Optimizing Economic Load Dispatch in Microgrids using Orangutan Optimization Algorithm
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Abstract
In recent years, the integration of renewable energy sources into microgrids has grown substantially, emphasizing the urgent need for efficient power generation management and cost optimization. To address this challenge, this paper introduces the Orangutan Optimization Algorithm (OOA) as an effective approach for solving the Economic Load Dispatch (ELD) problem in microgrids. A microgrid, comprising distributed energy resources and interconnected loads, functions as a coordinated system within well defined electrical boundaries. It incorporates diverse micro-sources such as distributed generators, solar photovoltaic units, and wind turbines, along with various types of loads. The proposed OOA is implemented in MATLAB to solve the ELD problem under different power demand scenarios across a 24 hour operating horizon. The simulation results reveal that OOA achieves notable cost reductions of about 25.83% compared to other benchmark algorithms, including the Whale Optimization Algorithm (WOA), Cuckoo Search Optimization (CSO), Differential Evolution (DE), and Particle Swarm Optimization (PSO). These findings confirm the superior effectiveness of the OOA in optimizing economic load dispatch in microgrid environments.