Title :
Price-Based Unit Commitment With Wind Power Utilization Constraints
Author :
Qianfan Wang ; Jianhui Wang ; Yongpei Guan
Author_Institution :
Ind. & Syst. Eng. Dept., Univ. of Florida, Gainesville, FL, USA
Abstract :
This paper proposes an optimal bidding strategy for independent power producers (IPPs) in the deregulated electricity market. The IPPs are assumed to be price takers, whose objectives are to maximize their profits considering price and wind power output uncertainties, while ensuring high wind power utilization. The problem is formulated as a two-stage stochastic price-based unit commitment problem with chance constraints to ensure wind power utilization. In our model, the first stage decision includes unit commitment and quantity of electricity submitted to the day-ahead market. The second stage decision includes generation dispatch, actual usage of wind power, and amount of energy imbalance between the day-ahead and real-time markets. The chance constraint is applied to ensure a certain percentage of wind power utilization so as to comply with renewable energy utilization regulations. Finally, a sample average approximation (SAA) approach is applied to solve the problem, and the computational results are reported for the proposed SAA algorithm showing the sensitivity of the total profit as the requirement of wind power utilization changes.
Keywords :
approximation theory; power generation dispatch; power generation scheduling; power markets; power utilisation; wind power; IPP; SAA; deregulated electricity market; energy imbalance; generation dispatch; independent power producers; optimal bidding strategy; renewable energy utilization regulations; sample average approximation; stochastic price; unit commitment problem; wind power utilization constraints; Convergence; Electricity; Generators; Real-time systems; Stochastic processes; Uncertainty; Wind power generation; Chance constrains; mixed integer programming; price based unit commitment; sample average approximation; stochastic programming; wind power;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2012.2231968