A systematic framework for the assessment of the reliability of energy supply in Integrated Energy Systems based on a quasi-steady-state model
Résumé
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. © 2022
Mots clés
Quasi-steady-state models
Reliability assessments
Supply reliability
Systematic framework
Time dependent
Assessment method
gas pipeline
Machine learning
Natural gas
Reliability analysis
CSML model
Quasi-steady-state model
Reliability assessment
Intelligent systems
Learning systems
Monte Carlo methods
Natural gas pipelines
Uncertainty analysis
Complex characteristics
Dependent relationship
Energy supplies
Integrated energy systems