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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...
Citations
... In thermal unit scheduling, the probabilistic nature of wind power is very crucial. Emission dispatch minimizes costs and emissions [3][4][5], focusing on enhancing ELD problem-solving under practical constraints, including dynamic/static cases with complex cost functions. Wind power uncertainty creates stochastic optimization problems, leading to the search for optimal solutions [6][7]. ...
... Here PL calculated using equation (5) ...
This paper demonstrates the application of the Starfish Optimization Algorithm (SFOA) to solve the Economic Emission Dispatch (EED) problem considering chance constraints, integrating wind energy sources. Wind power is modeled as a Weibull distribution, and the problem is set up in the framework of Chance-Constrained Programming (CCP) to capture the variability of wind energy. The applied chance constraints ensure that the power flow equation is satisfied with a specified probability, and the resulting CCP formulation is transformed into a deterministic optimization problem using the premises of probability theory. Inspired by the peculiar behaviours of starfish, such as exploration, preying, and regeneration, the SFOA inspires strong global search capability and convergence efficiency. This approach effectively minimizes both generation costs and emissions while addressing the uncertainty associated with wind power. The method is tested on a ten-unit power system with wind energy integration, showing the robustness and efficiency of SFOA in achieving optimal solutions for the chance-constrained EED problem.
