Stochastic joint optimization of wind generation and pumped-storage units in an electricity market

被引:479
作者
Garcia-Gonzalez, Javier [1 ]
Ruiz de la Muela, Rocio Moraga [1 ]
Matres Santos, Luz [1 ]
Mateo Gonzalez, Alicia [2 ]
机构
[1] Univ Pontificia Comillas, IIT, Madrid, Spain
[2] Gamesa Energia, Madrid 28015, Spain
关键词
day-ahead electricity markets; energy storage; optimization; profit maximization; wind power;
D O I
10.1109/TPWRS.2008.919430
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
One of the main characteristics of wind power is the inherent variability and unpredictability of the generation source, even in the short-term. To cope with this drawback, hydro pumped-storage units have been proposed in the literature as a good complement to wind generation due to their ability to manage positive and negative energy imbalances over time. This paper investigates the combined optimization of a wind farm and a pumped-storage facility from the point of view of a generation company in a market environment. The optimization model is formulated as a two-stage stochastic programming problem with two random parameters: market prices and wind generation. The optimal bids for the day-ahead spot market are the "here and now" decisions while the optimal operation of the facilities are the recourse variables. A joint configuration is modeled and compared with an uncoordinated operation. A realistic example case is presented where the developed models are tested with satisfactory results.
引用
收藏
页码:460 / 468
页数:9
相关论文
共 18 条
[11]   Hydro unit start-up costs and their impact on the short term scheduling strategies of Swedish power producers - Discussion [J].
Tufegdzic, N .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1997, 12 (01) :44-44
[12]   A Two-Stage Planning Model for Power Scheduling in a Hydro-Thermal System Under Uncertainty [J].
Nuernberg, Robert ;
Roemisch, Werner .
OPTIMIZATION AND ENGINEERING, 2002, 3 (04) :355-378
[13]   MULTISTAGE STOCHASTIC OPTIMIZATION APPLIED TO ENERGY PLANNING [J].
PEREIRA, MVF ;
PINTO, LMVG .
MATHEMATICAL PROGRAMMING, 1991, 52 (02) :359-375
[14]  
Roberts B., 2005, IEEE Power & Energy Magazine, V3, P24, DOI 10.1109/MPAE.2005.1405867
[15]  
ROOLF KD, 2006, COMBINING NUMERICAL
[16]   Short-term prediction of wind energy production [J].
Sánchez, I .
INTERNATIONAL JOURNAL OF FORECASTING, 2006, 22 (01) :43-56
[17]  
Schainker RB, 2004, 2004 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1 AND 2, P2309
[18]  
Schultz R, 2003, MATHEMATICS - KEY TECHNOLOGY FOR THE FUTURE, P623