基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制

吴伟丽

您当前的位置：

首页 >

文章列表页 >

基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制

工程技术 | 更新时间：2026-01-21

- 基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制
- 基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制
- 新疆大学学报（自然科学版中英文） 2013年30卷第2期页码：243-247
- 作者机构：
  
  1. 伊犁师范学院电子与信息工程学院
  2. 华北电力大学电子与电气工程学院
- 作者简介：
- 基金信息：
  
  新疆维吾尔自治区高校科研青年培育基金(XJEDU2012S39)的资助
- DOI：
  中图分类号： TM714.3
- 纸质出版：2013
- 稿件说明：
移动端阅览
[1]吴伟丽.基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制[J].新疆大学学报(自然科学版),2013,30(02):243-247.

吴伟丽. 基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制[J]. Journal of Xinjiang University (Natural Science Edition in Chinese and English), 2013, 30(2): 243-247.
[1]吴伟丽.基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制[J].新疆大学学报(自然科学版),2013,30(02):243-247. DOI：

吴伟丽. 基于WNSGA-Ⅱ计及磁暴扰动无功补偿优化控制[J]. Journal of Xinjiang University (Natural Science Edition in Chinese and English), 2013, 30(2): 243-247. DOI：

摘要

为了补偿强磁暴导致的电力系统变压器集群无功损耗增高

提出了加权带精英策略非支配排序的遗传算法(WNSGA-Ⅱ).以电压失稳风险最小为目标进行的无功补偿优化

使电网无功潮流分布达到最优

缓解或消除强磁暴对复杂电网的不利影响.采用IEEE6节点算例

结果与人工鱼群算法对比

验证了WNSGA-Ⅱ的有效性.

Abstract

In order to compensate the increased reactive power loss transformer cluster in power system due to strong magnetic storms

this paper proposes weighted elitist non-dominated sorting genetic algorithm(WNSGA-Ⅱ) aiming to minimize voltage instability risk and optimize reactive power flow distribution to eliminate the adverse impact of strong magnetic storms on the complex grid.We tested the algorithm on IEEE6 nodes system and validate its good convergence

uniform distribution of the target spaceand reduced computational complexity.

关键词

Keywords

references

Dong X,Liu Y,Kappenman J G.Comparative Analysis of Exciting Current Harmonics and Reactive Power Consumptionfrom GIC Saturated Transformers[C].Columbus:Proc IEEE 2001 Winter Meeting,2001.

Walling R A,Khan A H.Characteristics of transformer exciting current during geomagnetic disturbances[J].IEEE Trans onPower Delivery,1991,6(4):1707-1714.

Girgis R,Vedante K,Gramm K.Effects of geomagnetically induced currents on power transformers and power systems[C].Paris:CIGRE 2012 Session,2012.

Chen Y L,Liu C C.Interactive fuzzy satisfying method for optimal multi-objective var planning in power systems[J].IEEProceedings-2C,1994,141(6):554-560.

Chattopadhyayd D,Chakrabartib B B.Voltage stability constrained VAR planning:model simplification using statisticalapproximation[J].International Journal of Electrical Power&Energy Systems,2001,23(5):349-358.

Venkatesh B,Sadasivam G,Khan M A.A new optimal reactive power scheduling method for loss minimization and voltage sta-bility margin maximization using successive multi-objective fuzzy LP technique[J].IEEE Trans on Power Systems,2000,15(1):844-851.

戴剑锋,周双喜,鲁宗相,等.基于风险的电力系统无功优化问题研究[J].中国电机工程学报,2007,27(22):38-43.

Eckart Zitzler,Marco Laumanns,Lothar Thiele.improving the strength pareto evolutionary algorithm for multiobjectiveoptimization[C].EUROGEN Evolutionary Method for Design:Optimization and Control for Industrial Problem,2001.

康凯龙.复杂电网GIC治理措施及方案优化研究[D].北京:华北电力大学,2010.

Deb K,Pratap A,Agarwal S,et al.A fast and elitist multi-objective genetic algorithm:NSGA2-Ⅱ[J].IEEE Transactions onEvolutionary Computation,2002,6(2):182-197.

Kappenman J G.Geomagnetic storms and their impacts on the U S power grid[R].Jan:Metatech report for Oak RidgeNational Laboratory,2010.

唐剑东,熊信银,吴耀武,等.基于人工鱼群算法的电力系统无功优化[J].继电器,2004,32(19):9-33.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据