Enhanced Hybrid Algorithm for Optimizing Economic Dispatch and Emission Management in Power Plants

This paper presents a hybrid methodology for addressing the Economic Load Dispatch Problem and Economic Emission problem in a thermal power unit, incorporating wind power units. The study focuses on optimizing multiple objectives, including individual power sharing between generators, emissions, and fuel cost, under a fixed load demand. The formation of the multi-objective function integrates considerations of emissions and fuel cost. The thermal power system is augmented with a wind power generator to mitigate emissions, leveraging Artificial Neural Networks for wind availability prediction. The effectiveness of the proposed techniques is validated using a ten-unit thermal system, treating fuel cost and emissions as conflicting objectives for simultaneous optimization. Implementation in the MATLAB platform, along with a comparison to existing methods in the literature, demonstrates the superiority of the proposed approach. The results indicate its efficacy in handling multi-objective optimization problems within the constraints of power systems, showcasing advancements in addressing economic and environmental concerns.