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CSEE Journal of Power and Energy Systems 2023, 9(6): 2236-2250 https://doi.org/10.17775/CSEEJPES.2021.06630
Regular Paper | Open Access | Issue | Published: 18 August 2022

Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation

Show Author's Information Minglei Bao1,  Xiaocong Sun1,  Yi Ding1,  Chengjin Ye1( ),  Changzheng Shao2,  Sheng Wang3,  Yonghua Song3
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
State Key Laboratory of Power Transmission Equipment and System Security at Chongqing University, Chongqing 400044, China
State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau 999078, China
Keywords:
reliability, Cross-sectorial failure propagation, fuzzy model, integrated electricity-gas systems, long-term reserve planning
Cite this article:
Bao M, Sun X, Ding Y, et al. Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation. CSEE Journal of Power and Energy Systems, 2023, 9(6): 2236-2250. https://doi.org/10.17775/CSEEJPES.2021.06630
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Abstract Full text About this article

With the increasing interactions between natural gas systems (NGS) and power systems, component failures in one system may propagate to the other one, threatening reliable operation of the whole system. Due to neglect of such cross-sectorial failure propagation in integrated electricity-gas systems (IEGSs), traditional economy-oriented reserve expansion models may lead to unreasonable planning results. In order to address this, an innovative reserve expansion model is proposed to determine the allocation of energy production components through the harmonization between costs and reliability. First, novel multifactor-influenced reliability indices are defined considering synthetic effects of multiple uncertainties, including failure propagation, load uncertainties and generation failures. In reliability index formulation, contribution of failure propagation on system reliability is analytically expressed. To avoid high computational complexity, the fuzzy set theory is combined with conventional methods, e.g., Monte-Carlo simulation technique to reduce numerous contingency states. Sampled contingency states are aggregated into several clusters represented by a fuzzy number. To effectively solve the planning model, a decomposition approach is introduced and applied to decompose the original problem into a master problem and two correlated reliability sub-problems. Numerical studies show the proposed model can plan reasonable reserves to guarantee reliability levels of IEGSs considering failure propagation.


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About this article

Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation

Show Author's information Minglei Bao1, Xiaocong Sun1, Yi Ding1, Chengjin Ye1( ), Changzheng Shao2, Sheng Wang3, Yonghua Song3
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
State Key Laboratory of Power Transmission Equipment and System Security at Chongqing University, Chongqing 400044, China
State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau 999078, China

Abstract

With the increasing interactions between natural gas systems (NGS) and power systems, component failures in one system may propagate to the other one, threatening reliable operation of the whole system. Due to neglect of such cross-sectorial failure propagation in integrated electricity-gas systems (IEGSs), traditional economy-oriented reserve expansion models may lead to unreasonable planning results. In order to address this, an innovative reserve expansion model is proposed to determine the allocation of energy production components through the harmonization between costs and reliability. First, novel multifactor-influenced reliability indices are defined considering synthetic effects of multiple uncertainties, including failure propagation, load uncertainties and generation failures. In reliability index formulation, contribution of failure propagation on system reliability is analytically expressed. To avoid high computational complexity, the fuzzy set theory is combined with conventional methods, e.g., Monte-Carlo simulation technique to reduce numerous contingency states. Sampled contingency states are aggregated into several clusters represented by a fuzzy number. To effectively solve the planning model, a decomposition approach is introduced and applied to decompose the original problem into a master problem and two correlated reliability sub-problems. Numerical studies show the proposed model can plan reasonable reserves to guarantee reliability levels of IEGSs considering failure propagation.

Keywords: reliability, Cross-sectorial failure propagation, fuzzy model, integrated electricity-gas systems, long-term reserve planning

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Received: 03 September 2021
Revised: 11 December 2021
Accepted: 31 December 2021
Published: 18 August 2022
Issue date: November 2023

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