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

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.