DocumentCode
107076
Title
Control and Size Energy Storage Systems for Managing Energy Imbalance of Variable Generation Resources
Author
Xinda Ke ; Ning Lu ; Chunlian Jin
Author_Institution
Electr. & Comput. Eng. Dept., North Carolina State Univ., Raleigh, NC, USA
Volume
6
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
70
Lastpage
78
Abstract
This paper presents control algorithms and sizing strategies for using energy storage to manage energy imbalance for variable generation resources. The control objective is to minimize the hourly generation imbalance between the actual and the scheduled generation of wind farms. Three control algorithms are compared: 1)tracking minute-by-minute power imbalance; 2)postcompensation; and 3)precompensation. Measured data from a wind farm are used in the study. The results show that tracking minute-by-minute power imbalance achieves the best performance by keeping hourly energy imbalance zero. However, the energy storage system (ESS) will be significantly oversized. Postcompensation reduces the power rating of the ESS but the hourly energy imbalance may not be reduced to zero when a large and long-lasting power imbalance occurs. A linear regression forecasting algorithm is developed for a two-stage precompensation algorithm to precharge or predischarge the ESS based on the predicted energy imbalance. An equivalent charge cycle estimation method is proposed to evaluate the effect of providing the energy balancing service on battery life. The performance comparison shows that the precompensation method reduces the size of the ESS by 30% with satisfactory performance.
Keywords
compensation; energy storage; load forecasting; power generation control; power generation scheduling; regression analysis; wind power plants; battery life; control systems; energy imbalance management; equivalent charge cycle estimation; generation imbalance; linear regression forecasting; minute-by-minute power imbalance; post compensation; power rating; precompensation; scheduled generation; size energy storage systems; variable generation resources; wind farms; Batteries; Life estimation; US Department of Defense; Wind farms; Wind forecasting; Wind power generation; Ancillary service; energy management; energy storage; operation scheduling; renewable integration; wind forecast;
fLanguage
English
Journal_Title
Sustainable Energy, IEEE Transactions on
Publisher
ieee
ISSN
1949-3029
Type
jour
DOI
10.1109/TSTE.2014.2355829
Filename
6922575
Link To Document