Probabilistic-Interval Energy Flow Analysis of Regional Integrated Electricity and Gas System Considering Multiple Uncertainties and Correlations

This paper studies the uncertainty analysis of the regional integrated electricity and gas system (IEGS) composed of a three-phase unbalanced power distribution system and a gas distribution network. The well-known probabilistic energy flow (PEF) analysis of IEGS is extended to a comprehensive probabilistic-interval energy flow (PIEF) problem by modeling uncertainties in pipeline parameters as interval variables and spatial dependency between them as correlation angles. The polynomial chaos expansion (PCE) method is introduced to IEGS analysis and an improved PCE-based method combining the technique of dimension-reduction and the sparse-PCE is proposed to address the numerous uncertainties involved in a regional IEGS. A methodological framework considering probabilistic/interval uncertainties, linear/rank correlations among probabilistic variables, and dependency between interval variables is then developed for both PEF and PIEF analysis. Numerical simulations of a sample regional IEGS are used to verify the accuracy and efficiency of the proposed method, as well as the superiority of the proposed PIEF analysis over the existing PEF analysis.