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Multi Objective Desired Values Optimization for Power Load Distribution

Author: SunJing
Tutor: YuJiLai
School: Harbin Institute of Technology
Course: Electrical Engineering
Keywords: power system energy-saving and ejection-decreasing a multi objective desired values optimization dynamic weighted priority
CLC: F224
Type: Master's thesis
Year: 2010
Downloads: 222
Quote: 2
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Abstract


With the fast development of power industry and its marketization, the power system is becoming a large system which contains pluralistic benefit Groups. These Groups may involve many factors such as economic and environment. So optimization for power load distribution must give consideration to the benefit of power generation enterprises, grid company, social environment and so on, in order to get the greatest optimum arrangement of resource in more aspects.The tradition optimization models in power system is based on the minimization or the maximization of the objectives functions.However, The objectives that the optimization for power load distribution chase for, such as the degree of reducing energy consumption and emission of pollutants, will be proposed in form of periodic desired value rather than minimum value. Therefore, the actual demand cannot be met by the traditional idea of singal objective or multi objective optimization. According to this aspect, the paper proposed the conception of multi objective desired values optimization, built models for multi objective desired values optimization. And the paper gave several different computation methods based on models.Take the unit static load optimization distribution for consideration in power dispatch, for example, a multi objective desired values optimization models were built, which emphases on target of the coal consumption, pollutant and the expense of Grid Company. It is different from the traditional optimization problems, as it pursuits the objectivities to the expectation value rather than the optimization value considering the impacts of different objectives. The solution of this model according to the traditional thoughts multi-objective optimization ended when the objectives reach the desired value.A solution for the multi objective desired values optimization model which is based on dynamic weighted algorism was proposed in this paper. The algrithm adopted the multi objective weighted form estimated the weighted values by steadily narrowing the completion rate difference of different objectives. A power static load distribution strategy for the demands of multi objective desired is obtained. The initial weighted values have nothing to do with the emphasis degree of every objective, and have no effect on the final result. Through a real example, the correctness of the multi-objective desired control idea and the validity of the multi-objective weighted method of solving problems are verified.Based on the theory that the optimal values vary little at the optimal target point neighborhood, a multi-objectives hierarchy analysis algorism has been built to show the different emphasis degree on the different objective. The hierarchy can be reflected by the calculation sequence and the single objective’s value. Because every step is near the former optimal target point, the neighborhood control is carried out by controlling distance between the optimal target points to the former point. That is to say, every step of the multi-objectives optimization algorism is single objective optimization, so the key of neighborhood control is the range of neighborhood’s selection. Through a real example, this approach will have a extensive applicability It can not only solve the situation that partial objectives chase for the expectation value, the other objectives chase for the optimal value, but also give answers to the problem for all the objectives chase for the expectation value.This work is supported by the National Natural Science Foundation of China (No 50877014).

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CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
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