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Study on the straight power transactions between large power users and generation enterprises

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3 Author(s)
Xiying Chen ; China Electr. Power Res. Inst., Beijing, China ; Jiangyi Hu ; Xuesong Zhang

On the basis of analyzing the practical significance of developing the straight power purchasing for large power users in China and the advantages and shortcomings of this trade pattern, from the viewpoint of economics and marketing, and combining the electricity market theories and bidding algorithm and so on with straight power purchasing for large power users, the mathematical models are built. Large electricity users in China have three kinds of direct trading algorithms. In Consultation-sided trading algorithms, The two sides consultate trading power, price, electricity load, time and other factors, reporting to the electric power dispatching center and trading center together, the algorithm simple. Centralized auction trading algorithms with the conventional focus on the same bidding algorithm. So the paper focus on large users in China the Centralized algorithm for matching-type transactions. Direct purchase of electricity from large users in China centralize matching algorithm-based transactions in order to maximize social welfare as the goal.According to generators and large electricity users to declare, grid congestion situation, consider the requirement to meet the constraint. Access to large users and power producers in the trading platform focused on direct transactions. For different trading hours, the large users to declare the purchase of electricity prices and to buy electricity, power generation companies to declare the sale of electricity prices and electricity sales. According to the parties to declare the purchase electricity sales curve, considering the transmission losses were calculated in different large users and power generation corporate social welfare (the price between the two sides), the premise of meeting the network security constraints, priority is matching the biggest transaction of social welfare to form a transaction matching pairs; in sale purchase offer both sides, based on the principle of social benefits are divided to form t- - wo sides of the transaction price; repeat the above steps until less than social welfare. In order to improve computing speed, quick calculation method is given.The final example has been verified that the algorithm is faster than conventional optimization algorithm to calculate the speed of 0.2 times 0.3 times, The matchmaking tradeoff model and a fast algorithm to solve this model is given with emphasis. Finally case study is given.

Published in:

Power System Technology (POWERCON), 2010 International Conference on

Date of Conference:

24-28 Oct. 2010