Optimization of Unit Commitment Problems Integrated PV Generation Plants Based on Particle Swarm Optimization Algorithm - Hendrayant, Arya; Wirateruna, Efendi S; Melfazen, Oktriza; Utomo, Wahyu Mulyo (Informatics Department-Universitas Dr. Soetomo, 2025)
The increasing integration of renewable energy sources, particularly photovoltaic (PV) systems, poses significant challenges in the Unit Commitment (UC) problem due to their intermittent and inertial nature. This condition can cause frequency instability during system disturbances, necessitating the development of new strategies to maintain reliable power system operation. This study proposes an enhanced UC optimization framework by integrating conventional thermal generating units, PV plants, and energy storage systems (ESS) that act as virtual inertia providers. To solve the optimization problem while considering various technical constraints—such as ramping limits, minimum on/off times, rotating reserve requirements, and nadir frequency thresholds—a modified Particle Swarm Optimization (PSO) algorithm is employed. The model is tested on a generating system consisting of nine thermal units, one PV plant, and one ESS. Simulation results show that the proposed method is capable of maintaining the system frequency above the nadir threshold of 49.5 Hz during disturbances while minimizing the total operating cost. Specifically, the optimal configurations without nadir constraints and with ESS integration achieve convergence in only four iterations with a computational time of 1.9 seconds. These findings demonstrate the effectiveness of integrating ESS as virtual inertia and the efficiency of a modified PSO algorithm in handling UC in systems with high renewable energy penetration. This framework offers a promising approach to improving cost efficiency and frequency stability in future renewable energy-based power systems.