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Recently, wide installations of photovoltaic (PV) systems have been achieved in the electrical power systems. However, fluctuated output power of the PV generation and/or fluctuated load demands represent critical factors for the operation of PV systems. Thence, energy storage systems (ESSs) are highly needed for improving the supply reliability of PV generation systems. Among existing ESSs, the proton exchange membrane fuel cell (PEMFC) systems represent long-lifetime, efficient, and cost-effective solutions for PV systems. However, nonlinear behaviour exists in the output of PEMFC systems, which depends on the operating cell temperature, and the membrane water contents. The output of PEMFC has a unique operating maximum power point (MPP) for each operating combination of membrane water content and temperature, which requires MPP tracking (MPPT) control loop. Therefore, this paper presents a fuzzy logic control (FLC) MPPT method for enhancing the operation of PEMFC systems. The traditional MPPT methods in the literature employ three sensors, including voltage, water content, and temperature. The proposed controller employs only the PEMFC output current and voltage electrical signals. Compared to the classical fixed step size perturb and observe (P and O) and hill climbing MPPT methods, the proposed method represents variable step size MPPT method. In addition, compared to the widely employed incremental conductance (INC) and incremental resistance (INR) MPPT methods, the proposed method benefits the wide operating and adaptive step size MPPT operation due to using the FLC approach. The proposed method is simple and can be implemented using low cost microcontrollers. The design procedures, operating principle, and performance verification of the proposed method are presented in this paper. [ABSTRACT FROM AUTHOR]

Summary: The output power from thermoelectric generator (TEG) system is mainly dependent on the differential temperature between the hot side and cold side of TEG in addition to the load demand. Therefore, maximum power point tracking (MPPT) control is highly needed to continuously track the optimal operating point with changing the operating condition. In this research paper, a MPPT method based on optimized fuzzy logic control (FLC) is proposed. The proposed method utilizes the freedom and flexibilities from FLC systems to develop accurate and fast‐tracking controller of maximum power point for TEG applications. The parameters of the optimized FLC have been identified using recent manta ray foraging optimization (MRFO) algorithm. During the proposed optimization process, the gains of the membership functions are used as decision variables, whereas the integral of the error is used as a cost function. Different scenarios of changing the difference temperature are used to prove the reliability of the optimized FLC. The obtained results by using the optimized FLC are compared with conventional FLC and the hill‐climbing methods. The main findings confirm that the proposed design using combined features of MRFO and FLC presents a promising solution for MPPT in TEG systems. The proposed optimized FLC method achieves superior performance through minimizing the fluctuations in the output power at the various studied scenarios. Moreover, continuous tracking of the maximum power from TEG is achieved by the proposed optimized FLC method at different hot side and cold side temperatures in addition to output load variations. [ABSTRACT FROM AUTHOR]

Fuzzy logic control (FLC) systems have found wide utilization in several industrial applications. This paper proposes a fuzzy logic-based fault detection and identification method for open-circuit switch fault in grid-tied photovoltaic (PV) inverters. Large installations and ambitious plans have been recently achieved for PV systems as clean and renewable power generation sources due to their improved environmental impacts and availability everywhere. Power converters represent the main parts for the grid integration of PV systems. However, PV power converters contain several power switches that construct their circuits. The power switches in PV systems are highly subjected to high stresses due to the continuously varying operating conditions. Moreover, the grid-tied systems represent nonlinear systems and the system model parameters are changing continuously. Consequently, the grid-tied PV systems have a nonlinear factor and the fault detection and identification (FDI) methods based on using mathematical models become more complex. The proposed fuzzy logic-based FDI (FL-FDI)method is based on employing the fuzzy logic concept for detecting and identifying the location of various switch faults. The proposed FL-FDI method is designed and extracted from the analysis and comparison of the various measured voltage/current components for the control purposes. Therefore, the proposed FL-FDI method does not require additional components or measurement circuits. Additionally, the proposed method can detect the faulty condition and also identify the location of the faulty switch for replacement and maintenance purposes. The proposed method can detect the faulty condition within only a single fundamental line period without the need for additional sensors and/or performing complex calculations or precise models. The proposed FL-FDI method is tested on the widely used T-type PV inverter system, wherein there are twelve different switches and the FDI process represents a challenging task. The results shows the superior and accurate performance of the proposed FL-FDI method. [ABSTRACT FROM AUTHOR]

The voltage and frequency stability issues of power systems are the main challenges that arise from high penetration levels of wind energy systems. This paper presents an effective solution for voltage and frequency stability problems by using a superconducting magnetic energy storage (SMES) system controlled with a fuzzy logic controller (FLC). The proposed control system can suppress the voltage and frequency fluctuations due to the high variations of wind speed. In addition, the proposed control system is suitable for both balanced and unbalanced distribution systems with high penetration levels of wind turbines (WTs). A squirrel cage induction generator (SCIG) is selected in the case study, which represents the worst scenario of WT generation from the voltage and frequency stability aspects. This is due to the high reactive power consumed by the SCIG from the utility grid during steady state and voltage fluctuations that may lead to harmful consequences for power system components. The proposed control method is validated using the IEEE 33-bus radial distribution network (RDN), wherein the SMES and WT systems are connected to the weakest points of the RDN. The obtained results demonstrate the superior performance of the proposed FLC-SMES system for alleviating the voltage and frequency fluctuations of the distribution power system during high variations of wind power. [ABSTRACT FROM AUTHOR]

In this paper, an improved design approach for fuzzy logic control (FLC) systems is proposed for MPPT control of PEMFCs. The proposed design is based on the recent Equilibrium Optimizer method for determining the optimum parameters to fully benefit the inherent flexibility and freedom of FLC systems in addition to achieve fast and accurate tracking. During the optimization process, gains of membership functions of FLC is used as a decision variable, whereas the integral of error is used as a cost function. The obtained results are compared with particle swarm optimization (PSO), genetic algorithm (GA), electric charged particles optimization (ECPO) and spotted hyena optimizer (SHO). The proposed EO methodology outperformed all other methods, achieving the best mean, median, variance, and standard deviation. Moreover, statistical tests including Wilcoxon, Holm-Bonferroni correction, Kruskal Wallis, and Friedman tests are performed to prove efficiency of the proposed strategy. In last, different scenarios of changing operating temperature and water content are used to prove the reliability of the optimized FLC. The obtained results are compared with conventional FLC and hill-climbing method. The main findings confirm that the proposed design using combined features of EO and FLC presents a promising solution for MPPT in PEMFCs. • An improved design approach for FLC system is proposed for MPPT control of PEMFCs. • The proposed design is based on the recent Equilibrium Optimizer. • The proposed FLC method represents a variable step size MPPT control method. • The combination of FLC with the EO method results in optimizing the design of FLC MPPT. [ABSTRACT FROM AUTHOR]