Schedule-Based Operation Method Using Market Data for an Energy Storage System of a Customer in the Ontario Electricity Market

被引:2
|
作者
Hwang, Pyeong-Ik [1 ]
Kwon, Seong-Chul [2 ]
Yun, Sang-Yun [3 ]
机构
[1] Chosun Univ, Dept Elect Engn, 309 Pilmun Daero, Gwangju 61452, South Korea
[2] Korea Elect Power Corp KEPCO, KEPRI, 105 Munji Ro, Deajeon 34056, South Korea
[3] Chonnam Natl Univ, Dept Elect Engn, 77 Yongbong Ro, Gwangju 61186, South Korea
关键词
energy storage system; electricity charge reduction; market data; Ontario electricity market; optimal dispatch; schedule-based operation; MANAGEMENT; DISPATCH; USER;
D O I
10.3390/en11102683
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A new operation method for an energy storage system (ESS) was proposed to reduce the electricity charges of a customer paying the wholesale price and participating in the industrial conservation initiative (ICI) in the Ontario electricity market of Canada. Electricity charges were overviewed and classified into four components: fixed cost, electricity usage cost, peak demand cost, and Ontario peak contribution cost (OPCC). Additionally, the online market data provided by the independent electricity system operator (IESO), which operates the Ontario electricity market, were reviewed. From the reviews, it was identified that (1) the portion of the OPCC in the electricity charges increased continuously, and (2) large errors can sometimes exist in the forecasted data given by the IESO. In order to reflect these, a new schedule-based operation method for the ESS was proposed in this paper. In the proposed method, the operation schedule for the ESS is determined by solving an optimization problem to minimize the electricity charges, where the OPCC is considered and the online market data provided by the IESO is used. The active power reference for the ESS is then calculated from the scheduled output for the current time interval. To reflect the most recent market data, the operation schedule and the active power reference for the ESS are iteratively determined for every five minutes. In addition, in order to cope with the prediction errors, methods to correct the forecasted data for the current time interval and secure the energy reserve are presented. The results obtained from the case study and actual operation at the Penetanguishene microgrid test bed in Ontario are presented to validate the proposed method.
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页数:26
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