Research On Mid-long Term Contract For Difference Decomposition And Related Issues

Considering the uncertainty of the day-ahead market price, in order to reduce the market risk, CfD (Contract for Difference) is introduced to hedge against market risk in some domestic markets. Usually, contract energy accounts for more than 80% of total energy. Generally, CfD that generators and buyers signed are energy contracts, how to decompose the total contract engergy while covering all participants' benefit, is an issue which is important and worth studying. The contributions are summarized as follows:In order to apply the deterministic contract decomposition algorithm to decompose contract energy, typical load curve must be prepared. Abnormal historical load data affect the validity of typical load curve. The notion of D_ht is proposed, it is applied to identify the abnormal load data, and combined with t test to identify and correct the load outlier. The historical data of Zhejiang province is used to test the suggested approach, the result indicates that the algorithm is simple and effective.An analysis on the deterministic contract decomposition algorithm of East China electricity market is presented. Average contract quantity proportion, correlation of contract quantity proportion and price have been adopted to evaluate the equity of the algorithm. Expectation, standard deviation and half standard deviation have been adopted to evaluate the income and risks of generators. An empirical analysis is done based on the historical data of East China electricity market. The result indicates that the algorithm treats buyer and generators fairly in the trial operation, CfD contracts help to reduce the generator's risk effectively.From the viewpoint of cooperative game, per unit net revenue is adopted to evaluate single buyer and generators' utility, the conditions under which the generators and buyers are willing to participate in contract decomposition is derived. In a single-buyer-single-supplier market, if both parties are risk-averse, the coalition is always stable; if both parties are risk-adventurous, the coalition is always unstable. In a single-buyer-multi-supplier market, the coalition is conditionally stable. A numerical study based on the historical data of some China provincial electricity market is performed. The result indicates that the proposed model is reasonable and effective.Traditional decomposition of CfD decomposition is based on the forecasted load, the load uncertainty may lead to that decomposition result can't satisfy the expected target, so considering load uncertain is necessary when decomposing contract. A stochastic load model based on the GARCH (Generalize Autoregressive Conditional Heteroscedasticity) model is suggested for contract decomposition. Taking the minimized standard deviation of the difference between contract ratio and appointed ratio as the objective, the probability that actual standard deviation is smaller than the expected standard deviation as a chance constraint, an optimal contract decomposition based on chance constrained programming is proposed. A genetic algorithm based on Monte Carlo simulation is used to solve the problem, the numerical result indicates that the model and method is effective.Traditional contract decomposition method is based on such idea: "contracts are decomposed in a centralized way; generation companies accept the result passively". A new contract decomposition method named "generation company declaration method" is presented. The maintenance, the power capacity of units, etc. are taken into account. A difference evaluation function based on errors is adopted to build a multiple objective optimization model, "linear weighted sum" and minimax method are respectively selected to convert the original problem into a single objective optimization. A case study of a domestic market is performed, the results indicate that the suggested model is effective, the solution of the original problem can be obtained by both conversion methods. When minimax method is selected, the difference in generation companies' adjustment quantity is smaller.