IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2016i3p181-d65668.html
   My bibliography  Save this article

A Study on Development of a Cost Optimal and Energy Saving Building Model: Focused on Industrial Building

Author

Listed:
  • Hye Yeon Kim

    (Department of Architecture, Chung Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 138240, Korea
    These authors contributed equally to this work.)

  • Hae Jin Kang

    (Sustainable Design Team, Samoo Architects & Engineers, 295 Olympic-ro, Songpa-gu, Seoul 138240, Korea
    These authors contributed equally to this work.)

Abstract

This study suggests an optimization method for the life cycle cost (LCC) in an economic feasibility analysis when applying energy saving techniques in the early design stage of a building. Literature and previous studies were reviewed to select appropriate optimization and LCC analysis techniques. The energy simulation (Energy Plus) and computational program (MATLAB) were linked to provide an automated optimization process. From the results, it is suggested that this process could outline the cost optimization model with which it is possible to minimize the LCC. To aid in understanding the model, a case study on an industrial building was performed to outline the operations of the cost optimization model including energy savings. An energy optimization model was also presented to illustrate the need for the cost optimization model.

Suggested Citation

  • Hye Yeon Kim & Hae Jin Kang, 2016. "A Study on Development of a Cost Optimal and Energy Saving Building Model: Focused on Industrial Building," Energies, MDPI, vol. 9(3), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:181-:d:65668
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/3/181/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/9/3/181/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    2. Wang, Xiaoxin & Kendrick, Christopher & Ogden, Raymond & Walliman, Nicholas & Baiche, Bousmaha, 2013. "A case study on energy consumption and overheating for a UK industrial building with rooflights," Applied Energy, Elsevier, vol. 104(C), pages 337-344.
    3. Li, Danny H.W & Lam, Joseph C, 2000. "Measurements of solar radiation and illuminance on vertical surfaces and daylighting implications," Renewable Energy, Elsevier, vol. 20(4), pages 389-404.
    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. Danish Mahmood & Nadeem Javaid & Sheraz Ahmed & Imran Ahmed & Iftikhar Azim Niaz & Wadood Abdul & Sanaa Ghouzali, 2017. "Orchestrating an Effective Formulation to Investigate the Impact of EMSs (Energy Management Systems) for Residential Units Prior to Installation," Energies, MDPI, vol. 10(3), pages 1-25, March.
    2. Xue, Jian & Zhang, Wenjing & Zhao, Laijun & Zhu, Di & Li, Lei & Gong, Ruifeng, 2022. "A cooperative inter-provincial model for energy conservation that accounts for employment and social energy costs," Energy, Elsevier, vol. 239(PB).
    3. Joanna Ferdyn-Grygierek & Krzysztof Grygierek, 2017. "Multi-Variable Optimization of Building Thermal Design Using Genetic Algorithms," Energies, MDPI, vol. 10(10), pages 1-20, October.

    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. Pin Li & Jinsuo Zhang, 2019. "Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods," Energies, MDPI, vol. 12(2), pages 1-30, January.
    2. P. Giovani Palafox-Alcantar & Dexter V. L. Hunt & Chris D. F. Rogers, 2020. "A Hybrid Methodology to Study Stakeholder Cooperation in Circular Economy Waste Management of Cities," Energies, MDPI, vol. 13(7), pages 1-30, April.
    3. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    4. Michael O. Ukoba & Ogheneruona E. Diemuodeke & Mohammed Alghassab & Henry I. Njoku & Muhammad Imran & Zafar A. Khan, 2020. "Composite Multi-Criteria Decision Analysis for Optimization of Hybrid Renewable Energy Systems for Geopolitical Zones in Nigeria," Sustainability, MDPI, vol. 12(14), pages 1-27, July.
    5. Mostafa Shaaban & Jürgen Scheffran & Jürgen Böhner & Mohamed S. Elsobki, 2018. "Sustainability Assessment of Electricity Generation Technologies in Egypt Using Multi-Criteria Decision Analysis," Energies, MDPI, vol. 11(5), pages 1-25, May.
    6. Hong, Sanghyun & Kim, Eunsung & Jeong, Saerok, 2023. "Evaluating the sustainability of the hydrogen economy using multi-criteria decision-making analysis in Korea," Renewable Energy, Elsevier, vol. 204(C), pages 485-492.
    7. Hong, Sanghyun & Bradshaw, Corey J.A. & Brook, Barry W., 2014. "Nuclear power can reduce emissions and maintain a strong economy: Rating Australia’s optimal future electricity-generation mix by technologies and policies," Applied Energy, Elsevier, vol. 136(C), pages 712-725.
    8. Zheng Yuan & Baohua Wen & Cheng He & Jin Zhou & Zhonghua Zhou & Feng Xu, 2022. "Application of Multi-Criteria Decision-Making Analysis to Rural Spatial Sustainability Evaluation: A Systematic Review," IJERPH, MDPI, vol. 19(11), pages 1-31, May.
    9. Duck Bong Kim, 2019. "An approach for composing predictive models from disparate knowledge sources in smart manufacturing environments," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1999-2012, April.
    10. Cowan, Kelly & Daim, Tugrul & Anderson, Tim, 2010. "Exploring the impact of technology development and adoption for sustainable hydroelectric power and storage technologies in the Pacific Northwest United States," Energy, Elsevier, vol. 35(12), pages 4771-4779.
    11. Alkan, Ömer & Albayrak, Özlem Karadağ, 2020. "Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA," Renewable Energy, Elsevier, vol. 162(C), pages 712-726.
    12. Haddad, Brahim & Liazid, Abdelkrim & Ferreira, Paula, 2017. "A multi-criteria approach to rank renewables for the Algerian electricity system," Renewable Energy, Elsevier, vol. 107(C), pages 462-472.
    13. Ewa Roszkowska & Bartłomiej Jefmański, 2021. "Interval-Valued Intuitionistic Fuzzy Synthetic Measure (I-VIFSM) Based on Hellwig’s Approach in the Analysis of Survey Data," Mathematics, MDPI, vol. 9(3), pages 1-17, January.
    14. Manley, Dawn K. & Hines, Valerie A. & Jordan, Matthew W. & Stoltz, Ronald E., 2013. "A survey of energy policy priorities in the United States: Energy supply security, economics, and the environment," Energy Policy, Elsevier, vol. 60(C), pages 687-696.
    15. Venmans, Frank, 2012. "A literature-based multi-criteria evaluation of the EU ETS," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5493-5510.
    16. Stanislav Shmelev & Harrison Roger Brook, 2021. "Macro Sustainability across Countries: Key Sector Environmentally Extended Input-Output Analysis," Sustainability, MDPI, vol. 13(21), pages 1-46, October.
    17. Dianfa Wu & Zhiping Yang & Ningling Wang & Chengzhou Li & Yongping Yang, 2018. "An Integrated Multi-Criteria Decision Making Model and AHP Weighting Uncertainty Analysis for Sustainability Assessment of Coal-Fired Power Units," Sustainability, MDPI, vol. 10(6), pages 1-27, May.
    18. Ellen De Schepper & Steven Van Passel & Sebastien Lizin & Thomas Vincent & Benjamin Martin & Xavier Gandibleux, 2016. "Economic and environmental multi-objective optimisation to evaluate the impact of Belgian policy on solar power and electric vehicles," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(1), pages 1-27, March.
    19. Li, Danny H.W. & Lou, Siwei, 2018. "Review of solar irradiance and daylight illuminance modeling and sky classification," Renewable Energy, Elsevier, vol. 126(C), pages 445-453.
    20. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).

    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:9:y:2016:i:3:p:181-:d:65668. 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.