A multi-energy system (MES) is an integrated energy infrastructure that simultaneously models and optimizes the coupling and conversion processes among multiple energy carriers (e.g., electricity, thermal energy, and hydrogen, etc.) across diverse end-use sectors, enabling coordinated operation for improved efficiency, flexibility, and sustainability. Integrating renewable energy sources (RESs) into MES systems drives the adaptation of energy storage systems (ESSs) and the development of strategies to mitigate their intermittency. Indeed, this paper provides a sophisticated model of dispatchable ESSs in integrated energy hubs, demonstrating how storage units optimize the operational cost of combined heat and power (CHP) systems by jointly accounting for renewable generation and energy buffer states. The proposed controller employs relaxed model predictive control (RMPC), reducing computational time by managing complex decision variables more efficiently than standard MPC, making it suitable for residential energy management. Numerical simulations confirm that the control strategy effectively operates the integrated system, meeting constraints, and demands while minimizing device costs and maximizing profits.

The Virtual Synchronous Generator (VSG) represents a promising grid-forming (GFM) control approach that emulates the dynamic characteristics of synchronous generators through the implementation of virtual inertia and damping. This paper investigates the influence of including the inner current control and the current reference angle on the transient stability of VSG. While incorporating current control into the stability analysis improves the accuracy of the results, it also results in a reduced domain of attraction (DoA) for the system. To address these limitations, this paper proposed an advanced control strategy, which incorporates the standard VSG with additional feedback and feedforward functions to enhance VSG transient stability by expanding DoA. Numerical simulations demonstrate that the proposed control surpasses conventional VSG methods in terms of adaptability, stability, and reliability under various disturbances, such as three-phase faults and load increases.

Inverter-interfaced distributed generators (IIDGs) embedded in microgrids inject limited fault currents, thus imposing a challenge on the protection of the islanded microgrid. This article proposes a novel protection scheme that injects a negative phase sequence (NPS) current component from the IIDG interface control during fault conditions to facilitate fault detection and isolation. This injection is accomplished by augmenting the traditional droop controller of IIDG with a novel positive phase sequence (PPS) voltage versus NPS voltage ($V_{\text{PPS}}-V_{\text{NPS}}$) droop, designed to inject negative sequence current during fault conditions only. Differential NPS current relays are distributed at the line ends to provide fault detection and isolation. The effectiveness of the suggested protection algorithm has been tested and validated using PSCAD/EMTDC simulation software, which considers various fault conditions, such as different fault types, locations, and resistance. The suggested droop-based protection algorithm eradicates the need for a dedicated fault detection scheme and can accurately distinguish faulty and nonfaulty conditions.

Islanded operation of microgrids (MGs) with parallel-operated inverters imposes many control challenges in terms of stability and dynamic behavior, especially at contingency events. Hence, improving the dynamic performance and the stability margin is essential for robust MG operation. Therefore, the fractional-order derivative (FOD) droop controller is proposed to achieve these goals. A detailed small signal model is developed for the entire MG with the proposed controller and then used to assess the stability of the MG. The FOD and the integer-order derivative (IOD) droop controllers are applied to a benchmark MG and tuned via an optimization procedure under multiple loading conditions. The results show that the extra degrees of freedom introduced by the FOD droop facilitate pushing the dominant modes toward the required stability region. The proposed FOD droop is compared to the IOD droop, conventional droop, VOC, and virtual synchronous generator controllers under several contingency events and a reconfiguration scenario using MATLAB/SIMULINK, where the proposed controller shows superior performance. The experimental validations demonstrate the improved power-sharing performance of the proposed FOD droop controller.

The intermittency of renewable energy sources (RESs) leads to the incorporation of energy storage systems into microgrids (MGs). In this article, a novel strategy based on model predictive control is proposed for the management of a wind–solar MG composed of RESs and a hydrogen energy storage system. The system is involved in the daily and regulation service markets, characterized by different timescales. The long-term operations related to the daily market are managed by a high-layer control, which schedules the hydrogen production and consumption to meet the load demand, maximizes the revenue by participating in the electricity market, and minimizes the operational costs. The short-term operations related to the real-time market are managed by a low-layer control (LLC), which corrects the deviations between the actual and forecasted conditions, by optimizing the power production according to the participation in the market and the short-term dynamics and constraints of the equipment. In addition, the LLC is in charge of smoothing the power provided to the grid. Numerical simulations demonstrate that the strategy effectively operates the MG by satisfying constraints and energy demands while minimizing device costs. Moreover, when compared to other strategies, the controller yields fewer state switches in the hydrogen devices, thus extending their lifespan. The efficacy of the control strategy is further validated through a lab-scale MG setup.

Power electronics-based converters are the major and most vulnerable components in wind power generation systems. Converter faults will affect power quality,damage expensive equipment such asgenerators, or even pose a massive threat to the entire power grid. Fault diagnosis is considered as a powerful means to improve system reliability and reduce maintenance costs. Existing data-driven fault diagnosis methods related to improving feature extraction approaches to obtain high diagnostic accuracy are mostly based on single-scale feature of signals; this neglects the potentially valuable information of other scales. This paper proposes an algorithm of Dempster-Shafer and Deng entropy fusion multi-scale approximate entropy (DSDEMAE) for wind power converter fault diagnosis. Firstly, it calculates the multi-scale approximate entropy of fault signals, mining more potentially valuable information. Secondly, Dempster-Shafer is used to fuse features of various scales and effectively handles the conflicts and uncertainties between different features. Finally,Deng entropyis adopted to measure the uncertainty to adjust weight distribution, reducing the influence of highly conflicting features and mutually benefitting features of different scales. Extensive experimental results on simulated and experimental data demonstrate the effectiveness of the proposed algorithm. Compared with advanced methods, this method can diagnose the faults with higher accuracy and stronger robustness.

A new type of filter/extractor named independent time-delay signal cancellation (itDSC) method is proposed in this article. Unlike conventional harmonic sequence filter (HSF) designs, the phase modifying and vector recovering stages of the proposed itDSC are separately set with single targets to make time-delays independent from the targeted HS indices and fundamental period. Consequently, the proposed HSF is more flexible in design, more robust and accurate in performance as well as faster in dynamic response compared to the conventional ones. A new phasor representation of an arbitrary order and sequence is first introduced for three-phase signals by using only a single integer-index-number (h). Then, a generalized principle of filtering/extracting arbitrary HS is proposed where the conventional time-dependent methods are specific cases. Last, new designs with independent time-delays are proposed to avoid the drawbacks of dependent time-delays and improve the filter performance in the applied systems. Comparative performance and extended applications on fundamental-frequency positive-sequence extraction used in power converter control areas are presented. The experiments show the superiority, application potentials, and challenges of the proposed method in the power converter control area.

Ensuring the cost-effective operation of an unbalanced islanded microgrid (UBIMG) hinges on achieving a proportional power sharing relative to the capacity of the connected distributed energy resource units (DERs). However, inherent characteristics of UBIMG, such as heterogeneous line impedance and unbalanced loads, inevitably result in mismatching the reactive power-sharing (RPS) among the droop-controlled DERs. As a solution, this article introduces an advanced control scheme that combines unsymmetrical per-phase droop control with unsymmetrical per-phase virtual impedance, referred to as unsymmetrical per-phase droop-virtual impedance control (USPDVIC), to enhance the RPS among DERs within the UBIMG. To determine the settings of the proposed control scheme, this study formulates a multiobjective optimization approach to minimize the average generation costs and mismatching in the per-phase RPS within the UBIMG across a set of operating states simultaneously. The performance of the proposed USPDVIC is comprehensively evaluated within a parallel architecture UBIMG and a radial UBIMG-based IEEE 13-bus, IEEE 34-bus, and IEEE 123-bus benchmark systems under various states of operation. These states include changes in loading conditions, plug-and-play of DERs, and system reconfiguration and partitioning. The results, along with comparisons to existing literature, provide solid evidence for the effectiveness of the proposed control scheme in improving the per-phase RPS among the parallel-connected and dispersed DERs within UBIMGs.

Electric vehicle charging stations (EVCSs) heavily rely on communication systems, making them vulnerable to cyber uncertainties such as communication delays and False Data Injection (FDI) attacks. In this study, the techno-economic evaluation of the EVCS based on the developed and data-driven Takagi-Sugeno-Kang Fuzzy System & Multi-Agent Deep Reinforcement Learning (TSKFS&MADRL) method is presented to detect and compensate for cyber uncertainties such as FDI attacks and communication delay. In addition, the proposed approach provides a fast dynamic response and enhances the resilient operation of EVCS in the presence of FDI attacks. First, the target points of hackers such as communication systems and transducer sensors are modeled, and then, using the Euclidean norm theory, weighted least square error method, and residual error technique resulting from comparing measured data with reference values based on probability distribution functions, FDI cyber-attacks are detected. Then, the network control and recovery requirements are enabled by the proposed controller based on the TSKFS&MADRL method. The proposed approach has been implemented in the IEEE 33 bus network. The experimental operating cost is 7.33% less than the RL method and 12.15% less than the CNN method. Also, the experimental results of the proposed method show a 40% detection time reduction compared to other methods.

A high gain multilevel inverter (HGMLI) based solar power transfer system (SPTS) is proposed in this paper. The five-level symmetrical source topology consists of eight semiconductor switches and two non-isolated DC sources. The HGMLI is comprised of a multilevel generator unit and a polarity alternating unit. Four switches in the circuit operate to achieve unipolar multiple levels and another four switches change the alternate polarity to get the desired five-level AC output voltage. Four switches are operated in level-shifted pulse width modulation and the other four are at the fundamental frequency. Moreover, the polarity alternating switches are operated at zero voltage levels to reduce the switching losses. A voltage booster circuit extracts maximum power from the photovoltaic (PV) array and exhibits a high gain in the voltage transformation for obtaining the desired DC-link voltage even for a low input voltage. The MLI is controlled by a second-order generalized integral-based filter to integrate active power to the grid. At the point of common coupling (PCC), a nonlinear harmonic load is connected, and its impact on grid power quality is mitigated by the SPTS operation maintaining within IEEE limits. Hence, maximum power extraction, active power injection, and power quality enhancement are the major objectives of this work. The proposed system performance is validated at different operating conditions with extensive analysis in the MATLAB/Simulink model.

Low voltage ride through (LVRT) is one of the most important capabilities that modern renewable energy conversion systems should have to support grid voltage during fault conditions. Nevertheless, testing real LVRT scenarios experimentally is challenging. This paper examines the implementation of LVRT studies in laboratory scale. It uses a series inductance to mimic the effect of grid impedance, which makes voltage control possible and visible at the point of common coupling (PCC). Moreover, it analyzes the effects of overvoltage protection (OVP) using chopper resistor, the effects of the controllers, and the effects of faults magnitude and duration on the LVRT performances. A laboratory scale permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) is used to verify the LVRT studies. It is found that the examined LVRT effects influence the application of accurate LVRT studies in laboratory scale experiments.

This paper presents an efficient analytical technique to identify the optimal location and sizing of the distributed generation (DG) and shunt capacitor (SC) into a radial distribution system (RDS). The main objective of allocating DG and SC is to reduce the power losses which leads to improve the overall voltage profile with considering equality and inequality constraints. The DGs and SCs are placed at the bus that gives minimum power loss, while the optimal size is determined using the analytical technique. Moreover, a load variation with 50%, 100%, and 150% respected to the base case is studied to show the efficiency of proposed algorithm. Overall case studies are carried out using IEEE 69-bus RDS and the obtained results are compared with other optimization techniques used in the same manner.

SSSC is an important member of Flexible AC transmission Systems (FACTS) device family. It is considered to be a superior series FACTS device, as it has the ability to control the flow of both active and reactive power in a transmission line. Therefore, it is important to have a model for this device to facilitate studies involving it. This paper presents a simple SSSC model in NEPLAN power system analysis software, where it mainly depends on power injection method. This model is developed so that it can be utilized in studies concerned with SSSC in NEPLAN software, as the software suffers a lack of such a model. This model is tested on the standard IEEE 30 bus and IEEE 14-bus systems in different conditions to ensure its performance, quality in various load flow calculations and effectivity in NEPLAN software.

Linear quadratic regulator is an effective control technique that can provide active damping to grid-connected inverter with LCL filter. To meet the design requirements, the designer can alter the response and control expenditure by choosing the cost matrices of the state and control signals. The selection of these matrices relies on experience and is usually done empirically. In this paper, swarm intelligence is utilized to design a non-diagonal state cost matrix that outperforms an empirically tuned one. Furthermore, diagonal cost matrices are designed such that the total harmonic distortion requirements are met at multiple loading conditions.

False Data Injection (FDI) is one of the most dangerous attacks on cyber-physical systems as it could lead to disastrous consequences in the operation of the power grids. In this paper, a comprehensive investigation of the (FDI) attacks in smart grids is presented. A detection algorithm is utilized in analyzing the FDI attacks in real-time environment based on Principle Component Analysis (PCA). It provides an adequate solution to the FDI problem for its ability to extract information about correlation of the collected measurements. This provides a more accurate and sensitive response than the previous FDI detection techniques. Furthermore, the light computations associated with this algorithm make it a very good candidate for real-time environment testing. The results concluded in the paper illustrate a very promising future for the PCA-based realtime FDI attack detection schemes.

Switched reluctance motor (SRM) has various advantages which makes it an excellent candidate for many applications; nevertheless, its main drawback is torque ripples. This paper aims to enhance the SRM operation by reducing its torque ripples without the need for expensive and sophisticated physical changes in the motor materials or design. The SRM converter firing angles are optimized to produce the lowest possible torque ripples. The response surface method (RSM) is used to obtain the SRM optimization function that relates torque ripples with firing angles, and grey wolf optimizer (GWO) is used to minimize this function. The objective function convergence speed using the proposed GWO is compared with genetic algorithm (GA), and it is found to be faster than GA. Simulation and experimental results show the effectiveness of the proposed approach in enhancing SRM operation by providing the SRM converter firing angles that result the minimum feasible torque ripples.

Recently, the control problem of a quadrotor unmanned aerial vehicle (UAV) has been undergoing massive research. In this paper, a nonlinear disturbance observer-based (NDO) controller is proposed for attitude and altitude control of a quadrotor, in order to estimate and compensate disturbances that are imposed naturally on the quadrotor due to aerodynamics and parameter uncertainties. It is demonstrated herein that the proposed observer can estimate external disturbances asymptotically. Subsequently, it is employed with an input-output feedback linearization (FBL) controller - rendered as a baseline controller - to achieve a composite controller capable of rejecting external disturbances rigorously. The resulting controller is compared with a FBL controller that is equipped with an integral component. Simulation results demonstrate a superior performance using the former controller for disturbance rejection.

This paper addresses the time-delay effects of the wide-area monitoring and control systems (WAMCS) in smart power grids which may critically impact system stability. The main purpose is to conduct a detailed delay analysis of the WAMCS in case of grid contingences. This analysis is performed via an advanced WAMCS testbed where a flexible ac transmission system (FACTS) device is utilized and controlled via a wide-area controller (WAC). Phasor measurements units (PMUs) are adopted to collect the real-time measurements for the WAC. The testbed results from an interface of four main segments known as the WAC; the actual FACTS device, the local area controller, and the power grid system along with the PMUs are simulated via a real-time digital simulator. To mimic the real case scenario, both hardware-in-the-loop and software-in-the-loop schemes are adopted in the experimental testbed, considering time-delay effects. The results obtained clarify the effect of delay in WAMCS in case of smart grid contingences.

This paper develops selective strategies for Neutral Point Clamped Multilevel Inverter (NPC) in a microgrid application with load current decomposition based on Synchronous Reference Frame (DQ) method. The 3-level NPC inverter is investigated as widely used topology for medium and high power applications. In addition to the current injection into the grid, the 3-level NPC DG inverter is also being used to improve the power quality at point of common coupling, mitigating load current disturbances and improving power quality. For the islanded mode of operation, the control of the DG inverter involves the regulation of the instantaneous load line-to-neutral voltage magnitude, i.e. va, and frequency m. Single loop and multiloop voltage control scheme based on inductor filter current feedback are developed to regulate load voltage/frequency for a varity of load conditions. The control strategies are implemented in abc-frame. The principles supporting the selective control strategies are discussed and analyzed and the effectiveness of the control metod is demonstrated through digital simulations conducted by means of PSIM.

This paper presents a three phase grid connected DC/AC inverter with active and reactive power (VAR) control for medium size renewable and distributed DC energy sources. The inverter, based on a voltage sourced inverter (VSI) configuration, allows the local residential energy generation to actively supply reactive power to the utility grid, at the same time, this topology allows to work this installation in stand-alone (grid disconnected) mode maintaining nominal and clean voltage at nominal power. A low complexity grid synchronization method was introduced to generate direct and quadrature components of the grid voltage in a simple and computationally efficient manner in order to generate a synchronized current reference for the current loop control. Simulations were performed on Matlab/Simulink platform and a prototype was also developed in the lab to prove the effectiveness of the designed filter, controllers and grid synchronization method. The dSPACE hardware in the loop (HTL) was used, providing a good solution for laboratory implementation.

This paper provides an experimental evaluation of a four phase Floating Interleaved Boost Converter for a photovoltaic power system application. This converter offers improved efficiency and voltage gain, while having lower input current ripple than other DC-DC boost converters. A dual loop, discrete, linear feedback was developed to regulate inductor currents and output capacitor voltages. Maximum Power Point Tracking capability was included. Results of all control functions were used to validate the control development, and point to areas for further improvement.