Study On Bidding Decision For Power Plant In Power Market

Power market is the trend of Chinese power industry. Chinese power market is in the original period which there is competition only in the supply side. Power plant gets profit through competition as the main part in the market competition. How to built bidding decision model according with the market trade condition, establish optimal bidding strategy to maximize bidding profit of the plant is in urgent need for the power plant. In this thesis the power plant bidding strategy problem is studied from point of power plant taking part in power market bidding trade and increasing the profit of power plant.At present the main trade is for energy in Chinese power market. The bidding trade of the power plants is going on mainly in the medium and long trade and day-head market. In this thesis aiming at the main problem that will be met in the power plant bidding trade combined the power plant's producing characteristics and real condition in Chinese power plant developing, the power plant bidding decision framework is built. In this framework three aspects of problems are analyzed which are optimal generation allocation in medium and long trade market, multi-periods bidding in day-ahead trade market and the influence of transmission constraints on power plant bidding decision in peak load trade period.The energy trade in Chinese power market should be accomplished in year market, month market and day-ahead market. Influenced by the generation cost, different prices in market and relationship between supply and demand the limited generation allocated in each market according to different proportion will lead to different risk and profit. To harmonize the profit and risk of the power plant in this thesis an optimal allocation decision model based on satisfaction is proposed. In this model the fuzzy investment portfolio theory is used for reference. Combined with the experience of the decision-maker and his attitude to risk, the indexes reflecting risks and profits are expressed by fuzzy sets. The optimal generation allocation strategy accord with decision-maker satisfaction is decided by fuzzy optimization.In day-ahead trade market the main problem should be solved is arrange next day bidding generation in each trade period reasonably to get more profit in premise of satisfy the contract generation. In this thesis the historic trade data is analyzed, the fuzzy regression model which reflect the relationship between the market price and generator allocated generation is given. On this basis the multi-period bidding decision model based on fuzzy chance-constrained program model is built. In this model the risk problem caused by uncertainty of market power price is considered, the decision-maker's attitude to risk is reflected by selecting confidence level and tradeoff coefficient of pessimism profit and optimism profit. Considering the characteristic of this model the BPSO and GA are united to solve this problem. Aiming at the characteristics of the object and constraint condition, the heuristic rules and particle generation strategy to solve this model is given to assure the new particle is the feasible solve for the optimization problem and the performance of BPSO is improved.In the peak load period, the transmission power in the transmission equipment will reach the transmission capacity limit which can affect the clearing result of the power market and the bidding profit of the power plant. In this thesis the linear supply function equilibrium model of contracted power is considered, the power bidding decision with transmission constraints during peak load period is studied. The Nash equilibrium decisions with and without network constraints are compared. For the special real condition of power plant bidding in peak load period an advanced circulation iteration method is proposed to solve Nash equilibrium. This method prohibits iteration disconvergence by improper selection of original data. The iteration process guarantees that the congestion condition of the network will not change. And the solved Nash equilibrium has real sense.To make reasonable bidding strategy based on its characteristics and market environment outside, the power plant need to analyze and evaluate the position of itself and competing rival. In this thesis the market power evaluation index system for power plant is built. The evaluation index system is separated into pre-evaluation and post-evaluation index. The composition of the pre-evaluation is analyzed for emphasis. On the basis of analyzing must-run capacity the power flow tracing method is used to analyze influence of plant on node and branch from the point of microcosmic. The power plant serving control area is proposed. And on this basis the pre-evaluation index reflecting influences of power plant on node, branch, area and the system is formed. The pre-evaluation index is to compare the advantage of power plant position and the post-evaluation index is to evaluate self-market power and the bidding strategy.This research work is supported by National Nature Science Foundation (50377021). Part of the research results has been applied in Operation Decision Supporting System of Yantai Power Plant. This project achieved the Shandong Province Science and Technology Advancement Award.