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Optimize heat prosumers' economic performance under current heating price models by using water tank thermal energy storage

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  • Li, Haoran
  • Hou, Juan
  • Tian, Zhiyong
  • Hong, Tianzhen
  • Nord, Natasa
  • Rohde, Daniel

Abstract

Due to heat prosumers' dual roles of heat producer and heat consumer, the future district heating (DH) systems will become more flexible and competitive. However, the current heating price models have not yet supported the reverse heat supply from prosumers to the central DH system, which means the prosumers would gain no economic benefit from supplying heat to the central DH system. These unidirectional heating price models will reduce interest in prosumers, and thus hinder the promotion of prosumers in DH systems. This study aimed to optimize prosumers' economic performance under the current heating price models by introducing water tank thermal energy storage (WTTES). A dynamic optimization problem was formulated to explore prosumers' economic potentials. The size parameter of WTTESs was swept in prosumers to obtain the optimal storage size considering the trade-off between the payback period and the heating cost saving. The proposed method was tested on a campus DH system in Norway. The results showed that the prosumer's annual heating cost was saved up to 9%, and the investment of WTTES could be recovered in less than ten years. This study could provide guidelines on improving prosumers' economic performance and promote the development of prosumers during the transformation period of DH systems.

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  • Li, Haoran & Hou, Juan & Tian, Zhiyong & Hong, Tianzhen & Nord, Natasa & Rohde, Daniel, 2022. "Optimize heat prosumers' economic performance under current heating price models by using water tank thermal energy storage," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221023513
    DOI: 10.1016/j.energy.2021.122103
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    6. Joel Alpízar-Castillo & Laura Ramirez-Elizondo & Pavol Bauer, 2022. "Assessing the Role of Energy Storage in Multiple Energy Carriers toward Providing Ancillary Services: A Review," Energies, MDPI, vol. 16(1), pages 1-31, December.
    7. Yin, Linfei & Tao, Min, 2023. "Balanced broad learning prediction model for carbon emissions of integrated energy systems considering distributed ground source heat pump heat storage systems and carbon capture & storage," Applied Energy, Elsevier, vol. 329(C).
    8. Ryan, Erich & McDaniel, Benjamin & Kosanovic, Dragoljub, 2022. "Application of thermal energy storage with electrified heating and cooling in a cold climate," Applied Energy, Elsevier, vol. 328(C).
    9. Hering, Dominik & Faller, Michael R. & Xhonneux, André & Müller, Dirk, 2022. "Operational optimization of a 4th generation district heating network with mixed integer quadratically constrained programming," Energy, Elsevier, vol. 250(C).
    10. Lee, Minwoo & Han, Changho & Kwon, Soonbum & Kim, Yongchan, 2023. "Energy and cost savings through heat trading between two massive prosumers using solar and ground energy systems connected to district heating networks," Energy, Elsevier, vol. 284(C).
    11. Hou, Juan & Li, Haoran & Nord, Natasa, 2022. "Nonlinear model predictive control for the space heating system of a university building in Norway," Energy, Elsevier, vol. 253(C).
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