An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints

Malik Nadeem; Zafar Salman; Haroon Saaqib

doi:10.1631/FITEE.1400189

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An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints

Electrical Engineering | Updated：2022-06-06

- An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints
- 改进的混沌混合差分进化方法用于有现实限制的短期水-火电系统调度问题
- Frontiers of Information Technology & Electronic Engineering Vol. 16, Issue 5, Pages: 404-417(2015)
- Affiliations：
  
  Electrical Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan
- Author bio：
  
  †E-mail:tahir.nadeem@uettaxila.edu.pksalman.zafar@ucp.edu.pk
  ‡Corresponding Author
- Funds：
- DOI：10.1631/FITEE.1400189
  CLC：
- Received：18 May 2014，
  
  Revised：2015-03-04，
  
  Accepted：22 October 2014，
  
  Published：2015-03
- Accepted：
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Malik Nadeem, Zafar Salman, Haroon Saaqib. An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(5): 404-417.
DOI：

Malik Nadeem, Zafar Salman, Haroon Saaqib. An improved chaotic hybrid differential evolution for the short-term hydrothermal scheduling problem considering practical constraints[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(5): 404-417. DOI： 10.1631/FITEE.1400189.

摘要

目的

短期水-火电系统调度（STHTS）是含有一系列水、火电操作限制的非线性复杂最优化问题。此前，该问题已由许多常规方法解决。由于该问题代价曲线具有非线性和非凸性特点，人工智能方法也开始被应用于STHTS。在考虑现实限制条件的情况下，本文提出一种改进的混沌混合差分计划算法以获取STHTS的最优解。

创新点

针对差分进化存在控制参数为常数且获取时间较耗时和早熟收敛的问题，着重处理自调整参数集，通过防止早熟收敛和处理复杂限制提升差分进化的性能。

方法

本文方法流程（图1）关键点为：应用混沌理论获得差分进化中的自调整控制参数集；将混沌混合局部搜索机制应用于差分进化以有效防止其陷入早熟收敛；最后，应用不含惩罚因子集的启发式约束处理方解决水-火电的复杂限制。

结论

本文方法的优势和有效性在以往文献提出的两个虚拟水-火电测试系统上进行了评估（Lakshminarasimman and Subramanian (2008)）。此外，传输线损耗、水电站禁止排放区、火电站斜率限制等因素也被纳入仿真环境。仿真结果表明，与最近提出的其他进化方法相比，本文方法在降低水-火电系统成本和减少计算时间方面有竞争力。

Abstract

Short-term hydrothermal scheduling (STHTS) is a non-linear and complex optimization problem with a set of operational hydraulic and thermal constraints. Earlier

this problem has been addressed by several classical techniques; however

due to limitations such as non-linearity and non-convexity in cost curves

artificial intelligence tools based techniques are being used to solve the STHTS problem. In this paper an improved chaotic hybrid differential evolution (ICHDE) algorithm is proposed to find an optimal solution to this problem taking into account practical constraints. A self-adjusted parameter setting is obtained in differential evolution (DE) with the application of chaos theory

and a chaotic hybridized local search mechanism is embedded in DE to effectively prevent it from premature convergence. Furthermore

heuristic constraint handling techniques without any penalty factor setting are adopted to handle the complex hydraulic and thermal constraints. The superiority and effectiveness of the developed methodology are evaluated by its application in two illustrated hydrothermal test systems taken from the literature. The transmission line losses

prohibited discharge zones of hydel plants

and ramp rate limits of thermal plants are also taken into account. The simulation results reveal that the proposed technique is competent to produce an encouraging solution as compared with other recently established evolutionary approaches.

关键词

Keywords

references

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