Robust Microgrid Scheduling Considering Unintentional Islanding Conditions

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Abstract
This work presents a novel microgrid scheduling model considering the stochastic unintentional islanding conditions as well as forecast errors of both renewable generation and loads. By optimizing the dispatch of distributed energy resources (DERs), utility grid, and demand, the proposed model is targeted to minimize total operating cost of the microgrid, including start-up and shut-down cost of distributed generators (DGs), operation and maintenance (O&M) cost of DGs, cost of buying/selling power from/to utility grid, degradation cost of energy storage systems (ESSs) and cost associated with load shedding. To capture the stochastic unintentional islanding conditions and conventional forecast errors of renewable generation and loads, a two-stage adaptive robust optimization is proposed to optimize the objective function in the worst case scenario of the modeled uncertainties. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The result obtained ensures robust microgrid operation in consideration of all possible realization of renewable generation, demand and unintentional islanding condition. The proposed model is validated with results of case studies on a microgrid consisting of various DGs and ESSs.
Funding Information
  • UT-Battelle, LLC with the U.S. Department of Energy (DE-AC05-00OR22725)
  • Engineering Research Center Program of the National Science Foundation and the Department of Energy through the Engineering Research Center Shared Facilities (EEC-1041877)
  • Center for Ultra-wide-area Resilient Electric Energy Transmission Network (CURENT) Industry Partnership Program

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