Multiple microgrid (MMG) operation concept of community microgrid (MG) provides enhanced resiliency and reliability through self-healing, enabling a high penetration of distributed generations (DGs), power interchange between MGs and realtime communication. In this study, the methodology of optimal design of low-voltage greenfield distribution grids based on multiple MGs in the presence of uncertainties is presented. The electrical and geographical borders of MGs community are determined using some important criteria such as power balance and spatial distribution of load. Within MGs, both of dispatchable and non-dispatchable DGs are considered. The external grid is assumed as a backup for each MG in abnormal conditions. The proposed method determines the optimal borders of MGs, optimal size and site of DGs for each autonomous MG simultaneously. The imperialist competitive algorithm is used to optimise the total cost of optimal MG clustering problem. The method is implemented to a vacant area with residential and commercial customers. The MGs optimal service area, DGs location, size and type within each MG and LV feeder's route are indicated and compared both for deterministic and probabilistic planning cases.

Nowadays, the deployment of micro-grids (MGs) is one of the important trends in modern distribution network planning. Implementing this strategy aims to improve the ability of the distribution network to withstand extreme weather conditions and supplying critical loads. While the literature has focused chiefly on operating distribution systems and partitioning them into MGs, in this work, the idea of planning a new low voltage (LV) radial distribution system based on multi MGs for a greenfield is proposed. The main contribution is providing a framework to plan a resilient LV distribution system step by step for a new town without any operating grid. In the planning process, some MGs are formed and their service area and technical specifications like the number of MGs and their sizes are determined by a multi-objective optimization algorithm considering hardening and resiliency issues. The planning is done in a way that all predefined critical loads will be supplied. To consider the effects of extreme weather conditions, failure rates of poles and conductors due to thunderstorms are considered as a function of wind speed, and their appropriate models are used. The provided method is implemented in a test case with three major scenarios. Accordingly, planning in normal conditions considering hardening options and resilient network planning cases are evaluated. Simulation results and resiliency metrics are compared in detail.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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