Title :
Multi-agent systems applied to topological reconfiguration of smart power distribution systems
Author :
de Oliveira Saraiva, Filipe ; Nobuhiro Asada, Eduardo
Author_Institution :
Sao Carlos Sch. of Eng., Dept. of Electr. Eng. & Comput., Electr. Energy Syst. Anal. Group, Univ. of Sao Paulo, Sao Carlos, Brazil
Abstract :
One of the various features expected for a smart power distribution system - a smart grid in the power distribution level - is the possibility of the fully automated operation for certain control actions. Although this is very expected, it requires various logic, sensor and actuator technologies in a system which, historically, has a low level of automation. One of the most analyzed problems for the distribution system is the topology reconfiguration. The reconfiguration has been applied to various objectives: minimization of power losses, voltage regulation, load balancing, to name a few. The solution method in most cases is centralized and its application is not in real-time. From the new perspectives of advanced distribution systems, fast and adaptive response of the control actions are required, specially in the presence of alternative generation sources and electrical vehicles. In this context, the multi-agent system, which embeds the necessary control actions and decision making is proposed for the topology reconfiguration aiming the loss reduction. The concept of multi-agent system for distribution system is proposed and two case studies with 11-Bus and 16-Bus system are presented.
Keywords :
decision making; multi-agent systems; power distribution control; smart power grids; 11-Bus system; 16-Bus system; alternative generation sources; control action adaptive response; decision making; electrical vehicles; load balancing; multiagent systems; power loss minimization; power loss reduction; smart grid; smart power distribution systems; topology reconfiguration; voltage regulation; Decision making; Minimization; Multi-agent systems; Power distribution; Smart grids; Substations; Topology;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889791