Gas Network Aggregate Modeling and Identification Method for Integrated Energy System Operation

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.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
DOI
https://doi.org/10.12096/j.2096-4528.pgt.24118
Primary Topic
Food Security and Health in Diverse Populations
Type
article
Field-Weighted Citation Impact
0.00
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article

Gas Network Aggregate Modeling and Identification Method for Integrated Energy System Operation

SHILAP Revista de lepidopterología
Food Security and Health in Diverse Populations
article

Gas Network Aggregate Modeling and Identification Method for Integrated Energy System Operation

article en

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.

SHILAP Revista de lepidopterología
Jilin Electric Power Research Institute (China) (CN), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 33%
Food Security and Health in Diverse Populations
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