A systematic framework for the assessment of the reliability of energy supply in Integrated Energy Systems based on a quasi-steady-state model. (15th January 2023)

• Record Type: Journal Article
• Authors: Chi, Lixun; Su, Huai; Zio, Enrico; Qadrdan, Meysam; Zhou, Jing; Zhang, Li; Fan, Lin; Yang, Zhaoming; Xie, Fei; Zuo, Lili; Zhang, Jinjun
• Is Part Of: Energy. Volume 263:Part B(2023)
• Publication Date: 2023-01-15
• Subjects: Reliability assessment -- Quasi-steady-state model -- CSML model; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.125740
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The reliability analysis of IESs (Integrated Energy Systems) is a complicated task because of the complex characteristics of different subsystems and the multi-scale dynamics that develop therein. To effectively address such problems, this paper proposes a systematic framework to analyse the reliability of energy supply in IESs, considering the dynamics of IESs and the inter-relationships among uncertainties. First, based on the linepack-based performance analysis model of IES, a quasi-steady-state model is established to model the dynamic behaviours in IESs, properly accounting for practical engineering and operational strategies. Then, considering the inter-correlations among different uncertainty sources and time-dependent relationships of each variable, a model that combines the statistical structure of copula with the machine learning method of stacked autoencoder (CSML) is adopted to establish the timely multivariate joint distributions for variables. Monte Carlo simulation combined with Order Statistics is used for assessing supply reliability. Case studies are performed on a realistic IES that combines an IEEE-15 power system with an 18-node natural gas pipeline network. The efficiency and accuracy of the quasi-steady-state model are validated. The reliability evaluation results show that the inter-correlations among variables and time-dependent relationships of each variable have great effects on the system reliability assessment. The consideration of linepack can significantly improve the supply reliability of IES whereas the management strategy of linepack may lead to some risky points. Highlights: A unified quasi-steady-state electric-gas IES model. The correlations among uncertain factors are considered. The impact of the management strategy of linepack are investigated.