Abstract Electricity price has been the focus of electricity market participants from the beginning of electricity markets as the price reflects the prevailing market conditions. Its importance and volatile behavior have motivated many research works in the area of electricity price forecasting. While qualified electricity price forecasting methods have been presented in the literature, prediction of price spikes, as a distinctive and crucial aspect of electricity price time series, has been less researched and still remained as a critical challenge. In this paper, a new deep learning-based framework is proposed for price spike occurrence and value prediction. Three deep generative models, for data generation, rebalanced data clustering, and point value forecasting, are combined in this framework. In the first step, the Rebalancing Variational Autoencoder (RebalVAE) is proposed to rebalance the data using a mixture of discrete and continuous variables. After that, the Clustering Variational Auto-Encoder (ClusVAE) with a new clustering-specific loss term from the mutual information theory is proposed to make an accurate and automatic clustering. Subsequently, a deep diffusion model is applied to each cluster for price value prediction. This model, namely Diffused Predictor Variational Auto Encoder (DiffPredVAE), includes a Transformer Encoder, embedded in both Encoder and Decoder networks of a VAE, and is equipped with a new loss function. Results on two real-world datasets (in five cases) confirm the superiority of the proposed price spike prediction model compared to various other models.

Renewable energy technologies have made a profound impact on the global electricity sector by providing consumers with reliable and continuous power. In developing countries, one of the most critical research areas involves leveraging renewable energy sources to meet the energy demands of electric vehicle charging stations. This research investigates the technical and financial viability of grid and renewable-powered energy systems for an environmentally sustainable electric vehicle (EV) charging station for Ahmedabad (Gujurat), city of India. The presented setup is subjected to an economic analysis for satisfying the charging requirement of the EV load. The system is designed in such a way that the power exchange takes place between the grid network and different components of the energy system. The optimal sizing of the system component is performed to minimize the levelized cost of electricity and total net present cost while keeping the probability of power supply failure within acceptable limits using a novel hybrid particle swarm optimization and gray wolf optimization algorithm. the optimum values of the total net present cost and levelized cost of electricity for the city of Ahmedabad are 222762.80 $ and 0.023 $/kWh, respectively. The envisaged system could help to reduce the dependence on the overstrained grid, especially in developing nations.

Due to the rapidly increasing number of electric vehicles (EVs) in society, a robust charging infrastructure is essential to reduce dependency on fossil fuel generation. This article examines the technical, economic, social, and environmental viability of charging facilities for electric vehicles. It focuses on a parking lot integrated with photovoltaic distributed generation and a battery energy storage system to facilitate convenient EV charging and reduce carbon emissions. Moreover, energy management techniques (EMT) are employed to balance the active power demand between sources and loads by controlling the charging and discharging of the battery energy storage system (BESS). For a comprehensive analysis of economic benefits, mathematical models for the costs of charging facilities, the income of the parking lot, and social and environmental impacts have been developed. Additionally, the financial advantages of PV-BS PLs are evaluated, considering terms like changes in subsidies, installation costs, and the expenses of BESS and PV plants. The findings indicate that PV-BS PLs offer substantial social and economic benefits, with an estimated payback period (PP) of approximately five years, delivering 20% grid benefits and 71% societal benefits.

Power systems, consisting of interconnected components with dynamic properties, necessitate stable operations to ensure reliability. Small signal stability assessment (SSSA) plays a vital role in detecting and correcting small disturbances in power systems to maintain power system stability during unforeseen contingencies. While traditional model-based methods are accurate. However, these methods are computationally intensive. Machine learning (ML) techniques have emerged as efficient alternatives, offering faster and sometimes more accurate stability analysis. This paper evaluates various ML models, including neural networks and ensemble methods, for evaluation of SSSA using datasets containing eigenvalues and operating points. Additionally, it proposes a novel methodology for ensuring SSSA assessment using federated learning, addressing privacy concerns associated with data sharing in power systems research. By harnessing ML algorithms and real-world data, this study contributes to advancing SSSA methodologies, highlighting the potential of ML in enhancing power system stability assessment. The test system undertaken for this study is IEEE-14 bus system.

Speed sensor faults are very common in electric vehicle (EV) applications, often disrupting system performance due to the reliance on speed sensor data by the electric drives. Consequently, fault-tolerant control approaches require robust observer structures capable of functioning effectively during faults, swiftly identifying and reconfiguring failures. Thus, this paper presents a novel fault-tolerant control design leveraging a synergetic observer (SO) to substitute the speed sensor in the event of fault. Comparative analysis with a super-twisting sliding mode observer (ST-SMO) highlights the proposed observer's superior performance in terms of tracking accuracy and ripple reduction. The presented simulation results demonstrate promising performance of the proposed observer for fault-tolerant control in EV applications.

The transportation sector is a significant contributor to global carbon dioxide emissions. While electric vehicles (EVs) offer a solution to reduce these emissions, charging them with electricity from conventional sources can negate their environmental benefits. To address this, charging EVs with renewable energy sources is proposed, facilitated through the development of smart cities and smart homes. In this paper, a robust optimization problem is proposed to minimize the billing cost of the smart home while the thermal preferences of end-users are addressed. Also, in order to protect the upstream energy system with the high variation of smart home net loads with respect the renewable energies, flexibility constraints are added to the model. The upstream grid price uncertainty is addressed by the robust optimization approach. The proposed approach is a Mixed Integer Programming (MILP) problem and the CPLEX solver in the GAMS environment is used to solve the model. The results show that the flexibility constraint program has a significant impact on the energy cost of the smart home.

Conventional techniques used for current harmonic assessment suffer from limitations of inaccurate detection of total harmonic distortion due to inherent delay produced by the sampling window. To overcome this limitation, this paper proposes an AI model to predict harmonic distortions in grid current caused by interfaced renewable energy sources like PV and EV charging stations. The single AC source and single nonlinear load are simulated in MATLAB/Simulink, creating harmonics in the charging current and voltage supplied by the AC source. Sufficient data corresponding to various harmonic components ranging from third to twenty-one is generated using a simulation study. The generated data trains the machine learning model using different regression-based algorithms. Regression algorithms like Random Forest, XGBoost, and CatBoost showed strong accuracy in predicting harmonic distortion in grid current. The stacking strategy is used to combine the best-performing algorithms, which used linear regression as the meta model. The result captured from stacking shows the highest accuracy. This accuracy helps in the accurate assessment of harmonic components in charging drawn by nonlinear loads like EV chargers. The machine learning regression techniques precisely estimate various harmonic components. The paper follows IEEE-519 standard for harmonic control in electrical distribution networks.

In the existing power system architecture of military aircraft (such as F-35), electrical loads are fed from two 270V-HVDC buses. These two HVDC buses are completely isolated from each other. In existing architecture, there is no possibility of power transfer between the two buses. This inability reflects as overdesigning of the system to meet the dynamic loads and possible power quality deterioration during operation (occurring due to unequal loading of the two HVDC buses). This paper attempts to address this inability by introducing the concept of dynamic power balancing between the buses. As military aircraft design criteria are sensitive to weight and size, the introduction of the proposed feature must not add additional weight to the system. To ensure this, the authors have studied the existing architecture and have attempted to replace the two 270V to 28V Dual-Active Bridge (DAB) converter (used for charging the 28V battery) with the proposed Triple-Active Bridge (TAB) converter. This converter must be capable of achieving power balancing in addition to the conventional 28V battery charging operation. To achieve this, a modulation strategy to achieve bidirectional power flow and soft-switching is also discussed. Simulation results verifying the feasibility of the proposed converter and control are also presented.

This paper proposes a new structure of high gain DC-DC converter named as "Double Duty Converter (DDC)" with voltage boosting module and showing the wide voltage gain control. The proposed converter is operated with three switches which are controlled by two different duty pulses. Therefore, the voltage gain of the proposed converter depends on the two pulses which allow the converter to operate with high voltage gain at a low duty ratio. The key features of the proposed configurations are: i) three switches are controlled by two different duty cycles for wide voltage control, ii) continuous input current, iii) lower voltage stress on the switch, and iv) high voltage gain. Mathematical analysis, operational modes of the proposed converters and effect of the Effective Series Resistance (ESR) of inductors and diodes on voltage gain are presented in detail. Finally, the proposed converter configuration is validated using detailed simulation studies.

The main application of MLI is for motor, adjustable drives, distributed generation, hybrid system, and microgrid. The usual H-bridge inverter topology has some issues like it cannot produce multiple voltage levels, high switching losses, harmonics, voltage stress is high. Later on, multilevel inverter overcame this problem. The MLI requires a large number of diodes, capacitors, switches, and sources to produce multilevel output. The proposed work presents the modified multilevel inverter for standalone PV system applications. It generates 5-level output using less number of switches. As a result, the complexity issue of cascaded MLI is overcome. The THD factor is also lowered by the implementation of the SPWM technique of carrier frequency 10 kHz and reference signal of 50Hz. The DC Source required for MLI is given from the boost converter, which generates multiple output. In the first part, the simulation of a boost converter the key feature of this converter is that it produces two outputs of the same voltage rating. In the second part 5-level multilevel inverter using six switches, two sources. The converters are simulated in MATLAB software.

The proposed work presents a new Modified Boost Converter (MBC) for renewable energy applications. The proposed MBC is intended for high voltage applications and operates in the closed-loop control to maintain the desired constant voltage level. The voltage gain of the projected converter is high as compared to the conventional and recently addressed DC-DC converters with few numbers of components. The key features of the MBC are single switch topology which makes the simple control circuitry. By extending the voltage multiplier level, the voltage gain of the MBC can be increased and shows the balanced voltage across each output capacitor. Additionally, proposed converter have the continuous input and output current characteristics. The working principle and mathematical analysis of the MBC is done by considering the components to be ideal. In addition to that, the detailed state-space modeling of the converter is represented along with the controller design. All the analysis is done in Continuous Conduction Mode (CCM). The simulation results validate the feasibility of the proposed converter.

This paper presents Third Harmonic Operation (THO) of Current Fed Parallel Resonant Push-pull Inverter (CFPRPI) for Inductive Power Transfer (IPT) systems. THO is proposed for CFPRPI to achieve higher voltage ratio with lower switching frequency, which is essential for low input voltage IPT systems. The IPT system is considered based on PS compensation method, i.e. parallel compensation for the primary side and series compensation for the secondary side. Moreover, a phase-shift control method is presented based self-oscillating tuning loop for output voltage or power regulations. The tuning loop and IPT system are modeled and formulated in THO mode. To verify the validity of the proposed method, a laboratory prototype with resonant frequency of about 120 kHz and maximum output power of about 50 W has been implemented.

This paper aims to improve the power and voltage quality of a new multilevel inverter which contains a smaller number of switches in the specified voltage levels. The single phase of the proposed inverter includes 8 electronic power devices with three dc voltage sources for the seven-level waveforms. Selective harmonic elimination (SHE) technique has been used for the dominant harmonic elimination. The results of the proposed structure with traditional topologies and similar topologies show that, in terms of switch number, driver number, and the total blocking voltage, the proposed structure was superior to the previous versions. This topology is studied by simulations in the environment of PLECS.

This paper presents an improved single phase high frequency isolated gamma Z-source inverter (ZSI) with clamped diode. It consists of a high frequency transformer between the inverter bridge and load. A lossless snubber diode is employed to provide voltage clamping across the DC-link voltage to overcome the voltage overshoots caused by the leakage and stray inductances of the magnetic components. The proposed concept retains all the existing benefits of ZSIs which are buck/boost function, single stage power conversion, immunity from dead and overlap times, and increased reliability. Together with high frequency transformer makes it a good candidate for solar PV applications. High frequency isolation has many benefits in terms of protection and safety. In addition to these it can provide immunity from dc-circulating current without the need for external bulky line transformer. The proposed topology can increase gain with maximum value of modulation index which is currently not possible with any other impedance source topology. The described benefits and features of the proposed topology are verified through comprehensive theoretical analysis, simulations and prototype based hardware experiments.

In this work, a novel LCL filter topology for non-isolated Photovoltaic (PV) applications is developed. This topology has the ability to trap the High-Frequency (HF) Common Mode (CM) current inside the PV inverter. Consequently, suppressing the ground leakage current. Furthermore, the proposed solution is immune to ground leakage current resonance issues (i.e. effective for applications where the utility grid is characterized as a weak grid). Moreover, the theoretical analyses were validated on a 10 kW grid-connected PV system. The results demonstrated that at resonance conditions, the proposed system reduced the leakage current root-mean-square (RMS) value from 1 A to 25 mA. Thus, satisfying the VDE standard's leakage current limit.

In this paper, three-phase induction motor supplied by multilevel quasi impedance source inverter (qZSI) is controlled with V/f technique. Application of pulse width amplitude modulation (PWAM) technique for controlling the multilevel qZSI is implemented. In PWAM, modulation index which is defined as the ratio of peak of modulating signal to the peak of carrier signal always remains unity. Due to this, the voltage available at the output of the inverter is not controlled in correspondence to V/f control during starting of induction motor. In this paper, a novel control algorithm is proposed which helps in achieving starting of induction motor without starting current transients. Performance of Vlf-controlled induction motor drive obtained with different modulation techniques are compared by simulating the three - phase induction motor drive using Simulink. Comparison of switching losses with these methods is also presented. Experimental prototype of closed loop controlled three - phase seven - level qZSI is developed and tested with RL load.

This paper presents a hybrid method of active power and reactive power control strategy with Quasi Z-source inverter (QZSI) in single phase grid connected photovoltaic (PV) systems. The maximum power from the PV panel is extracted and most of it is supplied as active power to the grid. The major portion of required reactive power exchange to the grid is done by means of thyristor switched capacitor (TSC) and thyristor switched reactor (TSR) to improve the generation capacity of the PV system. In the proposed topology inverter shares the minimum reactive power and large change in reactive power will be delivered/absorbed by the TSC-TSR to get smoother operation in reactive power control. The DC voltage controller and the AC current controller is discussed in brief. The mathematical analysis for grid synchronization method is presented in detail. The control algorithm for active power and reactive power is analyzed and discussed in the paper. The simulation results are shown for validating the proposed concept.

In this paper, discontinuous space vector pulse width modulation for a five-phase quasi Z-source inverter is presented. Two schemes are introduced for the continuous SVM of five-phase qZSI (SVQ1 & SVQ2) and two schemes of discontinuous SVM (DSVQ1 & DSVQ2) are proposed SVQ1 method is based on subtracting the shoot-through state interval from the zero state interval only. While SVQ2 subtract the shoot-through state interval from all active and zero states intervals. The discontinuous SVQ schemes are based on eliminating one of the zero vectors which will lead to 20% reduction in number of switchings. These schemes are simulated using Matlab/Simulink. An experimental setup is developed to validate and test the proposed schemes.

Quazi Z-Source inverter (qZSI) is a promising inverter topology that can buck or boost input voltage without a DC-DC converter and hence can be used in transformerless configuration. This is a high efficiency solution because of single stage processing and conversion. In this paper a novel modified qZSI topology is proposed and new modulation technique is presented to reduce common mode leakage current that is generally present in non-isolated transformers feeding utility grid. The proposed inverter offers a, high efficiency and a high reliability solution in a single-phase solar photovoltaic system for grid integration. Presented topology, (1) uses phase-leg shoot through for boosting the DC voltage to the required level which eliminates the additional DC-DC converter, (2) eliminates the PWM dead-time and provides freewheeling through additional switches (smoothens output AC grid current), (3) minimizes leakage current, (4) avoids body diode conduction for main devices increasing the efficiency of the system because body diode have poor reverse recovery characteristics, (5) effectively utilizes magnetic components, (6) common mode leakage current will be reduced to 0.2% of the rated current which is negligibly small. Simulation and experimental results are verified for a 120V (peak), 15A (peak) at 0.99pf.

Motor drive system is considered the most important asset in industrial applications. Detection of broken rotor bars has long been important but difficult job in detection area of incipient motor faults. The need for highly efficient motor control drive systems becomes more and more important. Motors are controlled in closed-loop or open-loop modes of operation. This paper develops a novel approach for fault-detection scheme of broken rotor bar faults for three-phase induction motor using stator current signal. The empirical mode decomposition (EMD) combined with Wigner-Ville distribution (WVD) has been employed for the analysis of stator current signal. Artificial neural network is then used for pattern recognition of broken rotor bar signature. The proposed algorithm offers high performance in detecting broken rotor bar fault. Both simulation and experimental results show that stator current-based monitoring in conjunction with Winger-Ville distribution based on EMD yields a reliable indicator for detection and diagnosis of broken rotor bar faults using artificial neural network. All simulations in this paper are conducted using finite element analysis software. Experimental results validate the simulation and analytical results.

This paper proposes space vector pulse width modulation (SVPWM) technique for a direct matrix converter with five-phase input and three-phase output. This topology of matrix converter is developed exclusively for feeding three-phase stiff grid system with five-phase variable input supply. One of the presumed applications is wind electric energy generation system. The paper presents the complete space vector model of the five-to-three-phase matrix converter topology. The major breakthrough of the proposed control scheme is the enhanced input to output voltage transfer ratio. The maximum output phase voltage can go up to 104.4% of the input phase voltage in the linear modulation range and hence can act as a boost converter. The space vector model yields 215total switching combinations, which reduce to 125 states (for SVPWM implementation) considering the imposed constraints, out of which 120 are active and 5 are zero vectors. However, for SVPWM implementation only 30 active and 5 zero vectors can be used. A generalized formula for maximum modulation index for n-phase input and 3-phase output is also formulated. The SVPWM algorithm is presented in the paper, and the viability of the proposed solution is proved using analytical, simulation and real-time approach.

In an open-end winding drive topology two voltage source inverters (VSIs) are connected to the two separate sets of terminals of the stator winding. The most frequently investigated topology uses two two-level VSIs that require two isolated dc-bus supplies. The other alternative is to use a single dc-bus voltage source, which then requires elimination of the common-mode voltage to avoid the zero-sequence current flow. This paper investigates a seven-phase open-end winding topology, with the two two-level VSIs fed from a single dc supply. Hence, in addition to zeroing on average voltages in all non-flux/torque producing planes, it is necessary to restrict the zero-sequence current flow, which would be caused by the common-mode part of the phase voltages. The switching states providing zero common-mode voltage (CMV) are indentified and the corresponding space vectors determined. A correlation between these space vectors and the space vectors that are used in standard seven-phase two-level VSI modulation is investigated and a simple carrier-based PWM is proposed, based on this correlation. The method is implemented in simulations and experiments and the results are presented to verify the concept.

This paper proposes technique to obtain ten-phase output from three-phase input supply system using special and novel transformer connection. With the proposed supply system, pure ten-phase sine-wave voltage/current is obtained that can be used for the motor testing purposes and obtaining dual five-phase supply. The proposed transformer connection yield ten-phase output while the input is grid supplied three phases. Another application area of such transformer can be ten-phase power transmission and rectifier system. In this work an open ended five-phase induction motor is run on the sinusoidal output of a three-to-ten-phase converting transformer. Also two five-phase induction motors with single sided connection are supplied from the proposed transformer connection. Analytical results are validated using simulation and finally by experimental approach.

This paper presents space vector modulation strategy for eliminating the common mode (CM) voltage of a three level five-phase neutral point clamped (NPC) voltage source inverter (VSI). There are two hundred and forty three discrete switching states available for operation and control of the NPC VSI. Out of two hundred and forty three switching states only fifty one switching states gives zero common mode voltage. The method reported in this paper, only thirty one switching states are selected from those fifty one switching states so that the xy voltage vector component is restricted.. The same switching states also give zero neutral point current and hence the dc link capacitor has equal voltage distribution. Simulation results are provided to validate the concept.