Capacity-based service restoration using Multi-Agent technology and ensemble learning

Reliable and efficient distributed algorithms for power restoration are essential for self-healing electrical smart grids. Therefore, this paper presents a Multi-Agent System (MAS) for automatic restoration in power distribution networks. Moreover, as electrical demand fluctuates on the hourly and daily basis, an ensemble learning algorithm has been adopted for short-term forecasting of electrical energy demand. The prediction methodology is incorporated into the restoration algorithm in order to obtain a capacity-based restoration solution. Experiments carried out in two electrical networks demonstrate the importance and accuracy of the demand prediction algorithm and the feasibility of the MAS for system reconfiguration in decentralized power utilities.