Distributed Bilinear State Estimation Based on ADMM for Integrated Energy System Combining Electricity, Heat and Gas

Abstract

With the rapid development of integrated energy system (IES), there is an urgent need to implement state estimation to obtain accurate system-wide states for online analysis and optimal dispatch. Moreover, compared with the centralized scheme, distributed state estimation is more practical for IES due to the preservation of privacy, low communication burden, and high efficiency. This paper proposes a distributed bilinear state estimation algorithm based on the alternating direction method of multipliers (ADMM), which is applicable to IES combining electricity, heat, and gas. Based on the bilinear state estimation model, the conventional state estimation for IES is converted to a three-stage convex problem, including two linear estimation stages and an intermediate nonlinear transformation stage. Each of the three stages is further decoupled over the three sub-systems to perform a fully distributed state estimation via ADMM. A modified ADMM with self-adjusting penalty parameter is adopted to accelerate the convergence of ADMM iterations. Simulation results demonstrate the validity of the proposed algorithm.