Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/179184
Title: Microgrids for Enhancing the Power Grid Resilience in Extreme Conditions
Authors: Xindong Liu;Mohammad Shahidehpour;Zuyi Li;Xuan Liu;Yijia Cao;Zhaohong Bie
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/179184
volume: 8
issue: 2
More Information: 589,
597
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7489002.pdf1.86 MBAdobe PDF
Title: Microgrids for Enhancing the Power Grid Resilience in Extreme Conditions
Authors: Xindong Liu;Mohammad Shahidehpour;Zuyi Li;Xuan Liu;Yijia Cao;Zhaohong Bie
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/179184
volume: 8
issue: 2
More Information: 589,
597
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7489002.pdf1.86 MBAdobe PDF
Title: Microgrids for Enhancing the Power Grid Resilience in Extreme Conditions
Authors: Xindong Liu;Mohammad Shahidehpour;Zuyi Li;Xuan Liu;Yijia Cao;Zhaohong Bie
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/179184
volume: 8
issue: 2
More Information: 589,
597
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7489002.pdf1.86 MBAdobe PDF