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This paper presents a comprehensive review of advanced technologies with various control approaches in terms of their respective merits and outcomes for power grids. Distributed energy storage control is classified into automatic voltage regulator and load frequency control according to corresponding functionalities. These control strategies maintain a power balance between generation and demand. Besides, three basic electric vehicle charging technologies can be distinguished, i.e. stationary, quasi-dynamic and dynamic control. For realizing charge-sustaining operation at minimum cost quasi-dynamic and dynamic strategies are adopted for in-route charging, while stationary control can only be utilized when the electric vehicle is in stationary mode. Moreover, power system frequency stability and stabilization techniques in non-synchronous generator systems are reviewed in the paper. Specifically, a synchronverter can damp power system oscillations and ensure stability by providing virtual inertia. Furthermore, it is crucial to manage the massive information and ensure its security in the smart grid. Therefore, several attack detection and mitigation schemes against cyber-attacks are further presented to achieve reliable, resilient, and stable operation of the cyber-physical power system. Thus, bidirectional electrical power flows with two-way digital control and communication capabilities have poised the energy producers and utilities to restructure the conventional power system into a robust smart distribution grid. These new functionalities and applications provide a pathway for clean energy technology. Finally, future research trends on smart grids such as IoT-based communication infrastructure, distributed demand-response with artificial intelligence and machine learning solutions, and synchrophasor-based wide-area monitoring protection and control (WAMPC) are examined in the present study.

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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