Research On Short-Term Economic Operation Of Generation Company In Power Market

The electric power industry has experienced or has been experiencing an unprecedented reformation of deregulation to traditional monopoly and introduction of competition in many countries all over the world. Many requirements about the economic and technological issues in power market are presented. In traditional power systems, power dispatch organization plan generation schedule of the generation company (GENCO) according to the security and economic of power systems, whereas in the power market the independent GENCO has to cope with the economic operation which includes planning the self-schedule, establishing the generation bidding model and solving, controlling the risk of bidding strategy and etc. Therefore, this dissertation devoted to the research on short-term economic operation of GENCO in power market. The major research work is outlines as follows:(1) In the aspect of generation schedule optimization, the real number matrix is used to represent generation schedule, and therefore genetic operation or particle swarm optimization can solve the unit commitment (UC) problem, avoiding the disposal of the suboptimal economic dispatch (ED) problem. The new repairing mechanism that is used to adjust the chromosome or particle, guarantees that the generation schedule satisfies system and unit constraints. The window mutation and the greedy searching based on Priority list (PL) are applied to improve the convergence of genetic algorithm and particle swarm optimization respectively. Moreover, a new approach for solving optimal bidding strategies based hourly self-scheduling in a GENCO that participates in energy and ancillary service markets is presented. The matrix real-coded gentic algorithm (MRCGA) is used to solve the price-based unit commitment problem. (2) In the aspect of GENCO bidding strategy study, a new risk decision-making model of GENCO's bidding in System-Margin-Price power market based on the SP/A (Security, potential and aspiration) theory is built. In the model, the opportunity cost of economic theory is used to analyze and evaluate the potential of GENCO's biding strategy, and the security and aspiration are also analyzed and described mathematically. Because of considering the decision psychology and the self-scheduling, the proposed model is close to the actual decision-making process of GENCO. Furthermore, GENCO has different risk attitude and profit purpose towards different bidding blocks during the course of bidding decision in Pay-as-Bid power market, and accordingly the safety-first and the two mental accounts portfolio theory are introduced to model the psychology of GENCO, and a new risk decision-making of GENCO's bidding strategy is built also. This model is close to the actual decision-making process of GENCO in Pay-as-Bid power market too.(3) In the aspecnt of risk management of GENCO's bidding, a new risk evaluation method which is based on value at risk (VaR) is presented. Moreover, stochastic decision-making model of GENCO's bidding strategy and the model of bidding strategy adjustment are proposed also with using the presented method. Because of risk attitude of GENCO being expressed by chance constraints based on the method, a new aspect which research on GENCO's bidding strategy considering market risk is advanced.