Failure probability estimation of gas supply using the central moment method in an integrated energy system

The reliable supply of natural gas ensures the safe and stable operation of an integrated energy system. Operational uncertainty of the integrated energy system (IES) such as a surge in heating load can exacerbate an unreliable supply situation of natural gas. This paper examines gas supply reliability. A central moment method is proposed to estimate the failure probabilities for the gas supply in a combined heat- and power-based microintegrated energy system. To make the calculation more relevant to an actual project, we considered the energy network constraints and energy stochastic characteristics. To demonstrate the use of the central moment method in the estimation of failure probability of a gas supply, the results were validated using sufficient comparisons with traditional methods. Classic traditional methods include the Iman and Stein methods, the first order reliability method, the mixed algorithm based on Latin hypercube sampling, the Cholesky decomposition and the Nataf transformation, and the principle of maximum entropy method. An actual integrated energy system is provided to promote practical solutions for failure probability estimation of the gas supply.