Efficient Energy Storage System for Renewable Energy Source Integration to Grid

An efficient Energy Storage System (ESS) is essential for Renewable Energy Sources (RES) namely, solar and wind, which are intermittent and fluctuate with environmental conditions. ESS technologies, such as batteries enable grid stability by storing excess energy induced with high productivity and released throughout low volume of production. In this work proposes an efficient ESS for RES integration into the grid. The Photovoltaic (PV) system utilizes a High-Gain Z-Source Boost (HGZSB) converter, optimized through Recurrent Neural Network (RNN)-based Maximum Power Point Tracking (MPPT) algorithm to extract maximum energy. In parallel, the Doubly Fed Induction Generator (DFIG)-based Wind Energy Conversion Systems (WECS) are regulated by a PWM rectifier and a PI-controlled PWM generator to stabilize power flow. A bidirectional battery converter manages energy storage, enhancing stability and reliability by balancing supply-demand fluctuations. Artificial Neural Network (ANN) controllers are employed to control current and voltage levels, optimizing the overall system's dynamic response. Finally this work is implemented by using a MATLAB 2021a Simulink Software. The proposed HGZSBC achieves an efficiency of 94.5%.