An Approach to Dynamic Resource Allocation for Electric Power Disaster Response Management Open Access
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Electricity has become an invaluable commodity for the rest of humanity such that nations irrespective of their classification in the world economy will find it difficult to function without it’s reliable supply. For nations such as the United States and the rest of the developed world, sustainable electricity supply is no longer optional. It has become a race for survival and maintenance of the very fabrics of those societies that made them who or what they are. So, whenever there is a disruption of electricity supply due to major natural disasters, the electric utility industry in the United States marshal thousands of first responders. These first responders always answer to the call of duty to face the challenge of restoring this valuable service to affected communities within the shortest possible time. In addition to the human element, electric grid restoration methods after disasters have depended mainly on the ability of intelligent electronic devices (IEDs) to communicate vital grid information with each other for system status. At one end are field devices and at the other end are human operators through outage management systems (OMS) with considerable command and control capabilities using Supervisory Control and Data Acquisition (SCADA) processes. Traditional use of centralized SCADA for system restoration during natural disasters takes too long and presents serious constrains on field workforce especially those on mutual assistance. In this study, we present a hybrid multi agent system (MAS) form of electric grid disaster response management that decentralizes the SCADA functions. The proposed system forms a Mobile Coordination and Restoration Center (MCRC) model that allows the different restoration agents the autonomy to execute restoration functions per outage demand after a disaster. The choice of agent location is modelled on the concept of Facility Location and Relocation Problem – under Uncertainty (FLRP-U) to identify optimum grid nodes that minimize distance travel and response time for field restoration crews. The model considers a dynamic approach that identifies agent locations based on outage demand changes and minimizes the total weighted distance for first responders. Using systems engineering (SE) concepts, an encompassing viewpoint is presented. The resulting architecture will examine the different agents and subsystems to help establish a technical framework that is logistical for future electric utility disaster response managers. This could be adopted by disaster managers in different settings to achieve improved restoration performance.