Prediction-Correction Affine Energy Flow Algorithm for Integrated Electricity and Natural Gas System

Integrated electricity and natural gas system (IEGS) plays an important role in increasing efficiency of energy usage. Uncertain power flow calculation is helpful to system optimization and scheduling with increasingly prominent uncertainty. In this paper, an affine energy flow algorithm for integrated electricity and natural gas system is proposed to analyze the system uncertainty. First, the affine models and energy flow equations of the system are established. Secondly, the prediction-correction affine energy flow algorithm is proposed. The algorithm predicts the state variable according to the sensitivity analysis, and introduces correction coefficients to compress the predicted state variable. At the same time, an improved decomposition method of multi energy flow is adopted, without considering the calculation order of multi energy flow in the complex coupling network. Finally, the case simulation verifies the advantages of the affine power flow method in conservatism, computational efficiency and tracking the source of uncertainty.