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All Journal Bulletin of Electrical Engineering and Informatics International Journal of Renewable Energy Development
Pham, Ly Huu
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Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering

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Skill optimization algorithm for solving optimal power flow problem Hien, Chiem Trong; Duong, Minh Phuc; Pham, Ly Huu
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5280

Abstract

This research presents the implementation of a modern meta-heuristic algorithm called the skill optimization algorithm (SOA) to solve the optimal power flow problem (OPF). An IEEE 30-bus transmission system is selected to test the real performance of SOA. The main objective function of the study is to minimize the total fuel cost (TFC) of all thermal units. To clarify the high performance of SOA, a classical meta-heuristic named particle swarm optimization (PSO) is also applied for comparison. All results reached by SOA are compared with those of PSO on different criteria. Particularly, SOA has reached smaller cost than PSO by $1.04, equivalent to 0.13% of PSO’s TFC. Furthermore, SOA has reached a more stable performance by finding better average and maximum TFC over fifty runs. The evaluation of these criteria indicates that SOA completely outperforms PSO. Besides, the optimal solution reached by SOA satisfies all considered constraints with zero violation of the dependent variables. Therefore, SOA is highly suggested to handle the OPF problem.
Determining solutions to new economic load dispatch problems by war strategy optimization algorithm Nguyen, Hung Duc; Pham, Ly Huu
International Journal of Renewable Energy Development Vol 14, No 1 (2025): January 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60618

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.
Co-Authors Duong, Minh Phuc Hien, Chiem Trong Nguyen, Hung Duc