Wasserstein distance-based distributionally robust optimal scheduling in rural microgrid considering the coordinated interaction among source-grid-load-storage

The microgrid (MG) is an effective way to alleviate the impact of the large-scale penetration of distributed generations. Due to the seasonal characteristics of rural areas, the load curve of the rural MG is different from the urban MG. Besides, the economy and stability of MG's scheduling may be impacted due to the uncertainty of the distributed generations' output. To adapt the seasonal characteristics of the rural microgrid, a Wasserstein distance-based distributionally robust optimal scheduling model of rural microgrid considering the coordinated interaction among source-grid-load-storage is proposed to minimize the operating costs of the rural microgrid in this paper, and the distributionally robust optimization method based on the Wasserstein distance is utilized to deal with the uncertainty of distributed generations' output in the proposed model, which can balance the robustness and economy of MG's scheduling when compared with the robust optimization method and stochastic optimization method. The case study shows that the proposed model can achieve better economical and robust scheduling strategies of source-grid-load-storage than the robust optimization-based model and the stochastic optimization-based model. Besides, the robustness and economy of rural MG's scheduling strategies are adjusted flexibly by the proposed model. (C) 2021 The Authors. Published by Elsevier Ltd.