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Evaluation of distributed building thermal energy storage in conjunction with wind and solar electric power generation

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  • Jones, Byron W.
  • Powell, Robert

Abstract

Energy storage is often seen as necessary for the electric utility systems with large amounts of solar or wind power generation to compensate for the inability to schedule these facilities to match power demand. This study looks at the potential to use building thermal energy storage as a load shifting technology rather than traditional electric energy storage. Analyses are conducted using hourly electric load, temperature, wind speed, and solar radiation data for a 5-state central U.S. region in conjunction with simple computer simulations and economic models to evaluate the economic benefit of distributed building thermal energy storage (TES). The value of the TES is investigated as wind and solar power generation penetration increases. In addition, building side and smart grid enabled utility side storage management strategies are explored and compared. For a relative point of comparison, batteries are simulated and compared to TES. It is found that cooling TES value remains approximately constant as wind penetration increases, but generally decreases with increasing solar penetration. It is also clearly shown that the storage management strategy is vitally important to the economic value of TES; utility side operating methods perform with at least 75% greater value as compared to building side management strategies. In addition, TES compares fairly well against batteries, obtaining nearly 90% of the battery value in the base case; this result is significant considering TES can only impact building thermal loads, whereas batteries can impact any electrical load. Surprisingly, the value of energy storage does not increase substantially with increased wind and solar penetration and in some cases it decreases. This result is true for both TES and batteries and suggests that the tie between load shifting energy storage and renewable electric power generation may not be nearly as strong as typically thought.

Suggested Citation

  • Jones, Byron W. & Powell, Robert, 2015. "Evaluation of distributed building thermal energy storage in conjunction with wind and solar electric power generation," Renewable Energy, Elsevier, vol. 74(C), pages 699-707.
    • Handle: RePEc:eee:renene:v:74:y:2015:i:c:p:699-707
    DOI: 10.1016/j.renene.2014.08.031
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    References listed on IDEAS

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    Cited by:

    1. Alva, Guruprasad & Lin, Yaxue & Fang, Guiyin, 2018. "An overview of thermal energy storage systems," Energy, Elsevier, vol. 144(C), pages 341-378.
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    3. Li, Yu & Rezgui, Yacine & Zhu, Hanxing, 2017. "District heating and cooling optimization and enhancement – Towards integration of renewables, storage and smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 281-294.
    4. Zhang, Hao & Cai, Jie & Fang, Kan & Zhao, Fu & Sutherland, John W., 2017. "Operational optimization of a grid-connected factory with onsite photovoltaic and battery storage systems," Applied Energy, Elsevier, vol. 205(C), pages 1538-1547.
    5. Wiesheu, Michael & Rutešić, Luka & Shukhobodskiy, Alexander Alexandrovich & Pogarskaia, Tatiana & Zaitcev, Aleksandr & Colantuono, Giuseppe, 2021. "RED WoLF hybrid storage system: Adaptation of algorithm and analysis of performance in residential dwellings," Renewable Energy, Elsevier, vol. 179(C), pages 1036-1048.
    6. Omais Abdur Rehman & Valeria Palomba & Andrea Frazzica & Luisa F. Cabeza, 2021. "Enabling Technologies for Sector Coupling: A Review on the Role of Heat Pumps and Thermal Energy Storage," Energies, MDPI, vol. 14(24), pages 1-30, December.
    7. Kamal, Rajeev & Moloney, Francesca & Wickramaratne, Chatura & Narasimhan, Arunkumar & Goswami, D.Y., 2019. "Strategic control and cost optimization of thermal energy storage in buildings using EnergyPlus," Applied Energy, Elsevier, vol. 246(C), pages 77-90.
    8. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    9. Li, Xiwang & Wen, Jin & Malkawi, Ali, 2016. "An operation optimization and decision framework for a building cluster with distributed energy systems," Applied Energy, Elsevier, vol. 178(C), pages 98-109.

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