Abstract
Mobile emergency generators(MEGs) can accelerate disaster recovery and enhance the resiliency of the distribution system (SD). However, the resilience-oriented planning of MEGs has not been fully investigated. This paper proposes a method to achieve the resilience-oriented optimal plan of different kinds of MEGs via a two-stage stochastic optimization model. In the first stage, DS operators invest in various types of MEGs and allocate them in the second stage according to the line damage situation. A distributionally robust model based on confidence sets is used to reduce the number of scenario samples. The proposed model is transformed into a second-order cone program that commercial solvers can solve after convex relaxation. The case studies of a 33-bus test system demonstrate the effectiveness of the proposed method for scenario reduction and optimization of MEGs investment and allocation strategy.
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