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Comparative analysis of optimal operation strategies for district heating and cooling system based on design and actual load

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  • Deng, Na
  • He, Guansong
  • Gao, Yuan
  • Yang, Bin
  • Zhao, Jun
  • He, Shunming
  • Tian, Xue

Abstract

Computational load significantly influences energy and cost savings when developing an operation strategy for a district heating and cooling system. In this study, a model was identified to study the effects of the difference between design load and actual load on an optimal operation strategy. The established model is strongly dependent on the economy principle, and the proposed optimal strategy could achieve a dynamic balance between the users’ load and the system energy supply. This model was validated at 30% load rate, which demonstrated an obvious cost saving of 63.6% under the actual load and 42.2% under the design load. Based on the current strategy, the optimal strategy at different load rates was analyzed with respect to two characteristics of each sub-system: energy outputs and operation costs. Furthermore, in the optimal strategy, changes in total operation costs and cost savings rates under different load rates are also discussed. The results showed that, when the load rate was changed from 30 to 75%, the savings rates based on the design load were 42.2, 17.9, 2.5, and −12.6%, and the savings rates based on the actual load were 63.6, 49.8, 34.3, and 25.7%, respectively. Based on the actual load, the energy savings advantage of the optimal operation strategy could be maximized, in particular, during the initial stage of project construction. Furthermore, the commercial software MATLAB was used for programming and calculations. The simulation results indicated that the application of the combined cooling, heating, and power system could significantly improve the cost-effectiveness.

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  • Deng, Na & He, Guansong & Gao, Yuan & Yang, Bin & Zhao, Jun & He, Shunming & Tian, Xue, 2017. "Comparative analysis of optimal operation strategies for district heating and cooling system based on design and actual load," Applied Energy, Elsevier, vol. 205(C), pages 577-588.
    • Handle: RePEc:eee:appene:v:205:y:2017:i:c:p:577-588
    DOI: 10.1016/j.apenergy.2017.07.104
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    2. Pilotelli, M. & Grassi, B. & Lezzi, A.M. & Beretta, G.P., 2022. "Flow models of perforated manifolds and plates for the design of a large thermal storage tank for district heating with minimal maldistribution and thermocline growth," Applied Energy, Elsevier, vol. 322(C).
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    4. Haiyan Meng & Yakai Lu & Zhe Tian & Xiangbei Jiang & Zhongqing Han & Jide Niu, 2023. "Performance Evaluation Method of Day-Ahead Load Prediction Models in a District Heating and Cooling System: A Case Study," Energies, MDPI, vol. 16(14), pages 1-19, July.
    5. Chicherin, Stanislav, 2020. "Methodology for analyzing operation data for optimum district heating (DH) system design: Ten-year data of Omsk, Russia," Energy, Elsevier, vol. 211(C).

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