Zehua Yin , Xiaoqing Han , Tingjun Li , Xinfang Zhang , Wenchuan Wu
{"title":"A high-accuracy model of gas network for dynamic analysis of electricity-gas energy flow","authors":"Zehua Yin , Xiaoqing Han , Tingjun Li , Xinfang Zhang , Wenchuan Wu","doi":"10.1016/j.seta.2024.104018","DOIUrl":null,"url":null,"abstract":"<div><div>Accurate simulation of the dynamic energy flow is crucial for the reliability and economics of the integrated electric and gas systems (IEGS). In order to simplify the complex partial differential equations (PDEs) in the gas dynamics, previous studies have typically approximated the flow coefficients in the PDEs as fixed values. However, the flow coefficients vary significantly with the operating state of the IEGS, and ignoring this variation could lead to inaccurate modeling. In this paper, the expression for the flow coefficients is derived and the gas dynamics PDEs are transformed into variable coefficient partial differential equations (VC-PDEs). To solve the proposed VC-PDEs, a three-stage leapfrog finite difference method (TL-FDM) is developed, which updates the flow coefficients in real-time during the solution process, thus enabling high-accuracy simulation of the gas flow model. The consistency and stability of the proposed model are proven theoretically. In addition, an IEGS optimal scheduling model is developed based on the proposed dynamic gas flow model, and the improvement of system flexibility and reliability through high-accuracy gas flow simulation is quantitatively analyzed. Case studies demonstrate the accuracy and efficiency of the proposed model in different systems.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"71 ","pages":"Article 104018"},"PeriodicalIF":7.1000,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Technologies and Assessments","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213138824004144","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate simulation of the dynamic energy flow is crucial for the reliability and economics of the integrated electric and gas systems (IEGS). In order to simplify the complex partial differential equations (PDEs) in the gas dynamics, previous studies have typically approximated the flow coefficients in the PDEs as fixed values. However, the flow coefficients vary significantly with the operating state of the IEGS, and ignoring this variation could lead to inaccurate modeling. In this paper, the expression for the flow coefficients is derived and the gas dynamics PDEs are transformed into variable coefficient partial differential equations (VC-PDEs). To solve the proposed VC-PDEs, a three-stage leapfrog finite difference method (TL-FDM) is developed, which updates the flow coefficients in real-time during the solution process, thus enabling high-accuracy simulation of the gas flow model. The consistency and stability of the proposed model are proven theoretically. In addition, an IEGS optimal scheduling model is developed based on the proposed dynamic gas flow model, and the improvement of system flexibility and reliability through high-accuracy gas flow simulation is quantitatively analyzed. Case studies demonstrate the accuracy and efficiency of the proposed model in different systems.
期刊介绍:
Encouraging a transition to a sustainable energy future is imperative for our world. Technologies that enable this shift in various sectors like transportation, heating, and power systems are of utmost importance. Sustainable Energy Technologies and Assessments welcomes papers focusing on a range of aspects and levels of technological advancements in energy generation and utilization. The aim is to reduce the negative environmental impact associated with energy production and consumption, spanning from laboratory experiments to real-world applications in the commercial sector.