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面向可再生能源集成的综合能源系统熵态计算模型

李宜哲 王丹 李家熙 贾宏杰 周天烁 刘佳委

电力系统自动化2024,Vol.48Issue(11):162-172,11.
电力系统自动化2024,Vol.48Issue(11):162-172,11.DOI:10.7500/AEPS20230813002

面向可再生能源集成的综合能源系统熵态计算模型

Entropy State Calculation Model of Integrated Energy System for Renewable Energy Integration

李宜哲 1王丹 2李家熙 1贾宏杰 2周天烁 1刘佳委1

作者信息

  • 1. 智能电网教育部重点实验室(天津大学),天津市 300072
  • 2. 智能电网教育部重点实验室(天津大学),天津市 300072||天津市智慧能源与信息技术重点实验室(天津大学),天津市 300072
  • 折叠

摘要

Abstract

The entropy state mechanism and analysis method of the integrated energy system(IES)provides a new theoretical basis for the analysis of IES energy quality for renewable energy integration.For different energy system scales and scenarios,how to systematically solve the entropy state distribution of large-scale energy systems is one of the basic problems that need to be solved urgently in subsequent system planning,operation,and energy management and control.On the basis of IES entropy state theory,the calculation system and ideas of the system entropy state distribution are further sorted out.According to the needs of solving the entropy increase flow,some key calculation matrices and calculation column vectors are defined.Then,combined with the definition of IES exergy flow model and entropy state network,considering the entropy increase flow conversion and distribution mechanism of energy hub(energy station),the IES entropy state calculation models based on sequential solution and simultaneous solution are established.The correctness and effectiveness of the two calculation models are verified by cases,and the similarities,differences and applicability of the two calculation methods are discussed.

关键词

综合能源系统/可再生能源/能量品质/熵态/熵增流/㶲流/㶲损

Key words

integrated energy system/renewable energy/energy quality/entropy state/entropy increase flow/exergy flow/exergy loss

引用本文复制引用

李宜哲,王丹,李家熙,贾宏杰,周天烁,刘佳委..面向可再生能源集成的综合能源系统熵态计算模型[J].电力系统自动化,2024,48(11):162-172,11.

基金项目

国家自然科学基金资助项目(51977141) (51977141)

国家重点研发计划资助项目(2018YFB0905000) (2018YFB0905000)

国家电网公司总部科技项目(SGTJDK00DWJS1800232). This work is supported by National Natural Science Foundation of China(No.51977141),National Key R&D Program of China(No.2018YFB0905000),and State Grid Corporation of China(No.SGTJDK00DWJS1800232). (SGTJDK00DWJS1800232)

电力系统自动化

OA北大核心CSTPCD

1000-1026

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