Distributed robust cooperative scheduling of multi-region integrated energy system considering dynamic characteristics of networks

Abstract

Due to the advantages of reliability and economy, multiple adjacent region integrated energy systems (IESs) are interconnected to form a multi-region IES through multi-energy network. However, the limitation on private data exchange, multi-uncertainty and the complex dynamic characteristics bring challenges to the optimal scheduling of the multi-region IES. This paper proposes a distributed robust cooperative scheduling method for the multi-region electricity–natural gas–heat IES considering the dynamic characteristics and the uncertainties of wind turbine (WT) and electricity load. Firstly, a robust scheduling model of the multi-region IES considering dynamic characteristics and the uncertainties is built. In particular, the dynamic transmission models of gas and heating networks are constructed, and a regulation model of virtual heat storage is built to control the virtual heat storage in district heating network (DHN). Further, to preserve the information privacy and decision-making independence for each sub-region IES, a distributed cooperative scheduling framework based on the consensus-based alternating direction method of multipliers (ADMM) is developed for the multi-region IES, where the original robust scheduling model is decomposed into several subproblems that are solved independently. Moreover, the nonconvex dynamic natural gas flow function is addressed by convex relaxation technique, and the max–min robust model with binary variables is solved by alternative optimization procedure (AOP) method and duality theory. Finally, the simulation results show that the proposed method can converge reliably, realize the balance between the operation cost and the heat loss and provide a flexible scheduling scheme for the multi-region IES.