Energy Storage Sizing Optimization and Sensitivity Analysis Based on Wind Power Forecast Error Compensation

被引:7
作者
Yu, Xiaodong [1 ,2 ]
Dong, Xia [2 ]
Pang, Shaopeng [2 ]
Zhou, Luanai [3 ]
Zang, Hongzhi [4 ]
机构
[1] Shandong Univ, Minist Educ, Key Lab Power Syst Intelligent Dispatch & Control, Jinan 250061, Peoples R China
[2] Qilu Univ Technol, Shandong Acad Sci, Sch Elect Engn & Automat, Jinan 250353, Peoples R China
[3] Qingdao Harbor Vocat & Tech Coll, Qingdao 266400, Peoples R China
[4] State Grid Shandong Elect Power Co, Econ & Technol Res Inst, Jinan 250001, Peoples R China
关键词
wind power; error compensation; energy storage system (ESS); optimization; sensitivity analysis; SYSTEM;
D O I
10.3390/en12244755
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
To better track the planned output (forecast output), energy storage systems (ESS) are used by wind farms to compensate the forecast error of wind power and reduce the uncertainty of wind power output. When the error compensation degree is the same, the compensation interval is not unique, different compensation intervals need different ESS sizing. This paper focused on finding the optimal compensation interval not only satisfied the error compensation degree but also obtained the max profit of the wind farm. First, a mathematical model was proposed as well as a corresponding optimization method aiming at maximizing the profit of the wind farm. Second, the effect of the influencing factors (compensation degree, electricity price, ESS cost, and wind penalty cost) on the optimal result was fully analyzed and deeply discussed. Through the analysis, the complex relationship between the factors and the optimal results was found. Finally, the comparison between the proposed and traditional method was given, and the simulation results showed that the proposed method can provide a powerful decision-making basis for ESS planning in current and future market.
引用
收藏
页数:21
相关论文
共 35 条
[1]   Statistical analysis of wind power forecast error [J].
Bludszuweit, Hans ;
Antonio Dominguez-Navarro, Jose ;
Llombart, Andres .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (03) :983-991
[2]   A Probabilistic Method for Energy Storage Sizing Based on Wind Power Forecast Uncertainty [J].
Bludszuweit, Hans ;
Antonio Dominguez-Navarro, Jose .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (03) :1651-1658
[3]   Optimal Energy Storage Sizing and Control for Wind Power Applications [J].
Brekken, Ted K. A. ;
Yokochi, Alex ;
von Jouanne, Annette ;
Yen, Zuan Z. ;
Hapke, Hannes Max ;
Halamay, Douglas A. .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2011, 2 (01) :69-77
[4]   Optimal Allocation and Economic Analysis of Energy Storage System in Microgrids [J].
Chen, Changsong ;
Duan, Shanxu ;
Cai, Tao ;
Liu, Bangyin ;
Hu, Guozhen .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2011, 26 (10) :2762-2773
[5]   Two-Stage Optimization of Battery Energy Storage Capacity to Decrease Wind Power Curtailment in Grid-Connected Wind Farms [J].
Dui, Xiaowei ;
Zhu, Guiping ;
Yao, Liangzhong .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (03) :3296-3305
[6]  
[兑潇玮 Dui Xiaowei], 2017, [电网技术, Power System Technology], V41, P434
[7]  
Eyer J.M., 2008, SAND20080978 SAND NA
[8]  
Feng Jiangxia, 2013, Automation of Electric Power Systems, V37, P90
[9]   Energy storage sizing for wind power: impact of the autocorrelation of day-ahead forecast errors [J].
Haessig, Pierre ;
Multon, Bernard ;
Ben Ahmed, Hamid ;
Lascaud, Stephane ;
Bondon, Pascal .
WIND ENERGY, 2015, 18 (01) :43-57
[10]  
Ingram A.E., 2008, P ASME 2005 INT SOL