IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v353y2024ipas0306261923013703.html
   My bibliography  Save this article

Optimal use of renewable energy technologies during building schematic design phase

Author

Listed:
  • Hassan, Ahmed A.
  • El-Rayes, Khaled

Abstract

An increasing number of federal and state regulations and financial incentive programs have been enacted in recent years to promote renewable energy systems integration in new buildings. This requires designers to analyze the initial and lifecycle costs of feasible renewable energy systems in order to optimize their integration in buildings during all design phases. The goal of this study is to support designers in generating optimal building schematic designs to maximize the integration and generation of onsite renewable energy. To accomplish this goal, this paper presents the development of a novel multi-objective optimization model that can be used during the schematic design phase to identify optimal building design decisions including dimensions, orientation, location on site, solid-to-void ratio, and the type and size of onsite renewable energy systems. The optimization objectives of the developed model focus on maximizing the generation of onsite renewable energy, maximizing savings-to-investment ratio of all integrated renewable energy, and minimizing both construction and renewable energy costs. An application example of optimizing the schematic design of a 6500 m2 building was analyzed to highlight the model original contributions and its novel capabilities. The results of this analysis highlight the original contributions of the developed model and its novel capabilities that can be used to maximize the generation of onsite renewable energy and its savings-to-investment ratio while minimizing building cost by optimizing building schematic design and renewable energy (RE) technology decisions.

Suggested Citation

  • Hassan, Ahmed A. & El-Rayes, Khaled, 2024. "Optimal use of renewable energy technologies during building schematic design phase," Applied Energy, Elsevier, vol. 353(PA).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s0306261923013703
    DOI: 10.1016/j.apenergy.2023.122006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923013703
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.122006?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.

    References listed on IDEAS

    as
    1. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2016. "Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality," Applied Energy, Elsevier, vol. 174(C), pages 37-68.
    2. Ciardiello, Adriana & Rosso, Federica & Dell'Olmo, Jacopo & Ciancio, Virgilio & Ferrero, Marco & Salata, Ferdinando, 2020. "Multi-objective approach to the optimization of shape and envelope in building energy design," Applied Energy, Elsevier, vol. 280(C).
    3. Seung Hyo Baek & Byung Hee Lee, 2019. "Optimal Decision-Making of Renewable Energy Systems in Buildings in the Early Design Stage," Sustainability, MDPI, vol. 11(5), pages 1-19, March.
    4. Rodrigues, Eugénio & Gaspar, Adélio Rodrigues & Gomes, Álvaro, 2014. "Improving thermal performance of automatically generated floor plans using a geometric variable sequential optimization procedure," Applied Energy, Elsevier, vol. 132(C), pages 200-215.
    5. Zhang, Sheng & Huang, Pei & Sun, Yongjun, 2016. "A multi-criterion renewable energy system design optimization for net zero energy buildings under uncertainties," Energy, Elsevier, vol. 94(C), pages 654-665.
    6. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    7. Fabio Magrassi & Adriana Del Borghi & Michela Gallo & Carlo Strazza & Michela Robba, 2016. "Optimal Planning of Sustainable Buildings: Integration of Life Cycle Assessment and Optimization in a Decision Support System (DSS)," Energies, MDPI, vol. 9(7), pages 1-15, June.
    8. Lydia, M. & Kumar, S. Suresh & Selvakumar, A. Immanuel & Prem Kumar, G. Edwin, 2014. "A comprehensive review on wind turbine power curve modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 452-460.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Amin, Amin & Mourshed, Monjur, 2024. "Community stochastic domestic electricity forecasting," Applied Energy, Elsevier, vol. 355(C).
    2. Yu Dong & Haoqi Duan & Xueshun Li & Ruinan Zhang, 2024. "Influence of Different Forms on BIPV Gymnasium Carbon-Saving Potential Based on Energy Consumption and Solar Energy in Multi-Climate Zones," Sustainability, MDPI, vol. 16(4), pages 1-20, February.

    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. Li, Hangxin & Wang, Shengwei, 2019. "Coordinated optimal design of zero/low energy buildings and their energy systems based on multi-stage design optimization," Energy, Elsevier, vol. 189(C).
    2. Yang, Mao & Wang, Da & Xu, Chuanyu & Dai, Bozhi & Ma, Miaomiao & Su, Xin, 2023. "Power transfer characteristics in fluctuation partition algorithm for wind speed and its application to wind power forecasting," Renewable Energy, Elsevier, vol. 211(C), pages 582-594.
    3. Zhang, Sheng & Lin, Zhang & Ai, Zhengtao & Huan, Chao & Cheng, Yong & Wang, Fenghao, 2019. "Multi-criteria performance optimization for operation of stratum ventilation under heating mode," Applied Energy, Elsevier, vol. 239(C), pages 969-980.
    4. Adriana Del Borghi & Thomas Spiegelhalter & Luca Moreschi & Michela Gallo, 2021. "Carbon-Neutral-Campus Building: Design Versus Retrofitting of Two University Zero Energy Buildings in Europe and in the United States," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    5. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    6. Cristina Brunelli & Francesco Castellani & Alberto Garinei & Lorenzo Biondi & Marcello Marconi, 2016. "A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings," Energies, MDPI, vol. 9(11), pages 1-15, November.
    7. Gonzalez, Elena & Stephen, Bruce & Infield, David & Melero, Julio J., 2019. "Using high-frequency SCADA data for wind turbine performance monitoring: A sensitivity study," Renewable Energy, Elsevier, vol. 131(C), pages 841-853.
    8. Huang, Pei & Wu, Hunjun & Huang, Gongsheng & Sun, Yongjun, 2018. "A top-down control method of nZEBs for performance optimization at nZEB-cluster-level," Energy, Elsevier, vol. 159(C), pages 891-904.
    9. D'Agostino, D. & Minelli, F. & D'Urso, M. & Minichiello, F., 2022. "Fixed and tracking PV systems for Net Zero Energy Buildings: Comparison between yearly and monthly energy balance," Renewable Energy, Elsevier, vol. 195(C), pages 809-824.
    10. Juan Francisco Fernández Rodríguez, 2023. "Sustainable Design Protocol in BIM Environments: Case Study of 3D Virtual Models of a Building in Seville (Spain) Based on BREEAM Method," Sustainability, MDPI, vol. 15(7), pages 1-29, March.
    11. Binju P Raj & Chandan Swaroop Meena & Nehul Agarwal & Lohit Saini & Shabir Hussain Khahro & Umashankar Subramaniam & Aritra Ghosh, 2021. "A Review on Numerical Approach to Achieve Building Energy Efficiency for Energy, Economy and Environment (3E) Benefit," Energies, MDPI, vol. 14(15), pages 1-26, July.
    12. Zhao, Yongning & Ye, Lin & Li, Zhi & Song, Xuri & Lang, Yansheng & Su, Jian, 2016. "A novel bidirectional mechanism based on time series model for wind power forecasting," Applied Energy, Elsevier, vol. 177(C), pages 793-803.
    13. Chai, Jiale & Huang, Pei & Sun, Yongjun, 2019. "Investigations of climate change impacts on net-zero energy building lifecycle performance in typical Chinese climate regions," Energy, Elsevier, vol. 185(C), pages 176-189.
    14. Álvarez-García, Francisco J. & Fresno-Schmolk, Gonzalo & OrtizBevia, María J. & Cabos, William & RuizdeElvira, Antonio, 2020. "Reduction of aggregate wind power variability using Empirical Orthogonal Teleconnections: An application in the Iberian Peninsula," Renewable Energy, Elsevier, vol. 159(C), pages 151-161.
    15. Mohamed Hamdy & Gerardo Maria Mauro, 2017. "Multi-Objective Optimization of Building Energy Design to Reconcile Collective and Private Perspectives: CO 2 -eq vs. Discounted Payback Time," Energies, MDPI, vol. 10(7), pages 1-26, July.
    16. Harkouss, Fatima & Fardoun, Farouk & Biwole, Pascal Henry, 2018. "Passive design optimization of low energy buildings in different climates," Energy, Elsevier, vol. 165(PA), pages 591-613.
    17. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    18. Filippos Lygerakis & Nikos Kampelis & Dionysia Kolokotsa, 2022. "Knowledge Graphs’ Ontologies and Applications for Energy Efficiency in Buildings: A Review," Energies, MDPI, vol. 15(20), pages 1-32, October.
    19. Pablo Fernández-Bustamante & Oscar Barambones & Isidro Calvo & Cristian Napole & Mohamed Derbeli, 2021. "Provision of Frequency Response from Wind Farms: A Review," Energies, MDPI, vol. 14(20), pages 1-24, October.
    20. 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.

    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:353:y:2024:i:pa:s0306261923013703. 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: 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.