考虑负荷为概率负荷的机组承诺问题的解法

B. Saravanan, K. Swarup, D. Kothari
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引用次数: 0

摘要

本文将负荷考虑为随机(概率)变量,而不是确定性变量,给出了电力系统在一段时间内总生产成本最小的机组投入问题的求解方法。UCP是一个混合整数的大规模非线性规划。如果单位数量多,时间跨度大,那么分析就会变得更复杂。因此,研究人员仍在积极寻找机组承诺问题的解决方案。本文提出了将负荷作为一个概率变量而不是常规确定性变量来考虑的方法。通过这种方式考虑负载,我们可以将UCP问题作为一个实时问题来解决。在该方法中,采用LR方法将问题分解为一个原问题和一个对偶问题,并利用动态规划方法求解每个子问题。采用粒子群算法求解经济调度问题。通过与传统方法的比较,给出了生产成本最小的发电机调度方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A solution to unit commitment problem by considering load to be a probabilistic one
This paper gives a solution for the unit commitment problem (UCP) for an power system to minimize the total production cost over a period of time by considering the load as a random(Probabilistic) variable instead of a deterministic one. The UCP is a mixed integer large scale non linear program. If the number of unit is more and the time horizon is large, then the analysis become more complex. That is the reason still researches are active in finding the solution for unit commitment problem. In this paper the proposed methodology by considering the load as a probabilistic variable instead of regular deterministic one. By considering the load in this way we can solve the problem of UCP as a real time problem. In the proposed methodology LR method is used to separate the problem in to a primal and dual problem and each sub-problem is solved by using dynamic programming. The economic dispatch problem is solved by particle swarm optimization. By comparing the results with conventional method the proposed methodology gives the schedule of generator with minimum production cost.
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