Load frequency regulation of interconnected muli-source multi-area power system with penetration of electric vehicles aggregator model

The recent widespread installation of renewable energy sources in place of fossil fuel, along with the substitution of electric vehicles, has given rise to several integration difficulties. Due to their intermittent nature, these systems are generally supplied through variable power generators. The control architecture of such connected systems focuses especially on minimizing frequency deviations and tie-line power fluctuations. In this paper, a cascaded proportional integral-proportional derivative (PI-PD) controller is proposed based on a chaotic butterfly optimization algorithm (CBOA) for parametric determination. The suggested controller and optimization approach is tested on a two-area power network, consisting of multiple renewable energy systems and electric vehicles while considering different load and frequency fluctuations. The proposed algorithm is evaluated based on four performance features. Its superiority is demonstrated by comparing it with recent optimization-algorithms-tuned controllers such as artificial rabbit algorithm 1 + PD, chaos game algorithm 1 + PI, dragonfly search algorithm, fractional order PID, and firefly algorithm PID. The acquired results validate the efficient performance of the proposed methodology by mitigating the frequency and tie-line power variations. Moreover, it exhibits robustness and enhanced stability of the system throughout a broad range of parameters.