Nguyen, Quoc Trung
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Elk herd optimizer for cost-efficient hybrid energy systems under renewable uncertainty Pham, Ly Huu; Nguyen, Hung Duc; Truong, Chi Trung; Nguyen, Quoc Trung
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp430-439

Abstract

This paper suggests a new method, called elk herd optimizer (EHO), for effectively addressing the optimal generation cooperation problem involving thermal, hydro, solar, and wind power plants (WPPs), in which the uncertainty of wind speed and solar radiation from renewable power plants is considered. The primary goal of this study is to minimize the costs from thermal, wind, and solar power plants (SPPs) while adhering to all operational constraints associated with these power plants and the overall power system. Two systems were tested to evaluate the performance of EHO method alongside two other techniques: the coot optimization algorithm (COOT) and the tunicate swarm algorithm (TSA). Both systems were optimally scheduled over a 24-hour period; however, the second system accounted for uncertainties in generation and cost from solar and WPPs. From the result analysis, EHO method was able to achieve a lower cost compared to COOT, TSA, and other previously employed methods for optimizing generation across all plants. Therefore, EHO is recommended as an effective optimization tool for addressing the uncertainties associated with solar radiation and wind speed.