Design of Novel Secondary Controller for AGC in Multi-Area Multi-Sources Power System Incorporated Renewable Energy Using a Gray Wolf Optimizer Algorithm

Abstract

Three unequal-area multi-source interconnected hydrothermal systems with wind power plants integrated into each area are the subject of this paper's analysis of automatic generation control (AGC). A fully optimum two-level neuro-fuzzy proportional plus integral plus derivative with filter (TLNF-PIDF) is introduced as secondary controller. An appropriate generating rate constraint (GRC) has been considered for the hydro and thermal power plants. The study compares several performance indices and optimization algorithms, provides the most favorable performance. Subsequently, the Gray Wolf Optimizer (GWO), a recently developed optimization algorithm, is employed to optimize the parameters of the controllers. The effectiveness and adaptability of the proposed technique are demonstrated through its application to a three-area hydrothermal-wind power plant. The hydropower plant is integrated as a mechanical and electric governor; the thermal portion is considered a reheat turbine. The dynamic performance of electric and mechanical governor is evaluated and compared for further applications. The system performance is assessed and compared by considering wind energy sources with the TLNF-PIDF, NF-PIDF, and PIDF controllers. The analysis clearly shows that the TLNF-PIDF controller performs better than both NF-PIDF and PIDF. Finally, a robustness analysis is carrying out to proof the controller's resilience under varying loading conditions.