Optimal Scheduling of Integrated Electricity-Gas Network Considering Topology Control Actions: A Two-Stage Hybrid Robust-Stochastic Approach

Abstract

Integrated energy systems (IESs) with deep coupling of electric power and natural gas have recently attracted much attention. The issue of increasing uncertainty in both the generation and load sides of an integrated electric-natural gas system (IENGS) is a concerning problem. In this paper, a hybrid robust-stochastic optimization (RSO) framework is introduced to address the day-ahead contingency-constrained unit commitment (CCUC) problem of an IENGS equipped with promising technologies. The objective of the research is to minimize the total operation cost of the CCUC problem while ensuring system security under multiple uncertainties and contingencies. The uncertainties of load and gas demands are generated using the Monte Carlo Simulation (MCS) method, while a robust uncertainty set is applied to handle wind power deviations. Generation scheduling and topology control action are also co-optimized. To solve the proposed CCUC as a nonconvex problem, an augmented nested column-and-constraint generation algorithm is used to enhance the performance of the decomposition procedure. The quantitative results imply that with a negligible increase of 6.88% in operation cost, a huge cost reduction of 38.06% in the long run model can be anticipated. Additionally, the results show the effectiveness of the TLS action in day-ahead operation, reducing the total cost by up to 17.5%.