Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation
作者机构：the College of Electrical EngineeringZhejiang UniversityHangzhou 310027China the State Key Laboratory of Power Transmission Equipment and System Security at Chongqing UniversityChongqing 400044China the State Key Laboratory of Internet of Things for Smart CityUniversity of MacaoMacao 999078China
出 版 物：《CSEE Journal of Power and Energy Systems》 (中国电机工程学会电力与能源系统学报（英文）)
年 卷 期：2023年第9卷第6期
页 面：2236-2250页
核心收录：
学科分类：0820[工学-石油与天然气工程] 080801[工学-电机与电器] 0808[工学-电气工程] 08[工学]
基 金：the China NSFC under Grant 71871200 National Natural Science Foundation China and Joint Programming Initiative Urban Europe Call(NSFC-JPI UE)under grant 71961137004。
主 题：Cross-sectorial 1 failure propagation fuzzy model integrated electricity-gas systems long-term reserve planning reliability
摘 要：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 con-sidering 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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