achieved by controlling the voltage at the DC bus of VSI using a single voltage sensor. This facilitates the operation of VSI in fundamental frequency switching mode (Electronic Commutation of BLDC motor) in place of high frequency PWM (Pulse Width Modulation) switching for speed control. This leads to low switching losses in VSI and thus improves the efficiency of the drive. Moreover, a bridgeless configuration is used to reduce the conduction losses of DBR (Diode Bridge Rectifier). The bridgeless Zeta converter working in DCM (Discontinuous Conduction Mode) is used which utilizes a voltage follower approach thus requiring a single voltage sensor for speed control and PFC operation. The proposed drive is designed to operate over a wide range of speed control and under wide variation in supply voltages with high power factor and low harmonic distortion in the supply current at AC mains. An improved power quality is achieved with performance indices satisfying the international PQ (Power Quality) standards such as IEC-61000-3-2.

In various practical applications such as harmonic current elimination, reactive power compensation and power factor correction many adaptive filtering techniques are used for control of DSTATCOM (Distribution Static Compensator). This paper presents a comparative study of the performance of two weight updating adaptive algorithm LMS (Least Mean Square) based ADALINE (Adaptive Linear Neural Network) and Fuzzy logic based variable step size LMS used for harmonic current detection using VSC (Voltage Source Converter) based DSTATCOM (Distribution Static Compensator). Simulation results in MATLAB environment show that the convergence speed of fuzzy logic based variable step size LMS is much faster and its performance is better than LMS based Adaline under varying load conditions in DSTATCOM application for power quality improvement.

This paper deals with the design and modeling of a small scale stand-alone wind energy conversion system (WECS) using a maximum power point tracking (MPPT) controller and permanent magnet brushless dc (PMBLDC) generator. The WECS consists of a wind turbine, PMBLDC generator, MPPT controller, isolated half bridge dc-dc converter, battery, voltage source inverter (VSI) and output filter. The fuzzy logic based MPPT controller is designed for a stand-alone WECS for regulating the duty cycle of the dc-dc converter to extract maximum power. The power quality at the consumer load end is maintained using an output voltage controller, which regulates the output voltage and current of VSI. The designed system is modeled and its behavior is simulated in Matlab/Simulink using simpower system and fuzzy logic toolboxes.

This paper presents an implementation of shunt custom power device namely distribution static compensator (DSTATCOM) using a neural network based Anti Hebbian control algorithm for power quality improvement under linear/nonlinear type consumer loads. Learning based Anti-Hebbian control algorithm is used for extraction of fundamental active and reactive power components of load currents in terms of weighted signals which are used for deriving the reference source currents. This control algorithm is implemented on a developed DSTATCOM using a DSP for reactive power compensation, harmonic elimination and load balancing. Simulation and test results demonstrate satisfactory performance of proposed control algorithm for the control of DSTATCOM under time varying loads.

This paper deals with a variable speed induction generator supplying autonomous loads. The squirrel cage induction generator (SCIG) is connected to the load through back to back connected voltage source converters (VSCs) and the system is reinforced by a battery storage in order to keep the frequency and voltage constant during the variation of the loads and wind speeds. The reactive power for setting up magnetic field in this generator is drawn from the VSC. A dc-dc converter is used between back to back connected VSCs to control the battery and is maintain dc bus voltage constant. The generator torque is controlled by the generator side VSC using a field oriented control and the voltage of load side is controlled by the load side converter by means of simple d-q control. The effectiveness of the proposed system is verified using MATLAB/SIMULINK software and the results are presented and discussed for various operating conditions.

In this paper, an adaptive linear element (Adaline) based voltage and frequency (VF) controller is proposed for an isolated wind energy conversion system employing a permanent magnet synchronous generator (PMSG) for three-phase four-wire loads. A three-leg Voltage Source Converter (VSC) with a Scott-connected transformer is used as the VF controller. The Adaline based neural network is used to control the VSC of the proposed VF controller. The Adaline control technique is simple and has a fast response. The Scott-connected transformer is used for providing a path to the zero sequence current for three-phase four-wire loads. This reduces the complexity and also cost of the VF controller. The VF controller consists of insulated gate bipolar transistors (IGBTs) based 3-leg VSC with a battery energy storage system (BESS) at its dc link. The VF controller injects and absorbs both active power and reactive power by which it controls both frequency and voltage with varying consumer loads and wind speeds. The VF controller also functions as a harmonic compensator and a load balancer. The performance of the proposed VF controller is simulated using MATLAB software with its Simulink and Power System Blockset (PSB) toolboxes.

Use of distributed resources is growing in the world and India is no exception. The acceptance of such resources has increased mainly due to their modularity, increased reliability, good power quality and environment friendly operation. These renewable energy sources are currently being interfaced to the existing systems using voltage source converters (VSC's). The control of such distributed resources is significantly different than the conventional power systems with the synchronous generators due to the VSC's having no inertia. This paper deals with the modeling, design and control aspects of a distributed energy source feeding a common load in the presence of utility grid. Two control algorithms are developed for real and reactive power sharing of the load between the distributed source and the grid. The developed control schemes are tested for linear (R-L) load under equal and unequal power sharing. With suitable modifications, the control algorithms can be utilized for connecting several distributed resources in parallel.

Often in a networked AC system, substation witnessing loss of generation fails to supply the loads, which are sensitive and critical. Creation of dedicated infrastructure for support is quite costly. The paper proposes to augment a Multi-Terminal Medium Voltage DC Sub-Transmission System (MT-MVDCS) between the AC grid and AC distribution system, to enhance unlimited expansion, selection of power input, availability, stability and reliability at low cost. The control algorithm of the proposed system is discussed for control power flow, decoupled power control to input only real power from the mains, supply desired reactive power and cater to the critical load connected to the grid side witnessing the loss of generation. The indirect current control is utilized to control the Voltage Source Converters (VSC) under grid tied conditions, whereas, the VSCs are PWM controlled when supplying power to passive loads. The controller in later case regulates the AC side voltage by tight control on modulation index, and evenly compensates voltage drop on DC bus through injection of third harmonic component. Simulation based results demonstrate that proposed method provides effective control of VSC both in current controlled mode and voltage controlled mode for the aforesaid objectives. The presented results show that seamless power is provided to the critical loads connected to the grid with loss/failure of generation, without any transients in voltage.

Solid-state switch mode AC-DC converters having high-frequency transformer isolation are developed in buck, boost, and buck-boost configurations with improved power quality in terms of reduced total harmonic distortion (THD) of input current, power-factor correction (PFC) at AC mains and precisely regulated and isolated DC output voltage feeding to loads from few Watts to several kW. This paper presents a comprehensive study on state of art of power factor corrected single-phase AC-DC converters configurations, control strategies, selection of components and design considerations, performance evaluation, power quality considerations, selection criteria and potential applications, latest trends, and future developments. Simulation results as well as comparative performance are presented and discussed for most of the proposed topologies.