Economic Load Dispatch of Thermal-Solar-Wind System using Modified Grey Wolf Optimization Technique

The growing demand for electrical energy, coupled with the uneven distribution of natural resources, necessitates the integration of power plants. Coordinating the operation of interconnected generating units is crucial to meet the fluctuating load demand efficiently. This research focuses on the Economic Load Dispatch (ELD) problem in hybrid power systems that incorporate solar thermal and wind energy. Renewable energy resources, such as wind and solar thermal energy, depend on atmospheric conditions like wind speed, solar radiation, and temperature. This study addresses the ELD problem using a Modified Grey Wolf Optimization (MGWO) approach to obtain the most optimal solution for generator fuel costs. The Grey Wolf Optimization (GWO) approach, inspired by natural processes, is utilized but may exhibit both exploratory and exploitative behavior. To enhance its performance, we propose a novel version called MGWO, integrating memory, evolutionary operators, and a stochastic local search approach. The suggested MGWO approach is applied to two distinct test systems comprising 13 and 26 units, respectively, to solve the ELD with variable load requirements. Comparative analyses with other strategies demonstrate the effectiveness of MGWO in addressing the ELD problem. This modification enhances the GWO method, making it more robust and efficient for optimizing ELD in hybrid power systems.