PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 22, 2026Thermal Science0 citationsOpen Access

Construction of an economic evaluation model for regional energy systems based on thermal energy storage technology

YXYing XiaoAJAo JiaoNMNing Mou

Key Points

  • The aim is to create an economic evaluation model that minimizes lifecycle costs while maximizing energy efficiency for regional energy systems.
  • Developed a three-tiered parameter-indicator-optimization model.
  • Coupled charge-discharge efficiency decay curves with regional load fluctuations.
  • Conducted simulations using MATLAB/SIMULINK across four benchmark cases.
  • Analyzed 27 different scenarios under varying economic and environmental conditions.
  • Case 2 (Shanghai Commercial Complex) achieved an NPV of 1.286 million Yuan.
  • A 0.1 Yuan/kWh increase in subsidy results in an average 18.3% NPV increase.
  • Case 3 (Haikou Industrial Park) had a carbon reduction benefit valued at 3500 Yuan per kWh.
  • The correlation between thermal storage capacity and CER was strong (R2 = 0.98).

Abstract

This study constructs an economic evaluation model with the dual objectives of minimizing lifecycle costs and maximizing energy efficiency. This model employs a three-tiered "parameter-indicator-optimization" architecture. Its core approach is to dynamically couple the charge-discharge efficiency decay curves of thermal energy storage devices with regional load fluctuation coefficients to establish an hourly cost-benefit mapping. This coupling addresses static parameter flaws in existing models and improves alignment with real operating conditions. The model incorporates six economic indicators and uses MATLAB/SIMULINK as its core simulation platform. Four benchmark cases (covering different climate zones and user types) and 27 comparison scenarios are designed. Simulation results show that Case 2 (Shanghai Commercial Complex) is optimal with a 1000 kWh thermal storage capacity and a medium subsidy, achieving an net present value (NPV) of 1.286 million Yuan and an ECR of 1.42. For every 0.1 Yuan/kWh increase in sub?sidy, the NPV increases by an average of 18.3%. The CER was linearly correlated with the thermal storage capacity (R2 = 0.98). Case 3 (Haikou Industrial Park) achieved a unit thermal storage carbon reduction benefit of 3500 Yuan per kWh, 1.5 times that of Case 1.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Xiao et al. (2026) studied this question.

synapsesocial.com/papers/699a9e0e482488d673cd476dhttps://doi.org/10.2298/tsci2601145x
Ask AI
Helpful
Bookmark
Share
View Full Paper