基于混合纵横交叉算法的机组组合优化

马留洋; 孟安波; 殷豪

doi:10.12052/gdutxb.160161

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基于混合纵横交叉算法的机组组合优化

综合研究 | 更新时间：2026-05-27

- 基于混合纵横交叉算法的机组组合优化
- Unit Commitment Optimization Based on Hybrid Crisscross Optimization Algorithm
- 广东工业大学学报 2017年34卷第6期页码：68-72
- 作者机构：
  
  广东工业大学　自动化学院,广东,广州,510006
- 作者简介：
  
  马留洋(1992–)，男，硕士研究生，主要研究方向为电力系统经济调度与机组组合
- 基金信息：
  
  广东省科技计划项目(2016A010104016);广东电网公司科技项目(GDKJQQ20152066)
- DOI：10.12052/gdutxb.160161
  中图分类号： TM734
- 纸质出版：2017
- 稿件说明：
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马留洋, 孟安波, 殷豪. 基于混合纵横交叉算法的机组组合优化[J]. 广东工业大学学报, 2017, 34(6): 68-72.

Ma Liu-yang, Meng An-bo, Yin Hao. Unit Commitment Optimization Based on Hybrid Crisscross Optimization Algorithm[J]. 2017, 34(6): 68-72.
马留洋, 孟安波, 殷豪. 基于混合纵横交叉算法的机组组合优化[J]. 广东工业大学学报, 2017, 34(6): 68-72. DOI： 10.12052/gdutxb.160161.

Ma Liu-yang, Meng An-bo, Yin Hao. Unit Commitment Optimization Based on Hybrid Crisscross Optimization Algorithm[J]. 2017, 34(6): 68-72. DOI： 10.12052/gdutxb.160161.

摘要

针对机组组合问题的特点

提出一种混合纵横交叉算法(crisscross optimization

CSO)

分别用离散CSO和连续CSO优化机组的启停状态和机组的功率分配. 进化过程中

通过横向交叉在不同粒子的相同维进行交叉保证算法的全局收敛能力

纵向交叉在相同粒子的不同维进行交叉克服局部最优问题

两者通过一个竞争算子完美地结合

既加快了收敛速度

又能保证全局收敛能力. 引入启发式策略修正最小开停机时间、功率平衡等约束条件

有效地提高了求解的精度. 通过2个算例的仿真以及与其他算法的比较

验证了该算法的可行性和优越性.

Abstract

With regard to the characteristics of the unit commitment problem

a hybrid crisscross optimization algorithm (CSO) is proposed

discrete CSO and continuous CSO are used for the unit status scheduling and power economic dispatch

respectively. In the process of evolution

horizontal crossover performs crossover on the same dimension of different particles to guarantee the global convergence ability

and vertical crossover performs crossover on different dimensions of the same particle to overcome the local optimal convergence

and the perfect combination of the two crossovers by a competitive algorithm not only speeds up the convergence rate but also ensures the ability of the global constraints. The heuristic strategy is introduced to modify the constraint conditions

such as the minimum up and down time and the power balance

which can effectively improve the accuracy of the solution. The feasibility and superiority of the proposed algorithm are verified by the simulation of two examples and the comparison with other algorithms.

关键词

Keywords

references

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