Prevention and Survivability for Power Distribution Resilience: A Multi-Criteria Renewables Expansion Model




Wang, Honggang
Jin, Tongdan

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Institute of Electrical and Electronics Engineers


Distributed energy resources are capable of enhancing grid resilience through island operations in contingency. This paper proposes a multi-year, multi-criteria generation expansion model to achieve distribution power resilience through renewable energy integration. In cases that distribution circuits or fuel lifeline are destroyed post natural disasters, wind- and solar-based generators form island microgrids to power the critical load. The goal is to determine the sizing, siting and maintenance of distributed energy resources such that system cost and power shortage in contingency are minimized. Moment methods and central limit theorem are used to characterize the spatial climate uncertainty, generation intermittency,and voltage variation. The research contributions are twofold. First, the expansion model achieves triple goals by meeting the annual load growth, reducing the carbon footprint, and enhancing the grid resilience manifested as prevention and survivability. Second, we present an improved direct zigzag algorithm to searchfor the Pareto solutions. Numerical examples show that the zigzag search outperforms evolutionary-based algorithms as it can identify higher-quality non-dominant solutions by exploring a wider Pareto frontier.



island microgrid, prevention and survivability, zigzag algorithm, chance constraint, power resilience, Ingram School of Engineering


Wang, H., & Jin, T. (2020). Prevention and survivability for power distribution resilience: A multi-criteria renewables expansion model. IEEE Access, 8, pp. 88422–88433.


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