基于PSO和EP的机组承诺问题混合求解方法

R. R. Singh, C. Rajan
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引用次数: 7

摘要

机组承诺问题(Unit Commitment Problem, UCP)是电力系统发电机组在需求和备用需求约束下,为实现最小运行成本而进行调度运行的非线性混合整数优化问题。UC问题的任务是确定发电机组在规划期内每小时间隔的开/关状态,以便在承诺机组之间最优地传递负荷和储备。随着需求的不断变化,需要一个更有效的最优解决方案来解决UCP问题的重要性也在增加。在此,我们提出了一种混合方法,该方法解决了受必要约束的机组承诺问题,并给出了机组的最优承诺。通过粒子群算法可以确定可能的需求组合及其对应的最优发电计划。作为一种全局优化技术,进化规划(EP)是解决机组承诺问题的一种方法,它将每个机组的运行计划与启动/停机时间进行编码。当一个时间段内的需求作为输入输入到网络时,它成功地给出了每个单元的承诺计划,该计划满足所有时间段的需求,并导致总成本最小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid approach based on PSO and EP for proficient solving of Unit Commitment Problem
Unit Commitment Problem (UCP) is a nonlinear mixed integer optimization problem used in the scheduling operation of power system generating units subjected to demand and reserve requirement constraints for achieving minimum operating cost. The task of the UC problem is to determine the on/off state of the generating units at every hour interval of the planning period for optimally transmitting the load and reserve among the committed units. The importance for the necessity of a more effective optimal solution to the UCP problem is increasing with the regularly varying demand. Hereby, we propose a hybrid approach which solves the unit commitment problem subjected to necessary constraints and gives the optimal commitment of the units. The possible combination of demand and their corresponding optimal generation schedule can be determined by the PSO algorithm. Being a global optimization technique, Evolutionary Programming (EP) for solving Unit Commitment Problem, operates on a method, which encodes each unit's operating schedule with respect to up/down time. When the demand over a time horizon is given as input to the network it successfully gives the schedule of each unit's commitment that satisfies the demands of all the periods and results in minimum total cost.
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