Evaluating risk-constrained bidding strategies in adjustment spot markets for wind power producers

被引：38
作者：
Angeles Moreno, M. [1 ]
Bueno, Miriam [1 ]
Usaola, Julio [1 ]
机构：
[1] Univ Carlos III Madrid, Madrid 28911, Spain
来源：
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2012年 / 43卷 / 01期
关键词：
Electricity markets; Uncertainty; Wind energy; Imbalance prices; Risk management; CVaR; PROBABILISTIC FORECASTS; GENERATION; UNCERTAINTY; SYSTEM;
D O I：
10.1016/j.ijepes.2012.05.059
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：
Participation of wind energy in the day-ahead electricity market implies large deviations from the initial schedule, which leads to costs for the wind farm owner. By means of short-term wind power prediction programs, the contracted energy can be updated in adjustment spot markets, reducing the power deviations and increasing the total revenue for wind power producers. Taking into account the different uncertainties involved in the problem, an optimal bidding strategy can be used to maximize the wind power producer revenues. As the strategy could be very risky due to all these uncertainties, a CVaR constraint for the bid that maximizes the expected revenue is proposed as a way of reducing the risk. A test-case using the Spanish market rules during a 10-month period has been used to check the potential benefits of the aforementioned strategies. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码：703 / 711
页数：9
相关论文
共 40 条
[21]  
Monteiro C., 2009, Wind power forecasting: State-of-the-art 2009
[22]   Short-Term Trading for a Wind Power Producer [J].
Morales, Juan M. ;
Conejo, Antonio J. ;
Perez-Ruiz, Juan .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (01) :554-564
[23]   A decision-making tool for project investments based on real options: the case of wind power generation [J].
Munoz, J. I. ;
Contreras, J. ;
Caamano, J. ;
Correia, P. F. .
ANNALS OF OPERATIONS RESEARCH, 2011, 186 (01) :465-490
[24]   A three-stage short-term electric power planning procedure for a generation company in a liberalized market [J].
Nabona, Narcis ;
Pages, Adela .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2007, 29 (05) :408-421
[25]   Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts [J].
Nielsen, HA ;
Madsen, H ;
Nielsen, TS .
WIND ENERGY, 2006, 9 (1-2) :95-108
[26]   Forecasting next-day electricity prices by time series models [J].
Nogales, FJ ;
Contreras, J ;
Conejo, AJ ;
Espínola, R .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (02) :342-348
[27]   Skill forecasting from ensemble predictions of wind power [J].
Pinson, P. ;
Nielsen, H. Aa. ;
Madsen, H. ;
Kariniotakis, G. .
APPLIED ENERGY, 2009, 86 (7-8) :1326-1334
[28]   Trading wind generation from short-term Probabilistic forecasts of wind power [J].
Pinson, Pierre ;
Chevallier, Christophe ;
Kariniotakis, George N. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (03) :1148-1156
[29]   From Probabilistic Forecasts to Statistical Scenarios of Short-term Wind Power Production [J].
Pinson, Pierre ;
Madsen, Henrik ;
Nielsen, Henrik Aa. ;
Papaefthymiou, George ;
Kloeckl, Bernd .
WIND ENERGY, 2009, 12 (01) :51-62
[30]   Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach [J].
Pousinho, H. M. I. ;
Mendes, V. M. F. ;
Catalao, J. P. S. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 39 (01) :29-35
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