Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics

Abstract

State estimation plays an important role in the monitoring and control of integrated electric–gas systems (IEGSs), but it faces limitations due to insufficient measurement configurations and low data redundancy in these systems; additional measurement configurations are needed to increase the overall system observability. Owing to the lack of suitable observability analysis methods, optimal measurement configurations for IEGSs remain underexplored. This paper presents an IEGS observability analysis method that incorporates gas flow dynamics via the Lie derivative. This method incorporates the complex topological structure of the gas network and the dynamic process of gas flow into the IEGS observability analysis. Furthermore, the measurement configuration problem for IEGSs considering gas flow dynamics is formulated as a rank-constrained optimization problem. To handle the rank constraints effectively, an iterative cutting method is developed with convergence guarantees. Finally, the efficacy and practicality of the proposed methods are validated through case studies of varying scales. The proposed optimal measurement configuration model reduces measurement configuration costs while maintaining system observability.