Open AccessA three‐stage stochastic planning model for enhancing the resilience of distribution systems with microgrid formation strategy
Author(s) -
Ghasemi Mostafa,
Kazemi Ahad,
Mazza Andrea,
Bompard Ettore
Publication year - 2021
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12144
Subject(s) - microgrid , realisation , resilience (materials science) , computer science , scheduling (production processes) , correctness , operations research , reliability engineering , mathematical optimization , control (management) , risk analysis (engineering) , engineering , operations management , business , physics , mathematics , quantum mechanics , artificial intelligence , thermodynamics , programming language
In recent years, severe outages caused by natural disasters such as hurricanes have highlighted the importance of boosting the resilience level of distribution systems. However, due to the uncertain characteristics of natural disasters and loads, there exists a research gap in the selection of optimal planning strategies coupled with provisional microgrid (MG) formation. For this purpose, this study proposes a novel three‐stage stochastic planning model considering the planning step and emergency response step. In the first stage, the decisions on line hardening and Distributed Generation (DG) placement are made with the aim of maximising the distribution system resilience. Then, in the second stage, the line outage uncertainty is imposed via the given scenarios to form the provisional MGs based on a master‐slave control technique. In addition, the non‐anticipativity constraints are presented to guarantee that the MG formation decision is based on the line damage uncertainty. Last, with the realisation of the load demand, the cost of load shedding in each provisional MG is minimised based on a demand‐side management program. The proposed method can consider the step‐by‐step uncertainty realisation that is near to the reality in MG formation strategy. Two standard distribution systems are utilised to validate the correctness and effectiveness of the presented model.