Strategic Investments of Large Scale Battery Energy Storage Systems in the Wholesale Electricity Market

被引:0
|
作者
Li, Ang [1 ,2 ]
Fan, Lei [3 ]
Peng, Jiming [1 ]
Wang, Yubo [2 ]
机构
[1] Univ Houston, Dept Ind Engn, Houston, TX 77204 USA
[2] Siemens Technol, Princeton, NJ 08540 USA
[3] Univ Houston, Dept Engn Technol, Houston, TX USA
关键词
Battery Energy Storage System; Bayesian Optimization; Locational Marginal Pricing;
D O I
10.1109/KPEC61529.2024.10676253
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
This study addresses the investment strategy of large-scale Battery Energy Storage Systems (BESS) within wholesale electricity markets, emphasizing the viewpoint of BESS owners. The challenge of planning for large-scale BESSs, without accounting for potential shifts in wholesale market prices, could lead to unforeseen changes in Locational Marginal Prices (LMP). To navigate these challenges, we introduce a novel three-phase methodology tailored to the BESS investment landscape. The initial phase employs a Bayesian optimization to pinpoint the most efficient BESS configurations. Subsequent phases focus on optimizing market clearances for LMPs and establishing the most effective BESS operational schedules through iterative dispatch optimization tasks. The efficacy of our approach is confirmed through a decade-long simulation within the Electric Reliability Council of Texas (ERCOT) market framework. Our findings reveal that, compared to traditional grid search techniques, our Bayesian optimization approach achieves equivalent solution accuracy 16 times more rapidly.
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页数:4
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