A Multi-Objective Optimization Scheme for Resilient, Cost-Effective Planning of Microgrids

Natural disasters and cascading events have historically caused severe disruptions of the electric power system. For instance, in 2012, hurricane Sandy left over 8 million people in darkness and caused total damage costing 65 billion. Under emergency conditions, microgrids can help the electric powe...

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Bibliographic Details
Published in:IEEE access Vol. 8; pp. 206325 - 206341
Main Authors: Borghei, Moein, Ghassemi, Mona
Format: Journal Article
Language:English
Published: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accuracy
Darkness
Data centers
Disaster management
Distributed generation
Distribution network
Electric power
Electric power systems
Electrical loads
Electronic equipment tests
Energy sources
Energy storage
Hospitals
Hurricanes
Integer programming
Linear programming
Load modeling
Microgrids
Mixed integer
multi-objective mixed-integer linear programming (MO-MILP)
Multiple objective analysis
Natural disasters
network reconfiguration
Nodes
Optimization
Planning
Pumping stations
Reliability engineering
Resilience
resiliency
Robustness (mathematics)
Search algorithms
Storage systems
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:Natural disasters and cascading events have historically caused severe disruptions of the electric power system. For instance, in 2012, hurricane Sandy left over 8 million people in darkness and caused total damage costing 65 billion. Under emergency conditions, microgrids can help the electric power system recover critical loads, such as hospitals, data centers, and water pumping stations. While the literature has mostly focused on the utilization of existing microgrids, the idea of planning for future microgrids in combination with switching operations to make the grid more resilient against devastating events is investigated in this study. This work aims to simultaneously maximize the resiliency of distribution networks - in terms of service to the critical loads - and minimize the dispatchable generation capacity of microgrids. The considered microgrid model entails dispatchable power generators, renewable energy resources, and electrical energy storage systems (ESS) to serve consumers. Considering the topological and operational limitations, the robust optimization scheme optimizes the objectives by the effective selection of the node for microgrid connection and the minimum change in its generation capacity. While the problem is modeled as a multi-objective, mixed-integer linear programming (MO-MILP) problem, the results show more than 99% accuracy compared to the exact results of an exhaustive search algorithm. Numerical tests are performed on the IEEE 37-node test feeder and the IEEE 123-node test feeder to assess the proposed method's performance. Given the accuracy, computation time efficacy, and the generic formulation of the problem, the optimization scheme can be easily applied to any real network.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3038133