Abstract
The paper applies three cutting-edge algorithms - War Strategy Optimization Algorithm (WSO), Egret Swarm Optimization Algorithm (ESOA), and Black Widow Optimization Algorithm (BWOA) - as potential tools to determining the optimal generation power of power plants in both the Economic Load Dispatch problem (ELD) and the New ELD problem (NELD), which incorporates renewable energy resources into the traditional power system. These algorithms underwent rigorous evaluation using various test systems with complex constraints, a multi-fuel objective function, and 24-hour load demands. In System 1, at various load levels, WSO method achieves a lower total minimum cost compared to BWOA and ESOA. Specifically, WSO outperforms BWOA and ESOA by $0.68 and $2.79 for a load of 2400 MW, by $0.49 and $4.41 for a load of 2500 MW, by $0.79 and $4.83 for a load of 2600 MW, and by $0.54 and $4.53 for a load of 2700 MW. In System 2, WSO method is less cost in a day than ESOA by $ 80.92 and BWOA by $ 46.73, corresponding to 0.39% and 0.23%, respectively. Additionally, WSO excels in response capability, providing a quicker reaction time than BWOA and ESOA across all four subcases while maintaining the same control parameters. Moreover, WSO demonstrated comparable or superior results and improved search capabilities compared to previous methods. The comparison of these results underscored WSO's effectiveness in addressing these challenges and its potential for resolving broader engineering issues beyond ELD. Ultimately, the study aimed to offer valuable insights into the role of renewable energy resources in the traditional power system, particularly in cost savings.
Published Version
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