Optimal bidding strategies for day ahead electricity market by risk constrained stochastic price based unit commitment

Shileh Baf, Amir
Optimum bidding curves for a generating company to take part in the day ahead energy market are developed throughout this thesis. Continuous aim of the generating company to maximize its profit will be partly fulfilled by optimizing its bidding in the market. Price uncertainty has always been a major issue for proper bidding and maximizing the payoff. In contrast with traditional Price Based Unit Commitment which is only dependent on a good forecast of energy prices, stochastic programming takes care of the price volatility by generating different possible scenarios using Monte Carlo Simulation method. Generating Company would be able to control his risk factor by indicating its risk tolerance in the model and trade some of the profit in favor of taking less risk. MATLAB platform is used to code the Mixed Integer Linear Programming model while CPLEX 9.0 solver engine is utilized to solve the optimization problem. Several case studies have been examined to show the validity of the model and the results have been interpreted to give more insight of the optimization solution.