Research in Reservoir Optimal Operation Based on Modified Ant Colony Optimization

被引：0

作者：

Wang Zhengchu ^{[1
]}

Zhou Muxun ^{[2
]}

Li Jun ^{[1
]}

Fan Jian ^{[1
]}

Zan Baishao ^{[1
]}

机构：

[1] Taizhou Coll, Sch Mech Engn, Taizhou 318000, Peoples R China

[2] Taizhou Coll, Sch Phys & Electron Engn, Taizhou 317000, Peoples R China

来源：

2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2010年

关键词：

optimal operation; ant colony optimization (ACO); reservoir; chaos optimization algorithm; entropy;

D O I：

10.1109/WCICA.2010.5554809

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the problem of single reservoir operation optimization is studied. Firstly, the background and mathematic model of single reservoir operation optimization are given. Then modified ant colony optimization (MACO) is presented. According to the ergodicity, stochastic property and regularity of chaos, search and optimization are carried out using the chaos variables. Population entropy is introduced to judge whether the algorithm falls in local peak or not, and catastrophe operation is also adopted. Then detailed solving steps of reservoir operation optimization based on MACO are given. Lastly, an instance is given. By calculations of the instance and comparison with other algorithms, it proves the algorithm has much stronger ability of local search and better search efficiency. It also can find better solution and certifies that this method is feasible and valid.

引用

页码：5337 / 5342

页数：6