IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2016i10p849-d81054.html
   My bibliography  Save this article

Study on the Optimum Design Method of Heat Source Systems with Heat Storage Using a Genetic Algorithm

Author

Listed:
  • Min Gyung Yu

    (Department of Architectural Engineering, Pusan National University, 2 Busandaehak-ro 63, Geomjeong-gu, Busan 609-735, Korea)

  • Yujin Nam

    (Department of Architectural Engineering, Pusan National University, 2 Busandaehak-ro 63, Geomjeong-gu, Busan 609-735, Korea)

Abstract

Recently, a heat source system utilizing a heat storage tank for energy savings in buildings was designed. A heat storage tank is an effective system for solving the qualitative and quantitative differences in the required building energy. On the other hand, the existing design process of a heat storage system is difficult to determine if the air-conditioning time is unclear, and the design in a real-working level is too inaccurate, causing oversizing and a high initial investment cost. This results in inefficient operation despite the introduction of an efficient system. Therefore, this study proposes an optimal design method of a heat source system using a thermal storage tank. To demonstrate the usefulness of the proposed design method, feasibility studies were conducted with the existing system designs. As a result, the optimal solution could reduce the initial cost by approximately 25.6% when following the conventional design process and it was approximately 40% lower than the real-working method. In conclusion, the conventional designs are inefficiently over-designed and the optimal design solution is superior. In this regard, the suggested optimal design method is efficient when designing a heat source system using a thermal storage tank.

Suggested Citation

  • Min Gyung Yu & Yujin Nam, 2016. "Study on the Optimum Design Method of Heat Source Systems with Heat Storage Using a Genetic Algorithm," Energies, MDPI, vol. 9(10), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:10:p:849-:d:81054
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/10/849/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/9/10/849/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hafez, Omar & Bhattacharya, Kankar, 2012. "Optimal planning and design of a renewable energy based supply system for microgrids," Renewable Energy, Elsevier, vol. 45(C), pages 7-15.
    2. Shirazi, Ali & Najafi, Behzad & Aminyavari, Mehdi & Rinaldi, Fabio & Taylor, Robert A., 2014. "Thermal–economic–environmental analysis and multi-objective optimization of an ice thermal energy storage system for gas turbine cycle inlet air cooling," Energy, Elsevier, vol. 69(C), pages 212-226.
    3. Min Gyung Yu & Yujin Nam & Youngdong Yu & Janghoo Seo, 2016. "Study on the System Design of a Solar Assisted Ground Heat Pump System Using Dynamic Simulation," Energies, MDPI, vol. 9(4), pages 1-16, April.
    4. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2016. "Multi-objective optimization of a distributed energy network integrated with heating interchange," Energy, Elsevier, vol. 109(C), pages 353-364.
    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. Edorta Carrascal-Lekunberri & Izaskun Garrido & Bram Van der Heijde & Aitor J. Garrido & José María Sala & Lieve Helsen, 2017. "Energy Conservation in an Office Building Using an Enhanced Blind System Control," Energies, MDPI, vol. 10(2), pages 1-23, 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. Liu, Liuchen & Cui, Guomin & Chen, Jiaxing & Huang, Xiaohuang & Li, Di, 2022. "Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification," Energy, Elsevier, vol. 245(C).
    2. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    3. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    4. Bahramara, S. & Moghaddam, M. Parsa & Haghifam, M.R., 2016. "Optimal planning of hybrid renewable energy systems using HOMER: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 609-620.
    5. Sen, Rohit & Bhattacharyya, Subhes C., 2014. "Off-grid electricity generation with renewable energy technologies in India: An application of HOMER," Renewable Energy, Elsevier, vol. 62(C), pages 388-398.
    6. Xiaohua Song & Yun Long & Zhongfu Tan & Xubei Zhang & Leming Li, 2016. "The Optimization of Distributed Photovoltaic Comprehensive Efficiency Based on the Construction of Regional Integrated Energy Management System in China," Sustainability, MDPI, vol. 8(11), pages 1-19, November.
    7. Upadhyay, Subho & Sharma, M.P., 2016. "Selection of a suitable energy management strategy for a hybrid energy system in a remote rural area of India," Energy, Elsevier, vol. 94(C), pages 352-366.
    8. Batas Bjelic, Ilija & Ciric, Rade M., 2014. "Optimal distributed generation planning at a local level – A review of Serbian renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 79-86.
    9. Zheng, Shuhong & Yang, Juan & Yu, Shiwei, 2021. "How renewable energy technological innovation promotes renewable power generation: Evidence from China's provincial panel data," Renewable Energy, Elsevier, vol. 177(C), pages 1394-1407.
    10. Zhang, Haitian & Feng, Xiao & Wang, Yufei, 2018. "Comparison and evaluation of air cooling and water cooling in resource consumption and economic performance," Energy, Elsevier, vol. 154(C), pages 157-167.
    11. Maria Psillaki & Nikolaos Apostolopoulos & Ilias Makris & Panagiotis Liargovas & Sotiris Apostolopoulos & Panos Dimitrakopoulos & George Sklias, 2023. "Hospitals’ Energy Efficiency in the Perspective of Saving Resources and Providing Quality Services through Technological Options: A Systematic Literature Review," Energies, MDPI, vol. 16(2), pages 1-21, January.
    12. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    13. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    14. Li, Tianxiao & Li, Zheng & Li, Weiqi, 2020. "Scenarios analysis on the cross-region integrating of renewable power based on a long-period cost-optimization power planning model," Renewable Energy, Elsevier, vol. 156(C), pages 851-863.
    15. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2016. "Optimal design and techno-economic analysis of an autonomous small isolated microgrid aiming at high RES penetration," Energy, Elsevier, vol. 116(P1), pages 364-379.
    16. Liu, Zhiqiang & Cui, Yanping & Wang, Jiaqiang & Yue, Chang & Agbodjan, Yawovi Souley & Yang, Yu, 2022. "Multi-objective optimization of multi-energy complementary integrated energy systems considering load prediction and renewable energy production uncertainties," Energy, Elsevier, vol. 254(PC).
    17. Adil, Ali M. & Ko, Yekang, 2016. "Socio-technical evolution of Decentralized Energy Systems: A critical review and implications for urban planning and policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1025-1037.
    18. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    19. Shirazi, Ali & Taylor, Robert A. & White, Stephen D. & Morrison, Graham L., 2016. "Transient simulation and parametric study of solar-assisted heating and cooling absorption systems: An energetic, economic and environmental (3E) assessment," Renewable Energy, Elsevier, vol. 86(C), pages 955-971.
    20. Li, Bo & Li, Xu & Su, Qingyu, 2022. "A system and game strategy for the isolated island electric-gas deeply coupled energy network," Applied Energy, Elsevier, vol. 306(PA).

    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:10:p:849-:d:81054. 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.