Wind power bidding based on chance-constrained optimization

Wind power bidding is critical for wind power producers operations in an electricity market. Due to the uncertainly and variability of wind power output, some markets impose a penalty on the deviation between the wind power bids in the day-ahead market and the real wind power output in the realtime market. The objective of a wind power producers bidding problem is to maximize the producers profit while minimizing the penalty and ensuring the output from its wind farms can be utilized to the largest extent. In this paper, we present a wind power bidding strategy based on chance-constrained optimization. The chance constraint is used to define the probability that certain amount of wind power bid into the market can be accepted. We formulate the problem as a chance-constrained two-stage (CCTS) stochastic optimization program. The second stage represents the many possible realizations of wind power output by scenarios. We also consider pumped-storage hydro power plants as storage to accommodate the fluctuation of wind power. Sample Average Approximation (SAA) is used to solve the problem. Numerical examples are also provided.