Gas Network Aggregate Modeling and Identification Method for Integrated Energy System Operation
Year: 2025
Type: article
Abstract: ObjectivesNatural gas networks are important components of integrated energy systems, which can provide considerable flexibility for the operation of the integrated energy system. Developing an accurate gas network model is the foundation for the operation and control of integrated energy systems. However, existing mechanism models for gas networks show high complexity, with certain parameters being unidentifiable in practical engineering applications. Therefore, this study proposes a gas network aggregate modeling and identification method specifically for integrated energy system operation.MethodsTaking the gas network as the research object, the concept of the gas network aggregate model is proposed, its formula is derived, and a corresponding offline parameter estimation method is designed. Since the derivation of the gas network aggregate model depends on specific operating conditions, the model parameters vary with condition changes, leading to non-negligible errors in the offline estimation model. To address this issue, a rolling calibration method based on forgetting factor recursive least squares is proposed.ResultsUnder small gas flow variations, the offline parameter estimation method demonstrates satisfactory accuracy. However, under rapid flow variations, the offline estimation fails to accurately describe the operation status of the gas network, and rolling calibration can achieve accurate fitting of the model.ConclusionsThe proposed gas network aggregate model integrating offline estimation and online rolling calibration can provide a practical and efficient fluid network modeling solution for the operation analysis and control of integrated energy systems.
Authors: SUN Yong, GAO Zihang, HOU Zeyin, LI Dexin, WANG Yao, ZHANG Haifeng, LU Shuai
Institutions: State Grid Jilin Electric Power (China), Southeast University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7084071623
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