Estimating the failure probability in an integrated energy system considering correlations among failure patterns

Highlights: • The correlations among different failure patterns are established for integrated energy systems. • Theoretical analysis and statistical experiments are presented to estimate IES reliability. • Network constraints are modelled to fully analyse the nonlinearity of the IES failure estimation. • Both the estimation accuracy and efficiency are ensured using the proposed analytical method. -- Abstract: Hydrocarbons in the form of natural gas can be used in long-term energy production and could strengthen the defossilisation of the energy sector. However, operational reliability will decrease due to gas shortages in integrated energy systems. Correlations exist among the multiple failure patterns such as overloads of the transmission lines, overloads of the combined heat and power generator, and over-limit operations of gas compressors. The energy reliability assessment problem becomes more difficult to resolve for integrated energy systems than for power systems. This paper proposes an analytical method to address the multiple correlated risks that are caused by the energy network interactions in an integrated energy system. Three case results in MATLAB demonstrate the accuracy and computational efficiency of the proposed method. Compared to the Monte Carlo algorithm, which required approximately 550 s to obtain a precise failure probability with 50 thousand samples, the proposed method takes approximately 12.7 s to obtain an exact failure probability. The advantage is that, different from wide-bound theory and narrow-bound theory, the proposed method can offer a certain value rather than two bounds with respect to the failure probability.