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Conventional energy networks produce energy with less efficiency. Also, these source's development costs and size are more. So, the world is focusing on renewable energy networks for energy production to the consumer. In this work, a proton exchange membrane fuel stack (PEMFS) technology is selected for energy feeding to the hydrogen vehicle. The merits of this stack are more abundant, faster fuel stack operational response, and more efficient for electrical automotive networks. However, the fuel stack's energy production is nonlinear and its operational point varies concerning the fuel stack device operating temperature. The particle swarm optimized adaptive network‐based fuzzy inference system (PSO‐ANFIS) is proposed in this work to find the operational point of the fuel cell network. The features of this hybrid methodology are the low number of iteration values required, low convergence time, low‐level dependence on the fuel stack, and high compliance for the quick deviations of the fuel system temperature. The operating efficiency and tracking time of the proposed maximum power point tracking (MPPT) controller are 95.60% and 0.1089 s. Another issue of the fuel cell is high output current generation and less voltage production. This condition is happening in the fuel cell because of its chemical reaction dynamics, internal resistance of the cell, and electrochemical potential. Due to this excess current flow in the fuel cell, the direct fuel stack‐fed electrical networks face the issue of high power conduction losses. To reduce the power conduction losses of the system, a single‐switch power circuit is used to reduce fuel source current, thereby optimizing the excessive power losses of the system. The whole fuel stack energy production network is analyzed by selecting the MATLAB Window. [ABSTRACT FROM AUTHOR]

This paper presents the principles of developing an electromechanical emulator based on an original hybridization concept of a wind and tidal power system. Wind and tidal horizontal axis turbines showcase functional similarities and electromechanical coupling possibility. Tidal concepts are very close to those of wind power. Tidal turbine technology should thus reach maturity more quickly because it is possible for it to rely on a certain number of reliable and proven techniques developed for wind power. The proposed hybrid wind – tidal turbine system is electromechanically coupled on the axis of rotation of a single and common electric generator. An experimental simulation of the hybrid wind-tidal turbine system was carried out, using a developed architecture of an emulator system. The results are both numerical simulations carried out in the MATLAB/Simulink environment and tests obtained employing real-time emulators. [ABSTRACT FROM AUTHOR]

Renewable energy, particularly wind energy, is expected to contribute significantly to the overall power generation. Induction machines are extensively used as generators in wind power generation because of their multiple benefits, such as robustness, reliability, and low cost and maintenance. However, due to the reactive power demand from the system to which they are connected, this type of generator brings new problems related to power quality, generally consisting of voltage regulation and reactive power compensation. These problems may cause voltage drops and dynamic instability. This study presents a metaheuristic method to attain a microgrid system with an optimal distribution based on its different constraints. The numerical model of an induction generator constructed in MATLAB/Simulink was used, and the simulation results obtained demonstrate the efficacy of the proposed metaheuristic technique. [ABSTRACT FROM AUTHOR]

This paper explores the influence of design variations on the electrical and thermal efficiencies of PV/T (Photovoltaic-Thermal) systems. Utilizing COMSOL Multiphysics, three different PVT configurations with varying air duct designs were studied. The results demonstrated significant enhancements in both electrical and thermal efficiencies, with the PVT-3 configuration outperforming PVT-1 and PVT-2. Specifically, PVT-3, incorporating fin-shaped air ducts, exhibited the lowest recorded panel temperature of 55 °C, indicating improved electrical efficiency and thermal performance. Also, PVT-3 achieved the highest average thermal efficiency of 46.35% and the best electrical performance of 13.91%. Furthermore, the study highlights ameliorated airflow dynamics and uniformity within the ducts, particularly with the redesigned air inlet. These findings underscore the importance of design innovations in optimizing temperature management and energy output in PVT systems. It is worth noting that the tests were conducted under identical operating conditions, including air velocity, inlet temperature, ambient temperature, and solar irradiation. [ABSTRACT FROM AUTHOR]

This research addresses the improvement of the performance of a solar dryer equipped with a PVT unit by integrating a heat exchanger into the drying system. The results indicated that introducing a heat exchanger into the drying process had a positive impact on enhancing and raising the drying temperature by harnessing the amount of free energy dissipated after the drying operation. The absorbed energy ranged from 30 J/s to 275 J/s from the hot air emitted throughout the drying process during the day, depending on the drying temperature. This paper also discusses the influence of the drying room design on the thermal balance within the room. Consequently, four different designs for the drying room were developed and studied with the COMSOL software. The findings revealed that the design-4, which optimally places two air inlets (one at the bottom and one at the top) on one side, whereas the opposing side has a centralized air outlet, utilizing a fan to ensure effective air circulation, is the best solution in terms of thermal balance and distribution of the drying air inside the drying chamber. [ABSTRACT FROM AUTHOR]

The present power generation corporations are working on Renewable Power Systems (RPS) for supplying electrical power to the automotive power industries. There are several categories of RPSs available in the atmosphere. Among all of the RPSs, the most general power network used for Electric Vehicles (EVs) is hydrogen fuel which is available in nature. The H2 fuel is fed to the Proton Exchange Membrane Fuel Stack (PEMFS) for producing electricity for the EV stations. The advantages of this selected fuel system are more power conversion efficiency, environmentally friendly, low carbon emissions, more power density, less starting time, plus able to work at very low-temperature values. However, this fuel stack faces the issue of a nonlinear power density curve. Due to this nonlinear power supply from the fuel stack, the functioning point of the overall network changes from one position of the I–V curve to another position. So, the peak voltage extraction from the fuel stack is not possible. In this article, there are various metaheuristic optimization-based Maximum Power Point Tracking (MPPT) methodologies are studied along with the conventional methods for obtaining the Maximum Power Point (MPP) position of the PEMFS. From the simulative investigation, the Continuous Different Slope Value-based Cuckoo Search Method (CDSV with CSM) provides better efficiency with more output power. Also, for all the MPPT methods comprehensive analysis has been made by utilizing the simulation results. [ABSTRACT FROM AUTHOR]

A substantial level of significance has been placed on renewable energy systems, especially photovoltaic (PV) systems, given the urgent global apprehensions regarding climate change and the need to cut carbon emissions. One of the main concerns in the field of PV is the ability to track power effectively over a range of factors. In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers. Various factors, such as voltage, current, power, weather dependence, cost, complexity, response time, periodic tuning, stability, partial shading, and accuracy, are all intended to be evaluated by the study. It is aimed to provide insight into how well each controller performs in various circumstances by carefully examining these broad parameters. The main goal is to identify and recommend the best controller based on their performance. It is notified that, conventional techniques like INC, P&O, INC-PSO, P&O-PSO, achieved accuracies of 94.3, 97.6, 98.4, 99.6 respectively while AI based techniques Fuzzy-PSO, ANN, ANFIS, ANN-PSO, PSO, and FLC achieved accuracies of 98.6, 98, 98.6, 98.8, 98.2, 98 respectively. The results of this study add significantly to our knowledge of the applicability and effectiveness of both AI and traditional MPPT controllers, which will help the solar industry make well-informed choices when implementing solar energy systems. [ABSTRACT FROM AUTHOR]

Nowadays, electricity theft is a major issue in many countries and poses a significant financial loss for global power utilities. Conventional Electricity Theft Detection (ETD) models face challenges such as the curse of dimensionality and highly imbalanced electricity consumption data distribution. To overcome these problems, a hybrid system Multi-Layer Perceptron (MLP) approach with Gated Recurrent Units (GRU) is proposed in this work. The proposed hybrid system is applied to analyze and solve electricity theft using data from the Chinese National Grid Corporation (CNGC). In the proposed hybrid system, first, preprocess the data; second, balance the data using the k-means Synthetic Minority Oversampling Technique (SMOTE) technique; third, apply the GTU model to the extracted purified data; fourth, apply the MLP model to the extracted purified data; and finally, evaluate the performance of the proposed system using different performance measures such as graphical analysis and a statistical test. To verify the consistency of our proposed hybrid system, we use three different ratios for training and testing the dataset. The outcomes show that the proposed hybrid system for ETD is highly accurate and efficient compared to the other models like Alexnet, GRU, Bidirectional Gated Recurrent Unit (BGRU) and Recurrent Neural Network (RNN). [ABSTRACT FROM AUTHOR]

Multi-level inverters are widely employed to generate new energy because of their huge capacity and benefits in sound control performance. One of the critical areas of study for multi-level inverters is control strategy research. In this study, the control strategy for a multi-level inverter—which is frequently employed in HVDC and FACTS systems—is designed. An asymmetrical D.C. voltage source is supplied to create the appropriate output voltage waveform with fewer total harmonic distortions (THDs) at the output voltage and current waveforms. In this work, the pulse width modulation techniques of POD (phase opposition disposition) and APOD (alternative phase opposition disposition) MC PWM are applied to a multi-level inverter to generate the seven-level output voltage waveform. This study presents an enhanced variable carrier frequency APOD control approach that can successfully lower the overall harmonic distortion rate. The design and completion of the phase-shifting POD and APOD control strategies are followed by an analysis and comparison of the THD situation under various switching frequencies and a simulation and verification of the control strategy using MATLAB simulation. The TI DSP-based control approach has been programmed. The APOD technique increases the output voltage's THD to 18.27%, while the output current waveform's THD is reduced to 15.67% by utilizing the APOD PWM technique. Using the POD PWM approach increases the total harmonic distortion (THD) of the voltage waveform by 18.06% and the output current waveform's THD by 15.45%. [ABSTRACT FROM AUTHOR]

Mini Hydropower Plants (MHPPs) are increasingly popular for rural electrification in developing nations due to their ecologically friendly operation. However, constant load fluctuation in these facilities poses a speed control issue. The mechanical, hydraulic governor, commonly used to face this challenge, cannot provide the best speed control due to its mechanical component system. Thus, an electrohydraulic PIDbased governor is proposed to control the frequency and speed of MHPPs in a distribution network. This governor's suitability for regulating the system's frequency in response to significant load variations within the distribution network is going to be determined in this study. The small hydropower plant and distribution system are modeled using the PSCAD software. A comparison between the mechanical hydraulic governor and the electro-PID governor was conducted by analyzing load fluctuations between 5% and 20%. The electro-PID governor responded faster and more actively to load connections and disconnections than the mechanical hydraulic governor, as the latter reduces large overshoots and undershoots, which can be dangerous and damaging to equipment. The electro-PID governor also helps to maintain a stable frequency within acceptable limits, ensuring smooth operation and minimizing the risk of system failures or disruptions. [ABSTRACT FROM AUTHOR]