Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition

Almeida, José; Lezama, Fernando; Soares, João; Vale, Zita; Canizes, Bruno

http://hdl.handle.net/10400.22/22463

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In this paper, multiple evolutionary algorithms are applied to solve an energy resource management problem in the day-ahead context involving a risk-based analysis corresponding to the proposed 2022 competition on evolutionary computation. We test numerous evolutionary algorithms for a risk-averse day-ahead operation to show preliminary results for the competition. We use evolutionary computation to follow the competition guidelines. Results show that the HyDE algorithm obtains a better solution with lesser costs when compared to the other tested algorithm due to the minimization of worst-scenario impact.