Multi-Linear Probabilistic Energy Flow Analysis of Integrated Electrical and Natural-Gas Systems

TLDR

The deep interdependence between electrical and gas systems poses a threat to their security, making it essential to study how massive uncertainties affect their secure and economical operation. The paper proposes a probabilistic energy flow framework for integrated electrical and gas systems that accounts for correlated energy demands and wind power. The framework models couplings via gas‑fired generators, electric‑driven compressors, and power‑to‑gas units, and uses a multilinear method to generate deterministic energy flow solutions for each Monte Carlo sample. Test results show that the multilinear Monte Carlo method outperforms nonlinear MCS and that power‑to‑gas units improve the operation of both networks.

Abstract

The deep interdependence between electrical and gas systems entails a potential threat to the security (or reliability) of both systems. It is imperative to investigate the impacts of massive uncertainties on the overall secure and economical operation of both systems. In this paper, a probabilistic energy flow framework of integrated electrical and gas systems is initially proposed considering correlated varying energy demands and wind power. Three aspects of couplings between electrical and gas systems are considered: gas-fired generators, electric-driven compressors, and energy hubs integrated with power to gas (P2G) units. Furthermore, a multilinear method is specially designed to produce a deterministic energy flow solution for each sample generated by Monte Carlo simulation (MCS). Finally, test results have verified that the proposed multilinear MCS method prevails over the nonlinear MCS. In addition, P2G effectively benefits the operation of both electrical and gas networks.