IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i13p4715-d849208.html
   My bibliography  Save this article

Methodology to Determine Energy Efficiency Strategies in Buildings Sited in Tropical Climatic Zones; Case Study, Buildings of the Tertiary Sector in the Dominican Republic

Author

Listed:
  • Joan Manuel Felix Benitez

    (ENEDI Research Group, Energy Engineering Department, University of the Basque Country (UPV/EHU), 48013 Bilbao, Spain
    Directorate of Scientific Research Management, East Central University (UCE), San Pedro de Macorís 21000, Dominican Republic)

  • Luis Alfonso del Portillo-Valdés

    (ENEDI Research Group, Energy Engineering Department, University of the Basque Country (UPV/EHU), 48013 Bilbao, Spain)

  • Rene Pérez

    (Directorate of Scientific Research Management, East Central University (UCE), San Pedro de Macorís 21000, Dominican Republic)

  • David Sosa

    (Directorate of Scientific Research Management, East Central University (UCE), San Pedro de Macorís 21000, Dominican Republic)

Abstract

The application of energy-efficiency strategies in buildings is a hot topic around the world; in some countries, there are regulations with more or less degree of compliance, but in most countries located in the tropical zone, there are no regulations, and it is not easy to transfer regulations of countries outside of tropical zone. For countries located in tropical zones, the implementation of strategies to reduce the heat flow from outside to inside buildings is a key point. As a case study, the Dominican Republic (DR) was chosen, and during 2020, an analysis focusing on buildings of the tertiary level was carried out with the goal of using scientific methodology focused on tropical climates that allows for a significant reduction in energy consumption by implementing Energy Efficiency Strategies (EESs) that are available, with minimal intrusion into the building and low cost. The study includes, as parts of the proposed methodology, the characterization of building parks , including the climatic zonification of the country, an in-depth study of the building typologies in DR, and a massive survey around the country about the technical characteristics of air conditioning units and their usage; the election and characterization of buildings , including simulation and validation throughout the monitoring of eight different buildings; an analysis of the measures of energy efficiency and implementation in the models , including the election of a demonstrative building, the election of the most convenient EESs, modeling of EESs, implementing EESs in the building, monitoring, and validation; and an analysis of the impact of the measures at the region or country level , throughout which important conclusions can be obtained in order to reduce energy consumption in the country. The results show that this methodology is a valid tool for countries situated in tropical areas in order to reduce the energy consumption associated with air conditioning units with low cost, availability, and no intrusive EESs.

Suggested Citation

  • Joan Manuel Felix Benitez & Luis Alfonso del Portillo-Valdés & Rene Pérez & David Sosa, 2022. "Methodology to Determine Energy Efficiency Strategies in Buildings Sited in Tropical Climatic Zones; Case Study, Buildings of the Tertiary Sector in the Dominican Republic," Energies, MDPI, vol. 15(13), pages 1-31, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4715-:d:849208
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/13/4715/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/13/4715/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yao, Jian, 2012. "Energy optimization of building design for different housing units in apartment buildings," Applied Energy, Elsevier, vol. 94(C), pages 330-337.
    2. Liddle, Brantley & Loi, Tian Sheng Allan & Owen, Anthony D. & Tao, Jacqueline, 2020. "Evaluating consumption and cost savings from new air-conditioner purchases: The case of Singapore," Energy Policy, Elsevier, vol. 145(C).
    3. Eguía Oller, Pablo & Alonso Rodríguez, José María & Saavedra González, Ángeles & Arce Fariña, Elena & Granada Álvarez, Enrique, 2018. "Improving the calibration of building simulation with interpolated weather datasets," Renewable Energy, Elsevier, vol. 122(C), pages 608-618.
    4. Wang, Zhe & Hong, Tianzhen & Piette, Mary Ann, 2019. "Data fusion in predicting internal heat gains for office buildings through a deep learning approach," Applied Energy, Elsevier, vol. 240(C), pages 386-398.
    5. Yao, Jian, 2014. "Determining the energy performance of manually controlled solar shades: A stochastic model based co-simulation analysis," Applied Energy, Elsevier, vol. 127(C), pages 64-80.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fabrizio Ascione & Nicola Bianco & Rosa Francesca De Masi & Gerardo Maria Mauro & Giuseppe Peter Vanoli, 2015. "Design of the Building Envelope: A Novel Multi-Objective Approach for the Optimization of Energy Performance and Thermal Comfort," Sustainability, MDPI, vol. 7(8), pages 1-28, August.
    2. Zhouchen Zhang & Jian Yao & Rongyue Zheng, 2024. "Multi-Objective Optimization of Building Energy Saving Based on the Randomness of Energy-Related Occupant Behavior," Sustainability, MDPI, vol. 16(5), pages 1-20, February.
    3. Cristina Carletti & Fabio Sciurpi & Leone Pierangioli, 2014. "The Energy Upgrading of Existing Buildings: Window and Shading Device Typologies for Energy Efficiency Refurbishment," Sustainability, MDPI, vol. 6(8), pages 1-24, August.
    4. Joan Manuel Felix Benitez & Luis Alfonso del Portillo-Valdés & Victor José del Campo Díaz & Koldobika Martin Escudero, 2020. "Simulation and Thermo-Energy Analysis of Building Types in the Dominican Republic to Evaluate and Introduce Energy Efficiency in the Envelope," Energies, MDPI, vol. 13(14), pages 1-14, July.
    5. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    6. Jian Yao, 2014. "A Multi-Objective (Energy, Economic and Environmental Performance) Life Cycle Analysis for Better Building Design," Sustainability, MDPI, vol. 6(2), pages 1-13, January.
    7. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    8. Wei, Ziqing & Zhang, Tingwei & Yue, Bao & Ding, Yunxiao & Xiao, Ran & Wang, Ruzhu & Zhai, Xiaoqiang, 2021. "Prediction of residential district heating load based on machine learning: A case study," Energy, Elsevier, vol. 231(C).
    9. De Boeck, L. & Verbeke, S. & Audenaert, A. & De Mesmaeker, L., 2015. "Improving the energy performance of residential buildings: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 960-975.
    10. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A novel improved model for building energy consumption prediction based on model integration," Applied Energy, Elsevier, vol. 262(C).
    11. Prada, A. & Gasparella, A. & Baggio, P., 2018. "On the performance of meta-models in building design optimization," Applied Energy, Elsevier, vol. 225(C), pages 814-826.
    12. Castaldo, Veronica Lucia & Pisello, Anna Laura & Piselli, Cristina & Fabiani, Claudia & Cotana, Franco & Santamouris, Mattheos, 2018. "How outdoor microclimate mitigation affects building thermal-energy performance: A new design-stage method for energy saving in residential near-zero energy settlements in Italy," Renewable Energy, Elsevier, vol. 127(C), pages 920-935.
    13. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    14. Zhu, Mengshu & Huang, Ying & Wang, Si-Nuo & Zheng, Xinye & Wei, Chu, 2023. "Characteristics and patterns of residential energy consumption for space cooling in China: Evidence from appliance-level data," Energy, Elsevier, vol. 265(C).
    15. Gang, Wenjie & Wang, Jinbo, 2013. "Predictive ANN models of ground heat exchanger for the control of hybrid ground source heat pump systems," Applied Energy, Elsevier, vol. 112(C), pages 1146-1153.
    16. Jian Yao & David Hou Chi Chow & Yu-Wei Chi, 2016. "Impact of Manually Controlled Solar Shades on Indoor Visual Comfort," Sustainability, MDPI, vol. 8(8), pages 1-19, July.
    17. Achini Shanika Weerasinghe & Eziaku Onyeizu Rasheed & James Olabode Bamidele Rotimi, 2023. "Occupants’ Decision-Making of Their Energy Behaviours in Office Environments: A Case of New Zealand," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    18. Linlin Zhao & Zhansheng Liu & Jasper Mbachu, 2019. "Energy Management through Cost Forecasting for Residential Buildings in New Zealand," Energies, MDPI, vol. 12(15), pages 1-24, July.
    19. Tamer, Tolga & Gürsel Dino, Ipek & Meral Akgül, Cagla, 2022. "Data-driven, long-term prediction of building performance under climate change: Building energy demand and BIPV energy generation analysis across Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    20. Abdelhak Kharbouch & Soukayna Berrabah & Mohamed Bakhouya & Jaafar Gaber & Driss El Ouadghiri & Samir Idrissi Kaitouni, 2022. "Experimental and Co-Simulation Performance Evaluation of an Earth-to-Air Heat Exchanger System Integrated into a Smart Building," Energies, MDPI, vol. 15(15), pages 1-22, July.

    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:gam:jeners:v:15:y:2022:i:13:p:4715-:d:849208. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.