Load Frequency Control Strategy Using Hybrid Adaptive Particle Swarm-Spiral Dynamic Optimization Algorithm for Stand-Alone Renewable Rural Network

This paper proposes an advanced Load Frequency Contol (LFC) strategy, using a hybrid adaptive particle swarm-spiral dynamic optimization algorithm (HAPSSDOA). The optimization algorithms iteratively adjust the PID gains based on the evaluation of the cost function and eventually find the optimal values that minimize the cost function and result in a satisfactory frequency value of 50Hz. The P-I-D parameters for the APSO, SDA, and HAPSSDOA algorithms were 3.5112, 2.9691 and 1.1972; 2.3712, 2.8479 and 0.9827; 2.3519, 1.7989 and 0.8864 respectively. The system’s performance showed the rise time, settling time, percentage overshoot and ITAE of 0.28s, 2.33s, 42.10%, and 0.1076 for APSO; 0.324s, 3.67s, 38.4%, and 0.3590 for SDA; 0.36S, 2.2S, 33.5%, and 0.2430 for HAPSSDOA respectively. The LFC strategy using the hybrid HAPSSDOA achieved better performance, improved robustness, and the best response. The optimized PID controllers’ values brought more stability to the designed microgrid network, by ensuring that the frequency remained at 50Hz.