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

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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