E3S Web Conf.
Volume 233, 20212020 2nd International Academic Exchange Conference on Science and Technology Innovation (IAECST 2020)
|Number of page(s)||5|
|Section||NESEE2020-New Energy Science and Environmental Engineering|
|Published online||27 January 2021|
Region search evolutionary algorithm with constraint handling for multi-objective short-term wind-solar-hydro-thermal scheduling
1 School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
2 China Southern Power Grid Power Generation Company, Guang Zhou, Guang Dong, China
a Corresponding author: firstname.lastname@example.org
Due to the depletion of fossil energy and environmental pollution, renewable clean energy has been paid more and more attention. This paper researches a multi-objective wind-solar-hydro-thermal scheduling model (MOSWS), whose objectives are to minimize the economic cost and minimize the environmental pollution caused by thermal power generation. The region search evolutionary algorithm (RSEA) with constraint handling method is proposed to solve the constrained multi-objective problems and applied to MOSWS model. From the experimental results, we find that RSEA with constraint handling is able to solve the constrained multi-problems and outperforms MODE-ACM in terms of both convergence and diversity. The RSEA is also applied to hydro-thermal system. The results show that wind-solar-hydro-thermal system can not only increase economic benefits, but also reduce the impact of thermal power generation on the atmospheric environment.
© The Authors, published by EDP Sciences 2021
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