Optimal Design of Fuzzy Plus Fraction-Order-Proportional-Integral-Derivative Controller for Automatic Generation Control of a Photovoltaic-Reheat Thermal Interconnected Power System

Automatic generation control is imperative for enhancing a nation's economic level through the production of outstanding electricity generation. Integrating renewable or clean energy such as photovoltaics, into power systems to provide sustainability has attracted research attention worldwide. Therefore, this study proposes a novel application of a secondary fuzzy logic controller cascaded by a fractional-order proportional-integral-derivative controller to enhance automatic generation control performance. The proposed cascade controller regulated the frequency of a two-area interconnected power system comprising a photovoltaic grid and a reheat thermal generator, with and without governor dead band nonlinearity, as a novel application using a powerful optimizer, such as a water cycle algorithm. In addition, photovoltaic maximum power point tracking was considered. Traditional controllers were employed to illustrate the water cycle algorithm's ability to identify automatic generation control issues. Subsequently, a water cycle algorithm based on the fractional-order-proportional-integral-derivative controller demonstrated the fractional-order controller improvement compared to the classical type. The cascade control exhibited high performance, resulting in excellent performance for the suggested cascade controller-based fraction-order controller. The best results were achieved by minimizing the integral time absolute error performance function of frequency and tie-line power variations. Several scenarios evaluated the effectiveness of the proposed scheme under large load disturbances, various step-load perturbations, uncertainties, random load patterns, and governor dead band nonlinearity caused by the power system. The simulation results confirmed that the proposed scheme outperformed previously published approaches.