The existing studies on probabilistic steady-state analysis of integrated energy systems (IES) are limited to integrated electricity and gas networks or integrated electricity and heating networks. This paper proposes a probabilistic steady-state analysis of integrated electricity, gas and heating networks (EGH-IES). Four typical operation modes of an EGH-IES are presented at first. The probabilistic energy flow problem of the EGS-IES considering its operation modes and correlated uncertainties in wind/solar power and electricity/gas/heat loads is then formulated and solved by the Monte Carlo method based on Latin hypercube sampling and Nataf transformation. Numerical simulations are conducted on a sample EGH-IES working in the “electricity/gas following heat” mode to verify the probabilistic analysis proposed in this paper and to study the effects of uncertainties and correlations on the operation of the EGH-IES, especially uncertainty transmissions among the subnetworks.

The wide application of combined heat and power (CHP) units increases the interaction between electricity and heating networks and the interest in combined analysis of the integrated electricity and heating networks (IEHNs). However, most of the existing power and mass flow (PMF) analysis methods for IEHNs are deterministic in nature, which cannot address the uncertainties and their effects on the operation of IEHNs. Therefore, the well-known concept of probabilistic power flow (PPF) analysis of an electricity network is extended to IEHNs in this paper. A probabilistic power and mass flow (PPMF) problem of IEHNs considering various uncertainties and correlations in wind speeds, electricity loads, and heat loads under both grid-connected mode and island mode is formulated at first. A probabilistic method based on the Latin hypercube sampling (LHS) technique and Nataf transformation is then developed to solve the PPMF problem. Finally, the effectiveness of the proposed method is verified by a sample IEHN composed of a 33-bus distribution system and a 27-node heating network.