Intelligent Decision Support System for Electric Power Restoration

Despite all the technological advancement in the field of power grids, there is still a need to enhance those grids, especially in case of extreme events as being the leading cause of continuous blackouts. The recent severe blackouts have highlighted the prominence of improving the resilience of the electric power grid. There has been a steep interesting in the last couple of years to this issue from the power industry and a number of researchers were motivated to diagnose the issue via attempting to suggest ways to improve the self-healing ability. Nevertheless, issues pertinent to validity and resiliency are still raised. This paper proposes an architecture for intelligent decision support system based on deep learning algorithms that can help operators to decide what to do against blackout. The system can offer decision support in the power restoration process. The system aim to restore power in a quick and effective manner in order to reduce blackout duration as well as the economic losses.