IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v255y2019ics030626191931534x.html
   My bibliography  Save this article

Model complexity of heat pump systems to investigate the building energy flexibility and guidelines for model implementation

Author

Listed:
  • Clauß, John
  • Georges, Laurent

Abstract

Building performance simulation (BPS) is a powerful tool for engineers working in building design and heating, ventilation and air-conditioning. Many case studies using BPS investigate the potential of demand response (DR) measures with heat pumps. However, the models are often simplified for the components of the heat pump system (i.e. heat pump, electric auxiliary heater and storage tank) and for their interactions. These simplifications may lead to significant differences in terms of DR performance so that more comprehensive models for a heat pump system may be necessary. The contribution of this work is twofold. Firstly, this work investigates the influence of the modeling complexity of the heat pump control on different key performance indicators for the energy efficiency, the DR potential and the heat pump operation. To this end, the performance of six different heat pump controls is compared. Secondly, it describes the implementation of a comprehensive control for a heat pump system in BPS tools. This control is not often documented in the BPS literature and is error-prone. Generic pseudo-codes are provided, whereas IDA ICE is taken as an example in the case study. A predictive rule-based control is implemented to study price-based DR of residential heating. It is shown that a realistic operation of the heat pump system can be achieved using the proposed modeling approach. The results prove that the modeling complexity of the system control has a significant impact on the performance indicators, meaning that this aspect should not be overlooked. For some performance indicators, e.g. the annual energy use for heating and average water tank temperature, it is shown that a proportional (P-) and proportional-integral (PI-) control can lead to similar results. If the heat pump operation is investigated in detail and a short-time resolution is required, the difference between P- and PI-controls and their tuning is important. As long as the heat pump operation and electrical power at short timescales are not of importance, the choice of controller (P or PI) is not crucial. However, the use of P-control significantly simplifies the modeling work compared to PI-control. If DR is performed for domestic hot water, it is also demonstrated that the prioritization of domestic hot water heating can indirectly influence the operation of auxiliary heaters for space-heating, significantly increasing the use of electricity. However, the electricity use is only slightly increased if DR control is only used for space heating.

Suggested Citation

  • Clauß, John & Georges, Laurent, 2019. "Model complexity of heat pump systems to investigate the building energy flexibility and guidelines for model implementation," Applied Energy, Elsevier, vol. 255(C).
  • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s030626191931534x
    DOI: 10.1016/j.apenergy.2019.113847
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191931534X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.113847?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Massimiliano Manfren & Maurizio Sibilla & Lamberto Tronchin, 2021. "Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector," Energies, MDPI, vol. 14(3), pages 1-29, January.
    2. Manfren, Massimiliano & Nastasi, Benedetto & Groppi, Daniele & Astiaso Garcia, Davide, 2020. "Open data and energy analytics - An analysis of essential information for energy system planning, design and operation," Energy, Elsevier, vol. 213(C).
    3. Fredrik Skaug Fadnes & Reyhaneh Banihabib & Mohsen Assadi, 2023. "Using Artificial Neural Networks to Gather Intelligence on a Fully Operational Heat Pump System in an Existing Building Cluster," Energies, MDPI, vol. 16(9), pages 1-33, May.
    4. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    5. Langer, Lissy & Volling, Thomas, 2020. "An optimal home energy management system for modulating heat pumps and photovoltaic systems," Applied Energy, Elsevier, vol. 278(C).
    6. Fabian Wüllhorst & Christian Vering & Laura Maier & Dirk Müller, 2022. "Integration of Back-Up Heaters in Retrofit Heat Pump Systems: Which to Choose, Where to Place, and How to Control?," Energies, MDPI, vol. 15(19), pages 1-22, September.
    7. Olsen, Karen Pardos & Zong, Yi & You, Shi & Bindner, Henrik & Koivisto, Matti & Gea-Bermúdez, Juan, 2020. "Multi-timescale data-driven method identifying flexibility requirements for scenarios with high penetration of renewables," Applied Energy, Elsevier, vol. 264(C).
    8. Lee, Zachary E. & Zhang, K. Max, 2021. "Scalable identification and control of residential heat pumps: A minimal hardware approach," Applied Energy, Elsevier, vol. 286(C).
    9. Xiao, Tianqi & You, Fengqi, 2024. "Physically consistent deep learning-based day-ahead energy dispatching and thermal comfort control for grid-interactive communities," Applied Energy, Elsevier, vol. 353(PB).
    10. Taesub Lim & Yong-Kyu Baik & Daeung Danny Kim, 2020. "Heating Performance Analysis of an Air-to-Water Heat Pump Using Underground Air for Greenhouse Farming," Energies, MDPI, vol. 13(15), pages 1-9, July.
    11. Zhang, Yichi & Johansson, Pär & Kalagasidis, Angela Sasic, 2021. "Techno-economic assessment of thermal energy storage technologies for demand-side management in low-temperature individual heating systems," Energy, Elsevier, vol. 236(C).
    12. Wang, Fei & Li, Wanwan & Ding, Chao & Qu, Zhiguo & Luo, Rongbang & Chen, Xi, 2022. "Optimization on annual energy efficiency of heat pumps based on maximum solving of definition functions with multi constraints," Applied Energy, Elsevier, vol. 321(C).
    13. Piotr Ciuman & Jan Kaczmarczyk & Małgorzata Jastrzębska, 2022. "Simulation Analysis of Heat Pumps Application for the Purposes of the Silesian Botanical Garden Facilities in Poland," Energies, MDPI, vol. 16(1), pages 1-19, December.
    14. Dhirendran Munith Kumar & Pietro Catrini & Antonio Piacentino & Maurizio Cirrincione, 2023. "Integrated Thermodynamic and Control Modeling of an Air-to-Water Heat Pump for Estimating Energy-Saving Potential and Flexibility in the Building Sector," Sustainability, MDPI, vol. 15(11), pages 1-23, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:255:y:2019:i:c:s030626191931534x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.