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Development of Energy Demand Profile Based on Non-Historical and Non-Energy Variables: A Headquarters’ Offices Case Study

Author

Listed:
  • Juliana Cruz

    (CIRCE—Technology Centre, Av. Ranillas 3D 1A, 50018 Zaragoza, Spain)

  • Isabel Lasierra

    (CIRCE—Technology Centre, Av. Ranillas 3D 1A, 50018 Zaragoza, Spain)

  • Yassine Rqiq

    (CIRCE—Technology Centre, Av. Ranillas 3D 1A, 50018 Zaragoza, Spain)

  • Víctor Ballestín

    (CIRCE—Technology Centre, Av. Ranillas 3D 1A, 50018 Zaragoza, Spain)

Abstract

Under the Positive Energy Districts framework, cities authorities must be informed of the energy demand of districts to design tailor-made policies and strategies to promote the deployment of energy efficiency, sharing and transition actions. However, the diverse data sources and long procedures to collect data because of privacy permissions may result in a slow-down of the development of these roadmaps. To overcome these challenges, this paper is the outcome of the methodology developed under the UP2030 Project designed to estimate the energy demand and energy profile consumptions within urban areas to contribute to the stakeholders involved in decision making processes to inform them about the savings potential related with the use of energy in geographically delimitated areas. The methodology was validated in CIRCE’s headquarters, where the yearly energy estimation consumption is about 98% of the real energy consumed. The main finding of this study is obtaining a model that can estimate the energy usage for occupants’ comfort with minimal data required from the citizens’ side, which will allow stakeholders to consider global energy estimations at the district level in a fast and reliable way to design strategies in a timely manner as required by the energy transition and efficiency standards proposed by the European Union.

Suggested Citation

  • Juliana Cruz & Isabel Lasierra & Yassine Rqiq & Víctor Ballestín, 2025. "Development of Energy Demand Profile Based on Non-Historical and Non-Energy Variables: A Headquarters’ Offices Case Study," Energies, MDPI, vol. 18(3), pages 1-18, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:3:p:605-:d:1578761
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    References listed on IDEAS

    as
    1. Johari, F. & Peronato, G. & Sadeghian, P. & Zhao, X. & Widén, J., 2020. "Urban building energy modeling: State of the art and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    2. Leprince, Julien & Schledorn, Amos & Guericke, Daniela & Dominkovic, Dominik Franjo & Madsen, Henrik & Zeiler, Wim, 2023. "Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities," Applied Energy, Elsevier, vol. 348(C).
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