Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/24592
Title: A Stochastic-Robust Approach for Resilient Microgrid Investment Planning Under Static and Transient Islanding Security Constraints
Authors: Nakiganda, Agnes 
Dehghan, Shahab 
Markovic, Uros 
Hug, Gabriela 
Aristidou, Petros 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: unscheduled islanding;resilience;microgrids;Investment planning;low-inertia;frequency constraints
Issue Date: 2-Jan-2022
Source: IEEE Transactions on Smart Grid, 2022
Journal: IEEE Transactions on Smart Grid 
Abstract: When planning the investment in Microgrids (MGs), usually static security constraints are included to ensure their resilience and ability to operate in islanded mode. However, unscheduled islanding events may trigger cascading disconnections of Distributed Energy Resources (DERs) inside the MG due to the transient response, leading to a partial or full loss of load. In this paper, a min-max-min, hybrid, stochastic-robust investment planning model is proposed to obtain a resilient MG considering both High-Impact-Low-Frequency (HILF) and Low-Impact-HighFrequency (LIHF) uncertainties. The HILF uncertainty pertains to the unscheduled islanding of the MG after a disastrous event, and the LIHF uncertainty relates to correlated loads and DER generation, characterized by a set of scenarios. The MG resilience under both types of uncertainty is ensured by incorporating static and transient islanding constraints into the proposed investment model. The inclusion of transient response constraints leads to a min-maxmin problem with a non-linear dynamic frequency response model that cannot be solved directly by available optimization tools. Thus, in this paper, a three-stage solution approach is proposed to find the optimal investment plan. The performance of the proposed algorithm is tested on the CIGRE 18-node distribution network
URI: https://hdl.handle.net/20.500.14279/24592
ISSN: 19493061
DOI: 10.1109/TSG.2022.3146193
Rights: © IEEE
Type: Article
Affiliation : Cyprus University of Technology 
Imperial College London 
Leeds University 
ETH Zurich 
Appears in Collections:Άρθρα/Articles

Files in This Item:
File Description SizeFormat
2022JNakiganda.pdf3.65 MBAdobe PDFView/Open
CORE Recommender
Show full item record

SCOPUSTM   
Citations

9
checked on Nov 6, 2023

WEB OF SCIENCETM
Citations

7
Last Week
0
Last month
0
checked on Oct 9, 2023

Page view(s)

228
Last Week
2
Last month
8
checked on Jun 14, 2024

Download(s)

100
checked on Jun 14, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.