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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 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]

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]

Now, the present electric vehicle industry is focusing on the fuel cell technology because its features are high flexibility, continuous power supply, less atmospheric pollution, fast startup, and rapid response. However, the fuel cell gives nonlinear power versus current characteristics. Due to this nonlinear behavior, the maximum power extraction from the fuel stack is quite difficult. So, in this work, an adaptive genetic algorithm with an adaptive neuro-fuzzy inference system (ACS with ANFIS) MPPT controller is introduced for finding the MPP of the fuel stack system thereby extracting the peak power from the fuel stack. The proposed hybrid maximum power point tracking (MPPT) controller is compared with the other MPPT controllers which are enhanced incremental conductance-fuzzy logic controller (EIC with FLC), improved hill climb with fuzzy logic controller (IHC with FLC), adaptive beta with FLC, enhanced differential evolutionary with FLC (EDE with FLC), and marine predators optimization with FLC (MPO with FLC). Here, these hybrid controllers' comprehensive investigations have been carried out in terms of tracking speed of the MPP, oscillations across the MPP, settling time of the converter voltage, maximum power extraction from the fuel stack, and working efficiency of the MPPT controller. The fuel stack generates a very low output voltage which is improved by using the boost DC-DC converter, and the overall fuel stack-fed boost converter system is designed by utilizing the MATLAB/Simulink tool. From the simulation results, the AGA with ANFIS MPPT controller gives high MPP tracking efficiency when compared to the other hybrid controller. [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]

This document is a list of academic research papers related to optimal power flow (OPF) in power systems. The papers cover various topics, including the use of different optimization algorithms, the integration of renewable energy sources, and the application of flexible AC transmission system (FACTS) devices. The papers come from a diverse range of authors and institutions, including researchers from Pakistan, China, Saudi Arabia, and other countries. The document provides a valuable resource for library patrons conducting research on OPF and related topics in power systems. [Extracted from the article]

Subversive environmental impacts and limited amounts of conventional forms of energy necessitate the utilization of renewable energies (REs). Unfortunately, REs such as solar and wind energies are intermittent, so they should be stored in other forms to be used during their absence. One of the finest storage techniques for REs is based on hydrogen generation via an electrolyzer during abundance, then electricity generation by fuel cell (FC) during their absence. With reference to the advantages of the proton exchange membrane fuel cell (PEM-FC), this is preferred over other kinds of FCs. The output power of the PEM-FC is not constant, since it depends on hydrogen pressure, cell temperature, and electric load. Therefore, a maximum power point tracking (MPPT) system should be utilized with PEM-FC. The techniques previously utilized have some disadvantages, such as slowness of response and largeness of each oscillation, overshoot and undershoot, so this article addresses an innovative MPPT for PEM-FC using a consecutive controller made up of proportional-integral (PI) and proportional-derivative (PD) controllers whose gains are tuned via the golden jackal optimization algorithm (GJOA). Simulation results when applying the GJOA-PI-PD controller for MPPT of PEM-FC reveal its advantages over other approaches according to quickness of response, smallness of oscillations, and tininess of overshoot and undershoot. The overshoot resulting using the GJOA-PI-PD controller for MPPT of PEM-FC is smaller than that of perturb and observe, GJOA-PID, and GJOA-FOPID controllers by 98.26%, 86.30%, and 89.07%, respectively. Additionally, the fitness function resulting when using the GJOA-PI-PD controller for MPPT of PEM-FC is smaller than that of the aforementioned approaches by 93.95%, 87.17%, and 87.97%, respectively. [ABSTRACT FROM AUTHOR]

Photovoltaic systems have become more attractive alternatives to be integrated into electrical power systems. Therefore, PV cells have gained immense interest in studies related to their operation. A photovoltaic module's performance can be optimized by identifying the parameters of a photovoltaic cell to understand its behavior and simulate its characteristics from a given mathematical model. This work aims to extract and identify the parameters of photovoltaic cells using a novel metaheuristic algorithm named Modified Social Group Optimization (MSGO). First, a comparative study was carried out based on various technologies and models of photovoltaic modules. Then, the proposed MSGO algorithm was tested on a monocrystalline type of panel with its single-diode and double-diode models. Then, it was tested on an amorphous type of photovoltaic cell (hydrogenated amorphous silicon (a-Si: H)). Finally, an experimental validation was carried out to test the proposed MSGO algorithm and identify the parameters of the polycrystalline type of panel. All obtained results were compared to previous research findings. The present study showed that the MSGO is highly competitive and demonstrates better efficiency in parameter identification compared to other optimization algorithms. The Individual Absolute Error (IAE) obtained by the MSGO is better than the other errors for most measurement values in the case of single- and double-diode models. Relatedly, the average fitness function obtained by the MSGO algorithm has the fastest convergence rate. [ABSTRACT FROM AUTHOR]

The low bandgap antimony selenide (Sb2Se3) and wide bandgap organic solar cell (OSC) can be considered suitable bottom and top subcells for use in tandem solar cells. Some properties of these complementary candidates are their non-toxicity and cost-affordability. In this current simulation study, a two-terminal organic/Sb2Se3 thin-film tandem is proposed and designed through TCAD device simulations. To validate the device simulator platform, two solar cells were selected for tandem design, and their experimental data were chosen for calibrating the models and parameters utilized in the simulations. The initial OSC has an active blend layer, whose optical bandgap is 1.72 eV, while the initial Sb2Se3 cell has a bandgap energy of 1.23 eV. The structures of the initial standalone top and bottom cells are ITO/PEDOT:PSS/DR3TSBDT:PC71BM/PFN/Al, and FTO/CdS/Sb2Se3/Spiro-OMeTAD/Au, while the recorded efficiencies of these individual cells are about 9.45% and 7.89%, respectively. The selected OSC employs polymer-based carrier transport layers, specifically PEDOT:PSS, an inherently conductive polymer, as an HTL, and PFN, a semiconducting polymer, as an ETL. The simulation is performed on the connected initial cells for two cases. The first case is for inverted (p-i-n)/(p-i-n) cells and the second is for the conventional (n-i-p)/(n-i-p) configuration. Both tandems are investigated in terms of the most important layer materials and parameters. After designing the current matching condition, the tandem PCEs are boosted to 21.52% and 19.14% for the inverted and conventional tandem cells, respectively. All TCAD device simulations are made by employing the Atlas device simulator given an illumination of AM1.5G (100 mW/cm2). This present study can offer design principles and valuable suggestions for eco-friendly solar cells made entirely of thin films, which can achieve flexibility for prospective use in wearable electronics. [ABSTRACT FROM AUTHOR]

This paper proposes a self-excited induction generator model with saturation effect for power generating mode in a remote site. The model is led through the space vector mathematical formalism and allows one to analyze the steady and dynamic states. It is developed for a squirrel cage induction machine. This model provides magnetizing inductance variation able to influence the build-up and the stabilization of voltage generation when the load changes. The final result is a realistic approach model which takes into consideration the dependency of the magnetizing inductance versus magnetizing current. This novel model is validated through experimental measurements to demonstrate its validity and practicability. [ABSTRACT FROM AUTHOR]

Light-emitting diodes (LEDs) have recently become of utmost significance to replace conventional lighting sources. Power factor correction (PFC) control of LED lamps requires three sensors which cause more cost, increase time delay, and increase noise, thus reducing drive reliability. Alternative methods to estimate the inductor current instead of its measurement are mandatory. This paper proposes a sensorless predictive current controller to enhance power factor (PF) of LED lamp driver and reduce driver cost. The inductor current is estimated instead of employing current sensor relying on measured input and output voltages. Zero-crossing detector is utilized to accomplish robust performance during distorted supply voltage. The controller and power circuit are isolated. The control algorithm employs a two-loop control to achieve a high PF with sinusoidal input current. Rapid speed performance is accomplished. The influences of PFC on input current value, PF and harmonic orders are presented. A prototype LED lamp driver with the suggested PFC structure is tested practically by a digital signal processor (DSP) DS1104 platform to validate its effectiveness. Experimental tests under various working conditions are provided to prove the usefulness of the suggested PFC control. [ABSTRACT FROM AUTHOR]

This paper presents a two-degrees-of-Freedom (2DOF) and variable structure control (VSC) schemes for induction motor (IM) drives. The designed VSC incorporates independent feedback and feedforward terms as 2DOF control principle. This structure improves the response of the proposed VSC under speed reference tracking and load disturbance changes. Stability of VSC using Lyapunov theory is discussed. Due to the variable nature of the switching function of VSC, two conditions to ensure Lyapunov stability candidate are derived based on the error signal. A design criterion for the parameters of VSC are introduced to guarantee the stability. The complete IM drive system with the proposed VSC controller is built using MATLAB/Simulink. A laboratory prototype is executed experimentally using DSP-DS1104 control board. All controllers are implemented practically. Simulation and experimental results are provided under different working conditions. Performance evaluation of classic control schemes and the proposed VSC approach is presented. The proposed VSC approach gives superior behavior under speed reference variations and torque disturbances. The disturbances using the proposed controller are strongly suppressed compared to classic 2DOF control scheme. [ABSTRACT FROM AUTHOR]

This paper concerns a three-phase self-excited induction generator used for autonomous power generation. It presents a robust control strategy which makes it possible to maintain the frequency quasi constant during the voltage regulation without any control loop on this variable. This strategy, which also prevents the machine disengagement, uses as power converter a simple dimmer. The obtained theoretical and/or numerical results are validated on a laboratory test bench that allows the analysis of this control law effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents a non-invasive procedure to detect inter-turn short circuit faults in the stator windings of AC electrical machines. It proposes the use of the stray external magnetic field measured in the vicinity of the machine to determine stator faults. The originality introduced by this procedure is the analysis method presented in the paper, which when compared to usual diagnosis methods, does not require any data on the healthy state of the machine. The procedure uses the magnetic unbalance created by the rotor poles and the load variation in faulty cases. The presented method can be applied to induction and synchronous machines used as a motor or generator. It is based on the variation of sensitive spectral lines obtained from the external magnetic field when the load changes. Analytical relationships are developed in the paper to justify the proposed method and to explain the physical phenomenon. To illustrate these theoretical considerations, practical experiments are also presented. [ABSTRACT FROM AUTHOR]

Renewable energy systems have been extensively developed and they are attractive to become widespread in the future because they can deliver energy at a competitive price and generally do not cause environmental pollution. However, stand-alone energy systems may not be practical for satisfying the electric load demands, especially in places having unsteady wind speeds with high unpredictability. Hybrid energy systems seem to be a more economically feasible alternative to satisfy the energy demands of several isolated clients worldwide. The combination of these systems makes it possible to guarantee the power stability, efficiency, and reliability. The aim of this paper is to present a comprehensive analysis and to propose a technical solution to integrate a self-excited induction generator in a low power multisource system. Therefore, to avoid the voltage collapsing and the machine demagnetization, the various parameters have to be identified. This procedure allows for the limitation of a safe operating area where the best stability of the machine can be obtained. Hence, the load variation interval is determined. An improvement of the induction generator stability will be analyzed. Simulation results will be validated through experimental tests. [ABSTRACT FROM AUTHOR]

After avoiding the Standard Test Condition (STC) related to the manufacturer of PV cells, accurate solar system modeling is considered the most important task to study this system. Several mathematical developments based-approaches or algorithms were considered valuable tools to parameterize the electrical circuit of the photovoltaic models. Thus, these parameters are well determined using optimization algorithms. To achieve this goal, an experimental database or manufacturer's datasheet is requested. This paper proposes a novel Improved Arithmetic Optimization Algorithm (IAOA) to extract the solar cell/panel parameters. Also, practical tests are presented for obtaining the measured illustration of the I-V and P-V characteristics. Thus, the Double Diode Model (DDM) of the electrical circuit of PV panel is studied considering various statistical analyzes, to know the Minimum (Min Fobj,DDM), the Maximum (Max Fobj,DDM), the Average (Ave Fobj,DDM), and the Standard Deviation (SD Fobj,DDM). The estimated I-V and P-V curves using IAOA is compared with eight other recently published algorithms. In addition, the evaluation of the proposed IAOA proves that this proposal has a satisfactory performance than all tested algorithms. The obtained results show that the IAOA is considered first in terms of effectiveness and accuracy by 9.537e−06 of standard deviation. Moreover, considering the variability of operating conditions, the proposed IAOA shows its high superiority to optimize the electrical parameters of the solar cell TDM Where it has the lowest errors by 3.623e−05 of RMSE, 4.183e−06 of MAE, and 1.397e−05 of RMSD. [ABSTRACT FROM AUTHOR]