MDPA algorithm based multi-objective load dispatch

ZHU Yu; SI Fengqi; LIU Feilong; ZHOU Jianxin

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MDPA algorithm based multi-objective load dispatch

更新时间：2025-09-28

- MDPA algorithm based multi-objective load dispatch
- Thermal Power Generation Vol. 43, Issue 12, Pages: 89-94(2014)
- 作者机构：
  
  1. 广东电网公司电力科学研究院
  2. 东南大学能源热转换及其过程测控教育部重点实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM621
- Published：2014
- 稿件说明：
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ZHU Yu, SI Fengqi, LIU Feilong, et al. MDPA algorithm based multi-objective load dispatch[J]. Thermal power generation, 2014, 43(12): 89-94.
DOI：

ZHU Yu, SI Fengqi, LIU Feilong, et al. MDPA algorithm based multi-objective load dispatch[J]. Thermal power generation, 2014, 43(12): 89-94. DOI：

摘要

在传统的火电厂经济负荷分配模型基础上

综合考虑全厂供电煤耗率、污染物排放量以及全厂负荷升、降时间3个目标

构建了厂级负荷优化分配的多目标模型。将差分粒子群混合算法发展为一种新型的多目标进化(MDPA)算法

即利用擂台赛法和凝聚层次聚类分析方法分别构造和修剪非支配集

同时加入精英保留策略

保留进化过程中的极值点。将该算法应用于以经济、环保、快速3个目标为多目标的厂级负荷优化分配

并与基于非支配排序的多目标优化(NSGA-Ⅱ)算法进行对比。结果表明

MDPA算法较NSGA-Ⅱ算法收敛速度更快

解集分布更均匀。

Abstract

On the basis of the conventional single-object model only considering the energy consumption

a multi-objective optimization model for load dispatch was established

concerning the energy consumption

environmental protection and load response rate.A hybrid multi-objective differential evolution(DE)and particle swarm optimization(PSO)algorithm called MDPA was proposed

which uses arena's principle to establish non-dominate set

cluster analysis to change the size of no-dominate set

elitist strategy to retain extreme points during evolution.Results in three multi-objective load dispatch problems show faster convergence rate

higher convergence precision and more even distribution of solution set compared with NSGA-Ⅱ.

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