[1]赵文清,覃智补.智能水滴算法与SQP相混合的电力环境经济调度[J].智能系统学报,2018,13(03):346-351.[doi:10.11992/tis.201705002]
 ZHAO Wenqing,QIN Zhibu.Hybrid intelligent water drops algorithm and sequential quadratic programming for electric power economic emission dispatch[J].CAAI Transactions on Intelligent Systems,2018,13(03):346-351.[doi:10.11992/tis.201705002]
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智能水滴算法与SQP相混合的电力环境经济调度(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第13卷
期数:
2018年03期
页码:
346-351
栏目:
出版日期:
2018-05-05

文章信息/Info

Title:
Hybrid intelligent water drops algorithm and sequential quadratic programming for electric power economic emission dispatch
作者:
赵文清 覃智补
华北电力大学 控制与计算机工程学院, 河北 保定 071003
Author(s):
ZHAO Wenqing QIN Zhibu
School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China
关键词:
智能水滴算法序列二次规划电力环境经济调度阀点效应连续优化混合算法标准测试函数
Keywords:
intelligent water drops algorithmsequential quadratic programmingelectric power environmenteconomic dispatchvalve-point effectcontinuous optimizationhybrid algorithmstandard test function
分类号:
TP391.9;TPTM621.4
DOI:
10.11992/tis.201705002
摘要:
电力环境经济调度对于降低发电过程中煤耗成本和污染气体排放有着重要意义。本文给出一种智能水滴算法(intelligent water drops,IWD)和序列二次规划(sequential quadratic programming,SQP)相混合求解电力环境经济调度问题的方法(IWD-SQP)。针对SQP全局搜索弱的缺点,将智能水滴算法应用于求解连续优化问题,同时将每次迭代过程中水滴所产生的解作为序列二次规划初始解进行微调以得到更好的解。将提出的方法应用于一个10机组测试系统进行实验,与其他方法求解考虑阀点效应的电力环境经济调度问题相比,验证了IWD-SQP的可行性和有效性。
Abstract:
Economic dispatch in an electric power environment is critical to reducing the cost of coal consumption and the emission of air pollutants during power generation. We propose a hybrid methodology that combines an intelligent-water-drops (IWD) algorithm with sequential quadratic programming (SQP) to improve the economic dispatch. Because of SQP’s weak global search capability, we use IWD to seek a global solution. In addition, the solution generated by the water droplets in each iteration is then taken as the initial solution of SQP, which is also slightly adjusted to improve the solution. We test the proposed approach by using a ten-unit system. In comparison with other methods that consider the valve-point effect, the proposed IWD-SQP method is feasible and effective.

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备注/Memo

备注/Memo:
收稿日期:2017-05-03。
基金项目:中央高校基本科研业务费专项资金项目(12MS121).
作者简介:赵文清,女,1973年生,教授,博士,主要研究方向为人工智能与数据挖掘。发表学术论文50余篇,被SCI、EI检索30余篇;覃智补,男,1992年生,硕士研究生,主要研究方向为人工智能在电力系统中的应用。
通讯作者:赵文清.E-mail;jbzwq@126.com.
更新日期/Last Update: 2018-06-25