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Method and Case Study of Multiobjective Optimization-Based Energy System Design to Minimize the Primary Energy Use and Initial Investment Cost

Author

Listed:
  • Dong-Seok Kong

    (Department of Architectural Engineering, University of Seoul, Seoul 130-743, Korea)

  • Yong-Sung Jang

    (GS E & C Research Institute, GS Engineering & Construction Corp, Seoul 449-831, Korea)

  • Jung-Ho Huh

    (Department of Architectural Engineering, University of Seoul, Seoul 130-743, Korea)

Abstract

This study aimed to develop a building energy system design method to minimize the initial investment cost and primary energy use. As for the energy system, various combinations were generated depending on the type and capacity of the device used as well as the number of units, energy consumption, and efficiency of the building. Because the design process of energy systems is a critical step in determining the performance of the building throughout the lifecycle, an effective design method is necessary. The proposed method determines the energy system that can minimize the primary energy use and initial investment cost through a multiobjective optimization by calculating the cooling and heating energy consumptions of the building and initial investment cost of the energy system using the load profile by the design-day, and the information in the design phase of the building. This method can support the decision-making process by providing engineers with an alternative proposal for minimizing the initial investment cost and primary energy use by the Pareto analysis after reviewing the design combinations of various energy systems with limited information in the initial design phase. To verify the effectiveness of the methodology, a case study of the two buildings was performed, and the analysis results were compared to the conventional design alternatives. As shown in the case study results, using a method developed in comparison with the conventional result can provide the efficient alternative selection with 80% of initial investment cost and 86% of primary energy use, respectively. The results confirmed that the proposed methodology can provide various optimum results more effectively compared to the conventional design methods.

Suggested Citation

  • Dong-Seok Kong & Yong-Sung Jang & Jung-Ho Huh, 2015. "Method and Case Study of Multiobjective Optimization-Based Energy System Design to Minimize the Primary Energy Use and Initial Investment Cost," Energies, MDPI, vol. 8(6), pages 1-21, June.
  • Handle: RePEc:gam:jeners:v:8:y:2015:i:6:p:6114-6134:d:51476
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    References listed on IDEAS

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    Cited by:

    1. Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2019. "A new comprehensive framework for the multi-objective optimization of building energy design: Harlequin," Applied Energy, Elsevier, vol. 241(C), pages 331-361.
    2. 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.
    3. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    4. Mingcong Liu & Shaobo Yang & Hongyu Li & Jiayi Xu & Xingfei Li, 2019. "Energy Consumption Analysis and Optimization of the Deep-Sea Self-Sustaining Profile Buoy," Energies, MDPI, vol. 12(12), pages 1-26, June.
    5. Ali Sadollah & Mohammad Nasir & Zong Woo Geem, 2020. "Sustainability and Optimization: From Conceptual Fundamentals to Applications," Sustainability, MDPI, vol. 12(5), pages 1-34, March.
    6. Petkov, Ivalin & Gabrielli, Paolo, 2020. "Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems," Applied Energy, Elsevier, vol. 274(C).

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