A Mobile Agents Based Multi-Objective Optimization Resolution for Power Quality Problem Location

Author

Wang, Jingchun ; Luo, Jun

Author_Institution

Wanning Grid Co., Wanning, China

fYear

2011

fDate

25-28 March 2011

Firstpage

1

Lastpage

4

Abstract

Power Quality Problem (PQP) includes several kinds of problems such as harmonics and voltage sag. Locating PQP online can help take countermeasures, and it is very important. With help of mobile agents, PQP can be located with dynamically geographically changed agents. The Power Quality Management System (PQMS) is built on agents, and data transmission is implemented using Person to Person (P2P) and Foundations of Intelligent Physical Agents (FIPA). As PQP location is a Multi-Objective Problem (MOP) system, a Feedback Balanced Genetic Algorithm (FBGA) is used to help decide the location of PQP. The algorithm for actual PQP modeling is not discussed, and FBGA is an important algorithm for data collection and ultimate analysis. In FBGA, feedback messages are used to adjust optimization rules, and balanced genetic algorithm is used to achieve the Patero solution for MOP. Convergence of the algorithm is analyzed. Implementation of the algorithm proves feasibility of the algorithm.

Keywords

genetic algorithms; mobile agents; power supply quality; power system analysis computing; power system management; PQP; Patero solution; feedback balanced genetic algorithm; foundations of intelligent physical agents; mobile agents; multi-objective optimization resolution; person to person; power quality management system; power quality problem location; voltage sag; Algorithm design and analysis; Data communication; Encoding; Genetic algorithms; Mobile communication; Monitoring; Power quality;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific

Conference_Location

Wuhan

ISSN

2157-4839

Print_ISBN

978-1-4244-6253-7

Type

conf

DOI

10.1109/APPEEC.2011.5749140

Filename

5749140