This manuscript proposes the optimal power quality reinforcement in grid‐connected hybrid renewable energy sources like solar photovoltaic, wind turbine, battery storage using an intelligent approach. The proposed hybrid approach is the consolidation of Egyptian vulture optimization algorithm (EVOA) and random forest algorithm (RFA); hence, it is known as EVORFA technique. The major objective of this research is voltage stabilizing, power loss reduction, extenuating harmonic distortion. EVOA is mainly used to the offline way to differentiate the perfect combination and forms the dataset of proportional integral gain parameters; load current, DC‐link voltage, and voltage sources are based on reduced error objective function. In EVOA, multiple parameters are considered that is identified to the power quality (PQ) issues. The RFA predicts most optimal control signal with minimum error based on the accomplished dataset. The proposed EVORFA approach is executed in MATLAB/Simulink work site. The EVORFA approach performance is carried out in two modes, that is, simultaneous PQ reinforcement and RES power injection PRES > 0 and PQ reinforcement (PRES = 0). By then the experimental results are compared to the existing methods like gravitational search algorithm (GSA) and RFA.

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An intelligent control strategy is proposed in this paper which suggests the Optimum Power Quality Enhancement (OPQE) of grid-connected hybrid power systems with solar photovoltaic, wind turbines, and battery storage. Unified Power Quality Conditioner with Active and Reactive power (UPQC-PQ) is designed with Atom Search Optimization (ASO) based Fractional-order Proportional Integral Derivative (FOPID) controller in the proposed Hybrid Renewable Energy Sources (HRES) system. The main aim is to regulate voltage while reducing power loss and reducing Total Harmonic Distortion (THD). UPQC-PQ is used to mitigate the Power Quality (PQ) problems such as sag, swell, interruptions, real power, reactive power and THD reductions related to voltage /current by using ASO based FOPID controller. The developed technique is demonstrated in various modes: simultaneous to improve PQ reinforcement and RES power injection, PRES > 0, PRES = 0. The results are then compared to those obtained using previous literature methods such as PI controller, GSA, BBO, GWO, ESA, RFA, and GA and found the proposed approach is efficient. The MATLAB/Simulink work framework is used to create the model.

This paper made an attempt to put forward the comparative performance analysis of different energy storage devices (ESDs), such as redox flow batteries (RFBs), superconducting magnetic energy storage (SMES) device and ultra-capacitors (UCs), in the combined frequency and voltage stabilization of a multi-area interconnected power system (MAIPS). The investigative power system model comprises two areas, and each area consists of the power-generating sources of thermal, hydro and gas units. The intelligent control mechanism of fuzzy PID was used as a secondary controller optimized with a hybridized approach of the artificial electric field algorithm (HAEFA) subjected to the minimization of integral time absolute error (ITAE) objective function. However, the superiority of fuzzy PID in dampening the deviations of combined load frequency control (LFC) and automatic voltage regulator (AVR) responses was revealed upon comparison with conventional PI and PID. Further, the LFC-AVR combined analysis was extended to incorporate different ESDs one after the other. The simulation results reveal the efficacy of incorporating ESDs with the LFC-AVR system and the supremacy of RFBs in damping out the fluctuations in frequency and voltage.