文档介绍：毕业设计(论文)
题目基于粒子群算法的电力
系统环境经济调度问题
专业自动化
班级
学生
指导教师
摘要
实现电力系统安全、可靠、优质、经济运行对国民经济发展具有很强的重要性。本文研究的电力系统经济环境调度问题就是电力系统优化的一部分,是一个需要多方面多层次考虑的多目标问题。首先,运行成本最低历来是它的主要目标。其次,必须考虑环污染的问题,减少污染排量,当然在发电机发电的过程中也会考虑到阀点效应和网络损耗等实际问题。这个多目标问题是一个有约束的、非线性的组合优化问题。粒子群算法简单、易于实现,并且已经成功运用到各类优化问题当中,所以采用了粒子群算法来解决。
采用多目标粒子群算法解决电力系统环境经济调度问题,先研究基本粒子群算法,分析它的思想并利用测试函数对其算法进行仿真。然后再此基础上将基本粒子群算法应用到多目标优化的问题上,多目标粒子群算法与单目标粒子群算法虽然有很多的不同,但也可以利用粒子位置和速度的改变更新,在熟悉多目标粒子群算法的基础上利用测试函数对该算法进行仿真,并对仿真结果进行优化。基于对多目标粒子群算法的研究利用这种方法解决多目标的电力系统环境经济调度问题。作为有污染排放量和燃料花费两个目标和有等式约束和不等式约束的两个约束的复杂问题,结合多目标粒子群算法的思想,在考虑网络损耗的基础上最终能得出合理的解集。
这种方法解决电力系统环境经济调度问题,虽然还有不足,但基本能达到对其优化的作用
关键词:电力系统环境经济调度问题,基本粒子群优化算法,多目标优化问题,多目标粒子群优化
Abstract
Achieve power system is safe, reliable and high quality, economic operation of national economic development has a strong importance. This study of the power system, economic environment scheduling problem is part of the power system, is a need to consider the various levels multi-objective question. Firstly, the lowest operating costs, it is always main objectives. Second, must consider ring, reduce pollution problem of pollution emissions, of course, in the process of generating generator will also consider valve point effects and practical problems such work loss. This problem is a multi-objective nonlinear constraints, binatorial optimization problem. Particle swarm algorithm is simple, easy to be realized, and has been essfully applied to all kinds of optimization problem, so using particle swarm optimization algorithm to solve.
Adopts multi-objective particle swarm optimization algorithm to solve environmental economic power system, the first study scheduling problem, analyzes the basic particle swarm optimization algorithm of ideology and use it to its algorithm testing function simulation. Then the basis of basic particle swarm algorithm is applied to the multi-objective optimization problem, the multi-objective particle swarm algorithm with single target particle swarm algorithm while there a