Paper Info
Title
Impact of Uncertainties on Resilient Operation of Microgrids: A Data-Driven Approach.
Abstract
In this paper, the impact of uncertainties in loads, renewable generation, market price signals, and event occurrence time on the feasible islanding and survivability of microgrids is analyzed. A data-driven approach is proposed for estimating the maximum deviation level of uncertain parameters dynamically based on historical data. Similarly, fragility curves are utilized for determining the preparation time for the potential events based on the estimated event occurrence time and physical constraints of the microgrid components. In addition, a resilience-oriented demand response program is proposed for enhancing the utilization of renewables and other available resources for reducing the load shedding during the emergency period. Finally, a resilience index is proposed for quantifying the benefits of the proposed method for the resilience-oriented operation of microgrids. In normal mode, the impact of event occurrence time and uncertainty level is analyzed via an adaptive robust optimization method. In emergency mode, 10 000 Monte Carlo scenarios of all the uncertain parameters are generated, and their impact on the operation cost, amount of load shed, and the range of the proposed resilience index are analyzed for each case.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2891786
IEEE ACCESS
Keywords
Field
DocType
Adaptive robust optimization,demand response,fragility curves,microgrid resilience,uncertainty modeling
Monte Carlo method,Survivability,Data-driven,Computer science,Robust optimization,Demand response,Fragility,Islanding,Reliability engineering,Microgrid,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Akhtar Hussain1748.39
Anastasios Oulis Rousis200.68
Ioannis Konstantelos331.11
Goran Strbac47519.95
Jin-hong Jeon56611.82
Hak-Man Kim611124.92