A Stochastic Optimization Method for Energy Storage Sizing Based on an Expected Value Model

Delong Zhang, Jianlin Li, Xueqin Liu, Jianbo Guo and Shaohua Xu
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Delong Zhang: China Electric Power Research Institute, No.15 Xiaoying East Road, Haidian District, Beijing 100192, China
Jianlin Li: China Electric Power Research Institute, No.15 Xiaoying East Road, Haidian District, Beijing 100192, China
Xueqin Liu: School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT9 5AH, UK
Jianbo Guo: China Electric Power Research Institute, No.15 Xiaoying East Road, Haidian District, Beijing 100192, China
Shaohua Xu: China Electric Power Research Institute, No.15 Xiaoying East Road, Haidian District, Beijing 100192, China

Energies, 2019, vol. 12, issue 4, 1-14

Abstract: Energy storage technologies have been rapidly evolving in recent years. Energy storage plays different roles in various scenarios. For electricity consumers, they are concerned with how to use the energy storage system (ESS) to reduce their costs of electricity or increase their profits. In this paper, a stochastic optimization method for energy storage sizing based on an expected value model for consumers with Photovoltaic Generation (PV) is proposed. Firstly, the Gaussian mixture model clustering method is used to cluster the historical load and PV data and calculate the probability of each cluster. Secondly, the optimal model of total system profit is established. Finally, according to the expected value model, the optimal ESS power and capacity are determined. Two case studies are used to demonstrate the calculation of optimal ESS capacity. The results obtained by the method proposed in this paper are compared with the results produced by the deterministic method. Through the analysis and comparison, the validity and superiority of the method proposed in this paper are verified. The profits obtained by the method proposed in this paper are 0.87% to 127.16% more than the deterministic method.

Keywords: energy storage system; expected value model; stochastic optimization; consumer side (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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