Optimal Allocation of Shared Energy Storage Considering the Economic Consumption of Microgrid New Energy

被引：0

作者：

Xie Y. ^{[1
]}

Luo Y. ^{[1
]}

Li Z. ^{[2
]}

Xu Z. ^{[1
]}

Li L. ^{[1
]}

Yang K. ^{[1
]}

机构：

[1] School of Electrical and Electronic Engineering, Huazhong University of Science & Technology, Wuhan

[2] State Grid Hubei Electric Power Company Economic and Technical Research Institute, Wuhan

来源：

Gaodianya Jishu/High Voltage Engineering | 2022年 / 48卷 / 11期

关键词：

bi-level programming; KKT conditions; micro energy grid; renewable energy consumption; shared energy storage;

D O I：

10.13336/j.1003-6520.hve.20220403

中图分类号：

学科分类号：

摘要：

Shared energy storage is one of the solutions for renewable energy to achieve economic consumption. With a moderate investment scale, efforts should be made to match the capacity and power of energy storage power stations with the consumption target. In this regard, a capacity and power allocation method for shared energy storage power stations considering new energy consumption is proposed, and a bi-level programming model is established for the multi-objectives of the lowest operation cost of energy storage power stations and the optimal operation economy of micro-energy network. For the power station configuration problem, the inner model is used to solve the economic consumption rate and the optimal operation of the micro-energy network, and the KKT method is used to solve the model transformation. The calculation example analysis shows that the operating cost of the micro-energy grid system decreases by 15.01% after the shared energy storage is configured, and the new energy consumption rate increases to 97.06%. The shared energy storage service provider can recover the investment cost in 4.51 years. The research results prove that the two-tier planning and configuration method constructed in this paper can better consider the economic consumption of new energy, and improve the operation economy of shared energy storage power stations and micro-energy grids. © 2022 Science Press. All rights reserved.

引用

页码：4403 / 4412

页数：9

共 24 条

[1] TENG Yun, SUN Peng, LUO Huanhuan, Et al., Autonomous optimization operation model for multi-source microgrid considering electrothermal hybrid energy storage, Proceedings of the CSEE, 39, 18, pp. 5316-5324, (2019)
[2] SHU Yinbiao, ZHANG Zhigang, GUO Jianbo, Et al., Study on key factors and solution of renewable energy accommodation, Proceedings of the CSEE, 37, 1, pp. 1-8, (2017)
[3] LI Jianlin, TIAN Liting, LAI Xiaokang, Outlook of electrical energy storage technologies under energy internet background, Automation of Electric Power Systems, 39, 23, pp. 15-25, (2015)
[4] SHENG Gehao, QIAN Yong, LUO Lingen, Et al., Key Technologies and application prospects for operation and maintenance of power equipment in new type power system, High Voltage Engineering, 47, 9, pp. 3072-3084, (2021)
[5] LI Jianlin, WANG Zhe, ZENG Wei, Et al., Review of energy management research on 100-megawatt electrochemical energy storage power stations, High Voltage Engineering, pp. 1-15, (2022)
[6] SUN Yushu, YANG Min, SHI Changli, Et al., Analysis of application status and development trend of energy storage, High Voltage Engineering, 46, 1, pp. 80-89, (2020)
[7] LOMBARDI P, SCHWABE F., Sharing economy as a new business model for energy storage systems, Applied Energy, 188, pp. 485-496, (2017)
[8] LIU J K, ZHANG N, KANG C Q, Et al., Cloud energy storage for residential and small commercial consumers: a business case study, Applied Energy, 188, pp. 226-236, (2017)
[9] SIOSHANSI R., Using storage-capacity rights to overcome the cost-recovery hurdle for energy storage, IEEE Transactions on Power Systems, 32, 3, pp. 2028-2040, (2017)
[10] WANG Shijun, PING Chang, XUE Guobin, Synergic optimization of community energy internet considering the shared energy storage, Electric Power, 51, 8, pp. 77-84, (2018)

← 1 2 3 →