Browsing by Author "Arab, Ali"
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Item Asset Analytics of Smart Grid Infrastructure for Resiliency Enhancement(2015-05) Arab, Ali; Khator, Suresh K.; Han, Zhu; Lim, Gino J.; Tekin, Eylem; Khodaei, AminFirst, a post-hurricane restoration model for power grid which considers the economics of disaster is introduced. The physical and economic constraints of the system, including unit commitment and restoration constraints, are incorporated in the proposed model. The aim is to restore the hurricane-related damages to electric power system infrastructure in an economic and customer-centered manner, without violating the physics of the system, in order to mitigate the aftermath of natural disasters. Second, a proactive resource allocation model for repair and restoration of potential damages to the power system infrastructure located on the path of an upcoming hurricane is proposed. The objective is to develop an efficient framework for system operators to restore potential damages to power system components in a cost-effective manner. The problem is modeled as a two-stage stochastic integer program with recourse. This model can improve proactive preparedness of the decision makers to cope with emergencies, especially those of nature origins, in order to minimize the restoration cost, and enhance the resilience of the power system. Third, a model is proposed to incorporate the impact of potential damage due to hurricane in the maintenance scheduling of the power infrastructure components located in hurricane prone areas. The power infrastructure deterioration process, as well as two competing and independent failure modes, i.e., failure due to loss of reliability and failure due to hurricane damages are integrated into the model. Moreover, the interrelationship between the component, the grid, and the associated downtime cost dynamics are analyzed. The problem is modeled as a Markov decision process with perfect state information. Fourth, the impact of El Nino/La Nina phenomenon which has shown to induce seasonal effects on hurricane arrivals in long-term climatological horizon is considered in asset management strategies of the electric power systems. An integrated infrastructure hardening and condition-based maintenance scheduling model for critical components of the power systems is developed. The partially observable Markov decision processes are used to formulate the problem. The survival function against hurricane is derived as a dynamic stress-strength model, and is incorporated in the proposed framework.Item Electric Power Grid Restoration Considering Disaster Economics(IEEE Access, 2/1/2016) Arab, Ali; Khodaei, Amin; Khator, Suresh K.; Han, ZhuThis paper presents a cost-effective system-level restoration scheme to improve power grids resilience by efficient response to the damages due to natural or manmade disasters. A post-disaster decision making model is developed to find the optimal repair schedule, unit commitment solution, and system configuration in restoration of the damaged power grid. The physical constraints of the power grid, associated with the unit commitment and restoration, are considered in the proposed model. The value of lost load is used as a viable measure to represent the criticality of each load in the power grid. The model is formulated as a mixed-integer program and, then, is decomposed into an integer master problem and a dual linear subproblem to be solved using Benders decomposition algorithm. Different scenarios are developed to analyze the proposed model on the standard IEEE 118-bus test system. This paper provides a prototype and a proof of concept for utility companies to consider economics of disaster and include unit commitment model into the post-disaster restoration process.Item Proactive Recovery of Electric Power Assets for Resiliency Enhancement(IEEE Access, 2/16/2015) Arab, Ali; Khodaei, Amin; Han, Zhu; Khator, Suresh K.This paper presents a significant change in current electric power grid response and recovery schemes by developing a framework for proactive recovery of electric power assets with the primary objective of resiliency enhancement. Within the proposed framework, which can potentially present the next generation decision-making tool for proactive recovery, several coordinated models will be developed including: 1) the outage models to indicate the impact of hurricanes on power system components; 2) a stochastic pre-hurricane crew mobilization model for managing resources before the event; and 3) a deterministic post-hurricane recovery model for managing resources after the event. Proposed models will be extended to ensure applicability to a variety of electric power grids with different technologies and regulatory issues. The theoretical and practical implications of the developed models will push the research frontier of proactive response and recovery schemes in electric power grids, while its flexibility will support application to a variety of infrastructures, in response to a wide range of extreme weather events and natural disasters.