Title: Investment benefit evaluation of wind power energy storage based on improved minimum cross entropy method

Authors: Man-Li Zhao; Zi-Qin You; Jing-Lu Li

Addresses: Management School, Hunan City University, Yiyang, 413000, China; Hunan New Type Urbanization Research Institute, Yiyang, 413000, China ' School of Economics and Management, Hainan Normal University, Haikou, 571158, China ' Management School, Hunan City University, Yiyang, 413000, China

Abstract: In order to overcome the problems of low evaluation accuracy and poor correlation in the selection of evaluation parameters in existing benefit evaluation methods, a wind power generation energy storage investment benefit evaluation method based on the improved minimum cross entropy method is proposed. Firstly, in order to clarify the output characteristics of wind power generation, a wind power generation characteristic model is constructed. Then, based on the output characteristics of wind power generation, investment benefit evaluation indicators are determined from the perspectives of economic benefits, cost benefits, and environmental benefits. Finally, the continuous function improved minimum cross entropy method is introduced to calculate the weight of the evaluation index. An investment benefit evaluation model is then built. The test results show that the proposed method can improve the accuracy of investment benefit evaluation, with an evaluation accuracy of over 95%, and the parameter correlation in the evaluation is high.

Keywords: improved minimum cross entropy method; wind power generation; energy storage investment; benefit evaluation; continuous function.

DOI: 10.1504/IJETP.2023.134160

International Journal of Energy Technology and Policy, 2023 Vol.18 No.3/4/5, pp.179 - 194

Received: 09 Feb 2023
Accepted: 03 Jul 2023
Published online: 12 Oct 2023 *

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