Global Sensitivity Analysis for Integrated Heat and Electricity Energy System

Abstract

Although global sensitivity analysis (GSA) is gaining increasing popularity in power systems due to its ability to measure the importance of uncertain inputs, it has not been explored in the integrated energy system (IES) in the existing literature. Indeed, when coupled multi-energy systems (e.g., heating networks) are considered, the power system operation states are inevitably altered. Accordingly, its associated GSA, which relies on Monte Carlo simulations (MCS), becomes even more computationally prohibitive since it not only increases the model complexity but also faces large uncertainties. To address these issues, this paper proposes a double-loop generalized unscented transform (GenUT)-based strategy that, for the first time, explores the GSA in the IES while simultaneously achieving high computing efficiency and accuracy. More specifically, we first propose a GenUT method that can propagate the moment information of correlated input variables following different types of probability distributions in the IES. We further design a double-loop sampling scheme for GenUT to evaluate the GSA for correlated uncertainties in a cost-effective manner. The simulations of multiple heat- and power-coupled IESs reveal the excellent performance of the proposed method.