Performance improvement and power management based arithmetic optimization algorithm in grid-integrated photovoltaic with electric vehicle batteries systems

Abstract

Power quality is paramount for ensuring reliable, stable, and environmentally sustainable electricity supply from distributed renewable energy sources (DRESs). However, conventional controllers in hybrid Photovoltaic–Electric Vehicle Battery (PV–EVB) systems typically suffer from limitations such as steady-state error, harmonic distortion, suboptimal transient response, and voltage overshoot. Addressing these issues, this paper proposes a novel arithmetic optimization algorithm (AOA) to enhance performance and power quality in PV–EVB systems subject to load and environmental variability. The proposed methodology consists of two primary components. First, an AOA-based global maximum power point tracking (GMPPT) controller dynamically adjusts PV output to suppress upward frequency oscillations. Second, AOA is employed to optimize the proportional-integral (PI) controller gains for both the bidirectional DC/DC converter and the single-phase inverter of the EVB system, thereby reducing downward frequency fluctuations. These coordinated strategies effectively stabilize DC link voltage (DLV), control grid frequency, and minimize total harmonic distortion (THD) in the grid current. Quantitative results demonstrate that, AOA-based approach achieves a rapid settling time of 0.3 s, low overshoot (3%), and minimal steady-state error (0.2%), while maintaining high PV power and system efficiency (99%). Thus, the AOA-based control strategy significantly improves the grid-integration of hybrid PV–EVB systems and supports more robust, efficient, and sustainable energy infrastructure.