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A physically-based model for simulating inverter type air conditioners/heat pumps


  • Gomes, A.
  • Antunes, C. Henggeler
  • Martinho, J.


The engagement in demand response activities is increasingly becoming more attractive for several entities in the power systems sector. In general terms, the main goal of such activities is to change the demand level and patterns by implementing management actions over groups of loads to minimize peak demand or electricity bill, maximize profits or increase the systems reliability, among other objectives. However, in order to avoid potential undesirable impacts it is necessary to anticipate and adequately assess the changes in demand originated by such actions. This assessment requires adequate simulation tools and models with the ability to simulate demand management actions. This work presents a physically-based model that allows reproducing the behavior of an inverter type heat pump. This model can be used to simulate the demand of an individual device or several devices. Besides, it allows simulating and assessing the impacts of implementing demand management actions over this type of end-use loads. The results show that the model can effectively reproduce the demand of this type of equipment, becoming a useful tool for the prior assessment and even the design and selection of demand response actions to be applied over these loads.

Suggested Citation

  • Gomes, A. & Antunes, C. Henggeler & Martinho, J., 2013. "A physically-based model for simulating inverter type air conditioners/heat pumps," Energy, Elsevier, vol. 50(C), pages 110-119.
  • Handle: RePEc:eee:energy:v:50:y:2013:i:c:p:110-119
    DOI: 10.1016/

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    References listed on IDEAS

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    Cited by:

    1. Ana García-Garre & Antonio Gabaldón & Carlos Álvarez-Bel & María Del Carmen Ruiz-Abellón & Antonio Guillamón, 2018. "Integration of Demand Response and Photovoltaic Resources in Residential Segments," Sustainability, MDPI, Open Access Journal, vol. 10(9), pages 1-31, August.
    2. Carsten Palkowski & Andreas Zottl & Ivan Malenkovic & Anne Simo, 2019. "Fixing Efficiency Values by Unfixing Compressor Speed: Dynamic Test Method for Heat Pumps," Energies, MDPI, Open Access Journal, vol. 12(6), pages 1-16, March.
    3. Ahn, Jae Hwan & Lee, Joo Seong & Baek, Changhyun & Kim, Yongchan, 2016. "Performance improvement of a dehumidifying heat pump using an additional waste heat source in electric vehicles with low occupancy," Energy, Elsevier, vol. 115(P1), pages 67-75.
    4. Soares, Ana & Gomes, Álvaro & Antunes, Carlos Henggeler, 2014. "Categorization of residential electricity consumption as a basis for the assessment of the impacts of demand response actions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 490-503.
    5. Antonio Gabaldón & Carlos Álvarez & María Del Carmen Ruiz-Abellón & Antonio Guillamón & Sergio Valero-Verdú & Roque Molina & Ana García-Garre, 2018. "Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and Demand Response," Sustainability, MDPI, Open Access Journal, vol. 10(2), pages 1-27, February.
    6. Gonçalves, Ivo & Gomes, Álvaro & Henggeler Antunes, Carlos, 2019. "Optimizing the management of smart home energy resources under different power cost scenarios," Applied Energy, Elsevier, vol. 242(C), pages 351-363.
    7. Xie, Jiantong & Pan, Yiqun & Jia, Wenqi & Xu, Lei & Huang, Zhizhong, 2019. "Energy-consumption simulation of a distributed air-conditioning system integrated with occupant behavior," Applied Energy, Elsevier, vol. 256(C).


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