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Evolution Model of Source-Storage Function Characterization in New Power Systems Based on Automatic Piecewise Optimal Curve Fitting

  • Zhi Guo
  • , Shiwei Xia
  • , Xudong Zhang
  • , Jun Liu
  • , Peng Xia
  • , Wenying Liu
  • North China Electric Power University
  • State Grid Corporation of China

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Achieving the dual-carbon goals demonstrates China's commitment and responsibility as a major global power, while also posing significant challenges to the secure operation of China's new power system. On the one hand, the interaction between low-carbon emission reduction and secure power supply in new power systems leads to corresponding changes in the functional roles of various source and storage resources in supporting both decarbonization and supply security. On the other hand, these changes in functional positioning further affect the evolutionary process of low-carbon transition in new power systems. Therefore, it is an urgent issue to comprehensively consider low-carbon, security, and supply assurance factors, and to develop an evolution model of source-storage functional positioning in new power systems to characterize the evolutionary pathway. To this end, this paper first introduces a contribution-based method to address the quantification of the functional roles of various source and storage resources in low-carbon emission reduction and secure power supply during the transition of new power systems, and represents the functional evolution pathway in the form of curves. Second, according to the characteristics of these functional evolution curves, optimal fitting functions are selected, and a criterion is established to automatically segment the curves at inflection points for piecewise fitting, thereby developing an evolution model of source-storage functional positioning in new power systems based on contribution-oriented automatically segmented optimal function curve fitting. Finally, simulation-based error analysis is conducted using China's 2030 energy planning data to verify the reliability of the proposed model, providing theoretical and technical support for assessing the transition process and energy planning of new power systems in China.

Original languageEnglish
Title of host publication2026 IEEE 3rd International Conference on Electrical Power Systems and Intelligent Control, EPSIC 2026
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331552534
DOIs
StatePublished - 2026
Externally publishedYes
Event3rd IEEE International Conference on Electrical Power Systems and Intelligent Control, EPSIC 2026 - Hybrid, Tianjin, China
Duration: 22 May 202624 May 2026

Publication series

Name2026 IEEE 3rd International Conference on Electrical Power Systems and Intelligent Control, EPSIC 2026

Conference

Conference3rd IEEE International Conference on Electrical Power Systems and Intelligent Control, EPSIC 2026
Country/TerritoryChina
CityHybrid, Tianjin
Period22/05/2624/05/26

Keywords

  • Double carbon targets
  • Evolutionary modeling
  • New power system
  • Piecewise fitting
  • Source-storage functional positioning

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