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In this paper, an adaptive virtual inertia-damping system based on model predictive control (MPC) is proposed to enhance the frequency dynamic performance of islanded microgrids (MGs) considering a high penetration level of renewable energy sources (RESs). Where a large amount of RESs is recently replacing traditional generating units, causing an undesirable effect on the MG frequency stability and the system inertia, and thus weakening the MG. Therefore, the proposed control system handles this challenge to enhance the robust performance and stability of the MG with high RESs penetration during contingencies. The proposed online MPC strategy estimates the gains of the virtual inertia control (VIC) system (i.e., inertia and damping coefficients) in high RESs MG. The performance of the proposed adaptive VIC system is compared with the conventional VIC system (i.e., constant values of inertia and damping coefficients) using MATLAB/Simulink under numerous disturbances and system uncertainties. Also, the effectiveness of the proposed adaptive VIC system based on the online MPC strategy (which considers both inertia and damping coefficients) is verified by comparing its performance with the adaptive VIC system based on fuzzy logic control, which is designed to estimate only the inertial gain. The results highlight that the frequency stability is upgraded, and the adaptive virtual inertia system based on MPC successfully supports low-inertia islanded MGs with RESs and load fluctuations.INDEX TERMS Adaptive virtual inertia system, model predictive control (MPC), microgrid (MG), frequency stability, high penetration of renewable energy sources (RESs).

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Electrical power networks are expanded regularly to meet growing energy requirements. Reactive power dispatch (RPD) optimization is a powerful tool to enhance a system’s efficiency, reliability, and security. RPD optimization is classified as a non-linear and non-convex problem. In this paper, the RPD optimization problem is solved based on novel hybrid genetic algorithms—equilibrium optimizer (GAEO) optimization algorithms. The control variables are determined in such a way that optimizes RPD and minimizes power losses. The efficiency of the proposed optimization algorithms is compared to other techniques that have been used recently to solve the RPD problem. The proposed algorithm has been tested for optimization RPD for three test systems, IEEE14-bus, IEEE-30bus, and IEEE57-bus. The obtained results show the superiority of GAEO over other techniques for small test systems, IEEE14-bus and IEEE-30bus. GAEO shows good results for large system, IEEE 57-bus.

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A promising hierarchical nanocomposite of MIL-53(Al)/ZnO was synthesized as a visible-light-driven photocatalyst to investigate the degradation of amoxicillin (AMX). MIL-53(Al)/ZnO ultrafine nanoparticles were obtained by preparing Zn-free MIL-53Al and employing it as a reactive template under hydrothermal and chemical conditions. The synthesized nanocomposite (MIL-53(Al)/ZnO) has a low content of Al > 1.5% with significantly different characterizations of the parent compounds elucidated by various analyses such as SEM, TEM, XRD, EDX, and UV–Vis. The effect of operational parameters (catalyst dose (0.2–1.0 g/L), solution pH (3–11), and initial AMX concentration (10–90 mg/L)) on the AMX removal efficiency was studied and optimized by the response surface methodology. A reasonable goodness-of-fit between the expected and experimental values was confirmed with correlation coefficient (R2) equal to 0.96. Under the optimal values, i.e., initial AMX concentration = 10 mg/L, solution pH ~ 4.5, and catalyst dose = 1.0 g/L, 100% AMX removal was achieved after reaction time = 60 min. The degradation mechanism and oxidation pathway were vigorously examined. The AMX degradation ratios slightly decreased after five consecutive cycles (from 78.19 to 62.05%), revealing the high reusability of MIL-53(Al)/ZnO. The AMX removal ratio was improved with enhancers in order ($${\mathrm{IO}}_{4}^{-}$$ IO 4 - > H2O2 > S2O8−2). The results proved that 94.12 and 98.23% reduction of COD were obtained after 60 and 75 min, respectively. The amortization and operating costs were estimated at 3.3 $/m3 for a large-scale photocatalytic system.

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