• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

ELECTRIC POWER CONSTRUCTION ›› 2023, Vol. 44 ›› Issue (1): 39-46.doi: 10.12204/j.issn.1000-7229.2023.01.005

• National Key R&D Program of China • Previous Articles     Next Articles

Research on Operation Optimization of CCHP System Under Climate Change Based on TRNSYS

XU Ye1,2(), HE Zhechen1,2, TAN Junyuan1,2, GUO Junhong1,2, LI Wei1,2, LI Yalou3   

  1. 1. The College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
    2. MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Beijing 102206, China
    3. State Key Laboratory of Power Grid Safety and Energy Conservation (China Electric Power Research Institute), Beijing 100192, China
  • Received:2022-07-26 Online:2023-01-01 Published:2022-12-26
  • Contact: XU Ye E-mail:1591164778xuye@edu.cn


The extreme weather caused by climate change will have large impact on building load and energy supply strategy of combined cooling, heating and power (CCHP) system. Firstly, taking a hospital in Shanghai as the main research object, the regional climate model (PRECIS) is used to predict the temperature change of the area in the future to 2100. Secondly, the TRNSYS software is utilized to build energy consumption model of the hospital for calculating the annual hourly load under climate change. Next, the operation optimization model of CCHP system with the consideration of load variation is formulated. Finally, the operation scheme of the energy supply system adapting to climate change is generated. Load-prediction results demonstrated that the fluctuation variation trend of the cooling and heating load of targeted building caused by the extreme high temperature might lead to the imbalance between energy provision and requirement, e.g., the insufficient cold supply under the hot summer and the excessive heat supply under the warm winter. Compared with the traditional optimization model, the coordinated operation scheme generated by proposed model is capable of enhancing the user experience, reducing the cost and increasing the benefit.

This work is supported by National Key R&D Program of China (No. 2018YFE0208400).

Key words: combined cooling, heating and power (CCHP), climate change, load prediction, cooperative optimization

CLC Number: