| The reform of the electricity market has achieved good results in the power generation, opening up the electricity distribution side at this stage become a hot market research. Separation of transmission and distribution has become a electricity market's restructuring trend, the supply companies, as a market participant, in order to reduce the cost of the purchasing, avoid the overall risk, it is necessary to participate in a number of market transactions, and market bidding strategy optimization. An open electricity market, usually in the distribution side there is a similar long-term futures market and spot transactions similar to the structure of the short-term market, the supply companies usually take two to buy electricity market to meet the needs of users. But in fact, the supply company is always purchase most part in the long-term market part first, and then the remaining part to buy in the short term market, then it is difficult to establish the actual consumption of electricity, only on the basis of the total demand forecast value to make the purchase decision-making. As forecast errors, if there is the surplus of purchase quantity, the electricity trading center must be compensation; if there is shortage of purchase quantity, it must increase the power company's purchase cost, make the power company face to operational risks. Therefore, in the market environment, how to determine the optimal purchasing quantity of distribution company and it can reduce the distribution company's purchasing cost under the minimum the risk of power purchase costs, has become a very worthwhile research topic.This paper researches electricity purchasing strategy and risk assessment for Electricity Purchaser (EP). Through analyzing the characteristics involving in EP's long-term electricity purchasing problem, a general model based on modern portfolio theory is presented. Detail discussions are focused on electricity purchasing portfolio selection on two commonly existing markets: long-term contract and spot market, in order for discovering the relationship between long-term contract prices, contract amount with spot price. Specific examples set by the electricity purchaser's purchasing strategy and carry out a risk assessment, then verify the validity of the method. To address this problem of the purchase distribution problem, the paper is divided into four phases to discuss in detail:1. Through the existing business model and operating structure of the electricity market, we make up with the problem of the electricity purchaser to distribute the quantity between the long-term (contract) and the short-term market (electricity auction market), and through portfolio theory to establish a common objective function compose by the costs and risk. 2. The objective function is the meaning of choosing the purchase option, which is to enable the purchase cost smallest, meanwhile ensure that the probability of achieving its request to the confidence level. Well, this model is a classic opportunity constrained programming model. Therefore, this paper introduces the opportunity constraint programming, and the transfer the mathematical model through a certainty equivalent.3. Simplification purchasing model is a typical nonlinear constrained optimization problem. In view of this optimization problem, genetic algorithm is a good method to solve. Therefore this paper use C + + as a development platform to program this genetic algorithm procedures. Then, transfer the certainty equivalent model on last step to the genetic algorithm's purchasing distribution model.4. According to historical data, we can know the statistics of the contract market and the auction market for electricity prices and quantities, and also the two market-related factors, and then we can obtain the purchase quantity distribution ratio. Then, change the two markets'price of standard deviation and mean, check the distribution ratio's data changes. Through analysis and comparison that we can have the relevance of the two markets.
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