Unit Commitment Of Independent Power Producer In Electricity Market

With the electrical industry being restructured and the electricity market established, independent power producers (IPP) are being confronted with great challenges they have never faced before. The profit of IPP to some extent is determined by the information taken from electricity market and the operation strategy of their power plant. They have to make bidding strategy scientifically to maximize their operation profits. As the electric power industry evolves from being a fully regulated, cost-based industry into functionally and corporately separate generation entities, unit commitment problem (UC) becomes an essential issue of independent power producers. To meet the new character of optimizing UC in the electricity market, two UC models were constructed in this paper. The first one is based on forecasted marginal price and takes profit as optimizing goal, this model can give IPP a valuable reference when they are making their bidding strategy; the latter is a cost minimization model intending to help IPP lower their operation cost.Based on comprehensively comparing some sorts of algorithms available for solving UC and combining the characters of the models being proposed in this paper, genetic algorithm was chosen as numerical computing method. Some improvements concerning coding, operator designing, constrain handling etc. were made so as to make the algorithm more suitable for the models constructed in the paper. Numerical analysis illustrates that the improved genetic algorithm (IGA) designing is successful in solving high-dimension, multi-constrains, and nonlinear UC problem. The designing method is also helpful for solving other complex system optimization problems. Additionally, two bidding models were proposed in this paper. These models made bidding strategies from different aspects and can give IPP a valuable reference when they design their bidding curves.