Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/655256
Title: Microgrid Scheduling With Uncertainty: The Quest for Resilience
Authors: Amin Gholami;Tohid Shekari;Farrokh Aminifar;Mohammad Shahidehpour
subject: power system resilience|uncertainty|stochastic programming|Microgrids
Year: 2016
Publisher: IEEE
Abstract: In recent years, natural disasters around the world have underscored the need for operative solutions that can improve the power grid resilience in response to low-probability high-impact incidents. The advent of microgrids (MGs) in modern power systems has introduced promising measures that can fulfil the power network resiliency requirements. This paper presents a two-stage stochastic programming approach to the optimal scheduling of a resilient MG. The impact of natural disasters on the optimal operation of MGs is modeled using a stochastic programming process. Other prevailing uncertainties associated with wind energy, electric vehicles, and real-time market prices are also taken into account. The proposed hourly scheme attempts to mitigate damaging impacts of electricity interruptions by effectively exploiting the MG capabilities. Incorporating AC network constraints in the proposed model offers a better solution to the security-constrained operation of MGs. The proposed model is linearized which offers robustness, simplicity, and computational efficiency in optimizing the MG operation. The effectiveness of proposed approach is illustrated using a large-scale MG test bed with a realistic set of data.
URI: http://localhost/handle/Hannan/142454
http://localhost/handle/Hannan/655256
ISSN: 1949-3053
1949-3061
volume: 7
issue: 6
Appears in Collections:2016

Files in This Item:
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Title: Microgrid Scheduling With Uncertainty: The Quest for Resilience
Authors: Amin Gholami;Tohid Shekari;Farrokh Aminifar;Mohammad Shahidehpour
subject: power system resilience|uncertainty|stochastic programming|Microgrids
Year: 2016
Publisher: IEEE
Abstract: In recent years, natural disasters around the world have underscored the need for operative solutions that can improve the power grid resilience in response to low-probability high-impact incidents. The advent of microgrids (MGs) in modern power systems has introduced promising measures that can fulfil the power network resiliency requirements. This paper presents a two-stage stochastic programming approach to the optimal scheduling of a resilient MG. The impact of natural disasters on the optimal operation of MGs is modeled using a stochastic programming process. Other prevailing uncertainties associated with wind energy, electric vehicles, and real-time market prices are also taken into account. The proposed hourly scheme attempts to mitigate damaging impacts of electricity interruptions by effectively exploiting the MG capabilities. Incorporating AC network constraints in the proposed model offers a better solution to the security-constrained operation of MGs. The proposed model is linearized which offers robustness, simplicity, and computational efficiency in optimizing the MG operation. The effectiveness of proposed approach is illustrated using a large-scale MG test bed with a realistic set of data.
URI: http://localhost/handle/Hannan/142454
http://localhost/handle/Hannan/655256
ISSN: 1949-3053
1949-3061
volume: 7
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7539274.pdf2.05 MBAdobe PDFThumbnail
Preview File
Title: Microgrid Scheduling With Uncertainty: The Quest for Resilience
Authors: Amin Gholami;Tohid Shekari;Farrokh Aminifar;Mohammad Shahidehpour
subject: power system resilience|uncertainty|stochastic programming|Microgrids
Year: 2016
Publisher: IEEE
Abstract: In recent years, natural disasters around the world have underscored the need for operative solutions that can improve the power grid resilience in response to low-probability high-impact incidents. The advent of microgrids (MGs) in modern power systems has introduced promising measures that can fulfil the power network resiliency requirements. This paper presents a two-stage stochastic programming approach to the optimal scheduling of a resilient MG. The impact of natural disasters on the optimal operation of MGs is modeled using a stochastic programming process. Other prevailing uncertainties associated with wind energy, electric vehicles, and real-time market prices are also taken into account. The proposed hourly scheme attempts to mitigate damaging impacts of electricity interruptions by effectively exploiting the MG capabilities. Incorporating AC network constraints in the proposed model offers a better solution to the security-constrained operation of MGs. The proposed model is linearized which offers robustness, simplicity, and computational efficiency in optimizing the MG operation. The effectiveness of proposed approach is illustrated using a large-scale MG test bed with a realistic set of data.
URI: http://localhost/handle/Hannan/142454
http://localhost/handle/Hannan/655256
ISSN: 1949-3053
1949-3061
volume: 7
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7539274.pdf2.05 MBAdobe PDFThumbnail
Preview File