Energy Management Strategy of Battery Energy Storage System Participating in Primary Frequency Control Based on Markov Decision Process

被引：0

作者：

Wen K. ^{[1
]}

Li W. ^{[1
]}

Zhang M. ^{[1
]}

Wang Z. ^{[2
]}

Wu G. ^{[2
]}

机构：

[1] School of Electrical Engineering, Dalian University of Technology, Dalian

[2] State Grid Dalian Electric Power Supply Company, Dalian

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2019年 / 43卷 / 19期

基金：

中国国家自然科学基金;

关键词：

Ancillary service; Battery energy storage system; Energy management strategy; Markov decision process; Primary frequency control;

D O I：

10.7500/AEPS20190107001

中图分类号：

学科分类号：

摘要：

For the energy management of battery storage system (BESS) in the primary frequency control (PFC) market, in order to maximize the economic benefits within battery life span, it is necessary to weigh operation costs and frequency control revenues on the basis of maintaining bidirectional frequency regulation capability. This paper reveals that the sequential decision of energy management is essentially a controlled Markov process. Therefore, the dynamic transfer of frequency response demand is described by continuous-time Markov chain, and the dynamic degradation of battery capacity based on lifecycle throughput is characterized. Then, a Markov decision model is built to maximize expected economic benefits within battery life span. Against the curses of dimensionality in solving the above model by using standard iterative algorithm, a dimensionality reduction parallel value iteration (DRPVI) algorithm with the characteristics of state space decomposition and subsequent state identification is proposed. Results show that the dynamic threshold strategy can significantly improve economic benefits, and DRPVI algorithm can effectively reduce redundant calculation and accelerate the efficiency of solution. © 2019 Automation of Electric Power Systems Press.

引用

页码：77 / 86

页数：9

共 32 条

[1]

Chen G., Li M., Xu T., System protection and its key technologies of UHV AC and DC power grid, Automation of Electric Power Systems, 42, 22, pp. 2-10, (2018)

[2]

Li Z., Wu X., Zhuang K., Et al., Analysis and reflection on frequency characteristics of East China grid after bipolar locking of "9•19" Jinping-Sunan DC transmission line, Automation of Electric Power Systems, 41, 7, pp. 149-155, (2017)

[3]

Li W., Jin C., Wen K., Et al., Active frequency response control under high-power loss, Automation of Electric Power Systems, 42, 8, pp. 22-30, (2018)

[4]

Sun L., Gao C., Tan J., Et al., Load aggregation technology and its applications, Automation of Electric Power Systems, 41, 6, pp. 159-167, (2017)

[5]

Wu J., Xue Y., Xie D., Optimization of reserve service capability made by electric vehicle aggregator, Automation of Electric Power Systems, 43, 9, pp. 75-83, (2019)

[6]

Li J., Yuan X., Yu Z., Et al., Comments on power quality enhancement research for power grid by energy storage system, Automation of Electric Power Systems, 43, 8, pp. 15-25, (2019)

[7]

Li W.F., Du P.W., Lu N., Design of a new primary frequency control market for hosting frequency response reserve offers from both generators and loads, IEEE Transactions on Smart Grid, 9, 5, pp. 4883-4892, (2018)

[8]

Li X., Huang J., Chen Y., Et al., Review on large-scale involvement of energy storage in power grid fast frequency regulation, Power System Protection and Control, 44, 7, pp. 145-153, (2016)

[9]

Zeng H., Sun F., Shao B., Et al., Analysis of Australian 100 MW energy storage operation and its enlightenment to China, Automation of Electric Power Systems, 43, 8, pp. 86-95, (2019)

[10]

Swierczynski M., Stroe D.I., Stan A.I., Et al., Selection and performance-degradation modeling of LiMO2/Li4Ti5O12 and LiFePO4/C battery cells as suitable energy storage systems for grid integration with wind power plants: an example for the primary frequency regulation service, IEEE Transactions on Sustainable Energy, 5, 1, pp. 90-101, (2014)

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