Microgrids for Enhancing the Power Grid Resilience in Extreme Conditions

• Published in: IEEE transactions on smart grid Vol. 8; no. 2; pp. 589 - 597
• Main Authors: Xindong Liu, Shahidehpour, Mohammad, Zuyi Li, Xuan Liu, Yijia Cao, Zhaohong Bie
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Distributed generation; Electric power grids; Electricity distribution; extreme events; Indexes; Markov chains; Markov processes; Microgrids; Monte Carlo simulation; Power system operation; Power system reliability; Resilience
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2016.2579999

This paper presents a framework for analyzing the resilience of an electric power grid with integrated microgrids in extreme conditions. The objective of this paper is to demonstrate that controllable and islandable microgrids can help improve the resiliency of power grids in extreme conditions. Four resilience indices are introduced to measure the impact of extreme events. Index K measures the expected number of lines on outage due to extreme events. Index loss of load probability measures the probability of load not being fully supplied. Index expected demand not supplied measures the expected demand that cannot be supplied. Index G measures the difficulty level of grid recovery. The mechanism of extreme events affecting power grid operation is analyzed based on the proposed mesh grid approach. The relationship among transmission grid, distribution grid, and microgrid in extreme conditions is discussed. The Markov chain is utilized to represent the state transition of a power grid with integrated microgrids in extreme conditions. The Monte Carlo method is employed to calculate the resilience indices. The proposed power grid resilience analysis framework is demonstrated using the IEEE 30-bus and 118-bus systems assuming all loads are within microgrids.