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CSEE Journal of Power and Energy Systems 2023, 9(3): 1214-1226 https://doi.org/10.17775/CSEEJPES.2022.00740
Open Access | Issue | Published: 03 March 2023

Reliability Assessment for Integrated Power-gas Systems Considering Renewable Energy Uncertainty and Cascading Effects

Show Author's Information Yucui Wang1,  Yongbiao Yang2( ),  Qingshan Xu2
School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China
School of Electrical Engineering, Southeast University, Nanjing 210096, China and Nanjing Center for Applied Mathematics, Nanjing 210096, China
Keywords:
reliability, Cascading effects, integrated power-gas systems, multi-state model, renewable energy uncertainty
Cite this article:
Wang Y, Yang Y, Xu Q. Reliability Assessment for Integrated Power-gas Systems Considering Renewable Energy Uncertainty and Cascading Effects. CSEE Journal of Power and Energy Systems, 2023, 9(3): 1214-1226. https://doi.org/10.17775/CSEEJPES.2022.00740
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Abstract Full text About this article

Integrated power-gas systems (IPGSs) make the power system and natural gas system (NGS) as a whole, and strengthen interdependence between the two systems. Due to bi-directional energy conversion in IPGS, a disturbance may turn into a catastrophic outage. Meanwhile, increasing proportion of renewable energy brings challenges to reliability of IPGS. Moreover, partial failure or degradation of system performance leads IPGS operate at multiple performance levels. Therefore, this paper proposes a reliability assessment model of IPGSs which represents multiple performance of components and considers cascading effects, as well as renewable energy uncertainty. First, a framework of IPGS reliability assessment is proposed: multi-state models for main elements in the IPGS are represented. Especially a gas-power-generation calculation operator and a power-to-gas calculation operator are utilized to bi-directionally convert a multi-state model between NGS and power systems. Furthermore, nodal reliability indices for IPGS are given to display impacts of cascading effects and renewable energy uncertainty on reliabilities of IPGSs. Numerical results on IPGS test system demonstrate the proposed methods.


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About this article

Reliability Assessment for Integrated Power-gas Systems Considering Renewable Energy Uncertainty and Cascading Effects

Show Author's information Yucui Wang1, Yongbiao Yang2( ), Qingshan Xu2
School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China
School of Electrical Engineering, Southeast University, Nanjing 210096, China and Nanjing Center for Applied Mathematics, Nanjing 210096, China

Abstract

Integrated power-gas systems (IPGSs) make the power system and natural gas system (NGS) as a whole, and strengthen interdependence between the two systems. Due to bi-directional energy conversion in IPGS, a disturbance may turn into a catastrophic outage. Meanwhile, increasing proportion of renewable energy brings challenges to reliability of IPGS. Moreover, partial failure or degradation of system performance leads IPGS operate at multiple performance levels. Therefore, this paper proposes a reliability assessment model of IPGSs which represents multiple performance of components and considers cascading effects, as well as renewable energy uncertainty. First, a framework of IPGS reliability assessment is proposed: multi-state models for main elements in the IPGS are represented. Especially a gas-power-generation calculation operator and a power-to-gas calculation operator are utilized to bi-directionally convert a multi-state model between NGS and power systems. Furthermore, nodal reliability indices for IPGS are given to display impacts of cascading effects and renewable energy uncertainty on reliabilities of IPGSs. Numerical results on IPGS test system demonstrate the proposed methods.

Keywords: reliability, Cascading effects, integrated power-gas systems, multi-state model, renewable energy uncertainty

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Received: 06 February 2022
Revised: 08 April 2022
Accepted: 23 June 2022
Published: 03 March 2023
Issue date: May 2023

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This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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