A Study Of Electricity Value Equivalent Pricing Method And Bidding Strategies Of Power Suppliers

The objective of power system restructuring is to improve efficiency of electricity production, to reduce customer tariffs, and to make power industry develop continual as well as to maximize the social welfare. Electricity pricing is the key issue in power system restructuring. A scientific and reasonable pricing method should lead the market on to arrive at the balance of demand and supply for both short term and long term and lead to effective use of electricity resource. However, because of the particularity of electric power system, the real electricity market is not a perfect competitive one but rather locational oligarchic market and the power suppliers often maximize their own profits by strategy bidding. Pricing methods have great effects on the bidding strategies of power suppliers. In this dissertation, the pool purchase pricing method in electricity market and bidding strategies of power suppliers, which are two key issues in electricity market, are mainly studied. Six sub-issues will be addressed.The first, the day-ahead pool market is the base and core of the whole electricity market. So the study of pool purchase pricing is of key importance. After analyzing the problems of existing pricing methods, the basic principles of developing electricity markets and basic requirement of an open power market with electricity shortage are introduced. Then the Electricity Value Equivalent (EVE) Pricing Method is also introduced. Analytical expression of EVE Pricing Method is established. The right terminal principle and the ten market characteristics of EVE Pricing Method are described.The second, a trade mode for hydro-units in electricity market and a corresponding EVE pricing method are presented. The basic principle of this pricing method is that the hydro-energy is preferentially used, while the pool purchase price of it is determined by its equivalent unit in the thermo-unit pool market. Hydro-units' abilities to repay loans are discussed. And the relations between the hydro-units' repayment periods, capacity costs, interest rates of loans and the capacity cost references in the thermo-market are obtained. A simple case study is presented.The third, the effects of different pricing methods on the bidding strategies of power suppliers are studied. In the aspect of price decision-making, under uniform and PAB (pay as bid) pricing methods, power suppliers tend to bid above their true costs. However, it is proved that under the EVE pricing method, the payments to power suppliers are not sensitive to their bids, and their best bidding strategies are to bid the true costs. As for production decision-making, under the uniform pricing method, some power suppliers can get excessive profits by withholding generation capacities; but under PAB and EVE pricing methods, power suppliers will lose their profits if they withhold generation capacities. In the aspect of the inducing the power suppliers to play fair in bidding, EVE pricing method is better than the uniform and PAB pricing methods, expressing the internal autonomy mechanism of the EVE pricing method. Under electricity shortage, the bad bidding action are also restrained by EVE pricing method. The effect of the capacity cost reference on bidding strategies of power suppliers is preliminarily studied, which is useful for setting reference more reasonable.The fourth, short term market clearing price prediction is the base for power supplier's bidding. A market clearing price prediction method based on ARMAX model is developed. The inputs of the prediction model are selected by comparing the correlations between the historical loads and market clearing price. A k step ahead optimal prediction method is then employed. Case study based on real data of the New England Pool is given, and the results show that this prediction method has good precision. The optimal amount of historical data for parameter estimation and for the determination of the order of error polynomial are studied by using real data.The fifth, estimating other power supplier's bids i...