Multi-Agent system-based decentralized state estimation method for active distribution networks

Abstract

This paper deals with the state estimation problem in Active Distribution Networks. With energy deregulation and the emergence of renewable energy sources, more distributed generation is integrated into distribution networks which increases their complexity. To be able to manage, control and take appropriate decisions on power networks, it is necessary to have accurate real-time measurements to perform state estimation. However, the use of classical methods for state estimation, on complex distribution networks, reveal instantly their limits. To handle these systems complexity, a new decentralized multi-agent-based approach is proposed. This allows us to split systems into smaller parts whose estimation is easier and faster. Finally, Artificial Bee Colony algorithm is adopted for state estimation. Our approach is tested on IEEE 6-bus, 14-bus and 30-bus. Results show a dramatic decrease in the computational burden, thus a faster estimation on large systems. This demonstrates the effectiveness of the proposed strategy.