Optimal Offering Strategies for Wind Power Producers Considering Uncertainty and Risk
- 30 August 2011
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Systems Journal
- Vol. 6 (2) , 270-277
Abstract
This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.Keywords
This publication has 26 references indexed in Scilit:
- Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear approachEnergy, 2011
- A STATCOM-Control Scheme for Grid Connected Wind Energy System for Power Quality ImprovementIEEE Systems Journal, 2010
- Harmonic assessment of variable-speed wind turbines considering a converter control malfunctionIET Renewable Power Generation, 2010
- Power optimization of wind turbines with data mining and evolutionary computationRenewable Energy, 2010
- Short-Term Trading for a Wind Power ProducerIEEE Transactions on Power Systems, 2010
- Reserve-constrained multiarea environmental/economic dispatch based on particle swarm optimization with local searchEngineering Applications of Artificial Intelligence, 2009
- Minimization of Imbalance Cost Trading Wind Power on the Short-Term Power MarketIEEE Transactions on Power Systems, 2006
- Robust Self-Scheduling Under Price Uncertainty Using Conditional Value-at-RiskIEEE Transactions on Power Systems, 2005
- Trading wind generation in short term energy marketsIEEE Transactions on Power Systems, 2002
- Conditional value-at-risk for general loss distributionsJournal of Banking & Finance, 2002