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An integrated multi-objective optimization model for determining the optimal solution in implementing the rooftop photovoltaic system

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  • Koo, Choongwan
  • Hong, Taehoon
  • Lee, Minhyun
  • Kim, Jimin

Abstract

The photovoltaic (PV) system has been highlighted as a sustainable clean energy source. To successfully implement the PV system in a real project, several impact factors should be simultaneously considered. This study aimed to develop an integrated multi-objective optimization (iMOO) model for determining the optimal solution in implementing the rooftop PV system. This study was conducted in six steps: (i) establishment of database; (ii) generation of the installation scenarios in the rooftop PV system; (iii) energy simulation using the software program ׳RETScreen׳; (iv) economic and environmental assessment from the life cycle perspective; (v) establishment of the iMOO process using a genetic algorithm; and (vi) systemization of the iMOO model using a Microsoft-Excel-based VBA. Two criteria were used to assess the robustness and reliability of the developed model. In terms of effectiveness, the optimal solution was determined from a total of 399,883,120 (=91×49×19×80×59) possible scenarios by comprehensively considering various factors. In terms of efficiency, it was concluded that the time required for determining the optimal solution was 150s. The developed model makes it possible for final decision-maker such as construction managers or contractors to determine the optimal solution in implementing the rooftop PV system in the early design phase.

Suggested Citation

  • Koo, Choongwan & Hong, Taehoon & Lee, Minhyun & Kim, Jimin, 2016. "An integrated multi-objective optimization model for determining the optimal solution in implementing the rooftop photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 822-837.
    • Handle: RePEc:eee:rensus:v:57:y:2016:i:c:p:822-837
    DOI: 10.1016/j.rser.2015.12.205
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    Citations

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    Cited by:

    1. Jeong, Kwangbok & Hong, Taehoon & Kim, Jimin & Cho, Kyuman, 2019. "Development of a multi-objective optimization model for determining the optimal CO2 emissions reduction strategies for a multi-family housing complex," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 118-131.
    2. Hong, Taehoon & Koo, Choongwan & Oh, Jeongyoon & Jeong, Kwangbok, 2017. "Nonlinearity analysis of the shading effect on the technical–economic performance of the building-integrated photovoltaic blind," Applied Energy, Elsevier, vol. 194(C), pages 467-480.
    3. Koo, Choongwan & Hong, Taehoon & Jeong, Kwangbok & Ban, Cheolwoo & Oh, Jeongyoon, 2017. "Development of the smart photovoltaic system blind and its impact on net-zero energy solar buildings using technical-economic-political analyses," Energy, Elsevier, vol. 124(C), pages 382-396.
    4. Re Cecconi, F. & Moretti, N. & Tagliabue, L.C., 2019. "Application of artificial neutral network and geographic information system to evaluate retrofit potential in public school buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 266-277.
    5. Ganjehkaviri, A. & Mohd Jaafar, M.N. & Hosseini, S.E. & Barzegaravval, H., 2017. "Genetic algorithm for optimization of energy systems: Solution uniqueness, accuracy, Pareto convergence and dimension reduction," Energy, Elsevier, vol. 119(C), pages 167-177.
    6. Indre Siksnelyte & Edmundas Kazimieras Zavadskas & Dalia Streimikiene & Deepak Sharma, 2018. "An Overview of Multi-Criteria Decision-Making Methods in Dealing with Sustainable Energy Development Issues," Energies, MDPI, vol. 11(10), pages 1-21, October.
    7. Jeongyoon Oh & Taehoon Hong & Hakpyeong Kim & Jongbaek An & Kwangbok Jeong & Choongwan Koo, 2017. "Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle," Sustainability, MDPI, vol. 9(12), pages 1-52, December.
    8. Cucchiella, Federica & D’Adamo, Idiano & Gastaldi, Massimo & Koh, SC Lenny & Rosa, Paolo, 2017. "A comparison of environmental and energetic performance of European countries: A sustainability index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 401-413.
    9. Kim, Hakpyeong & Hong, Taehoon, 2020. "Determining the optimal set-point temperature considering both labor productivity and energy saving in an office building," Applied Energy, Elsevier, vol. 276(C).
    10. Koo, Choongwan & Hong, Taehoon & Oh, Jeongyoon & Choi, Jun-Ki, 2018. "Improving the prediction performance of the finite element model for estimating the technical performance of the distributed generation of solar power system in a building façade," Applied Energy, Elsevier, vol. 215(C), pages 41-53.
    11. Ramshani, Mohammad & Khojandi, Anahita & Li, Xueping & Omitaomu, Olufemi, 2020. "Optimal planning of the joint placement of photovoltaic panels and green roofs under climate change uncertainty," Omega, Elsevier, vol. 90(C).
    12. Oh, Jeongyoon & Koo, Choongwan & Hong, Taehoon & Cha, Seung Hyun, 2018. "An integrated model for estimating the techno-economic performance of the distributed solar generation system on building façades: Focused on energy demand and supply," Applied Energy, Elsevier, vol. 228(C), pages 1071-1090.
    13. Lee, Minhyun & Hong, Taehoon & Koo, Choongwan, 2016. "An economic impact analysis of state solar incentives for improving financial performance of residential solar photovoltaic systems in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 590-607.
    14. Lee, Minhyun & Hong, Taehoon & Jeong, Jaewook & Jeong, Kwangbok, 2018. "Development of a rooftop solar photovoltaic rating system considering the technical and economic suitability criteria at the building level," Energy, Elsevier, vol. 160(C), pages 213-224.
    15. Kim, Jimin & Hong, Taehoon & Jeong, Jaemin & Lee, Myeonghwi & Lee, Minhyun & Jeong, Kwangbok & Koo, Choongwan & Jeong, Jaewook, 2017. "Establishment of an optimal occupant behavior considering the energy consumption and indoor environmental quality by region," Applied Energy, Elsevier, vol. 204(C), pages 1431-1443.
    16. Chi, Fang'ai & Xu, Ying, 2022. "Building performance optimization for university dormitory through integration of digital gene map into multi-objective genetic algorithm," Applied Energy, Elsevier, vol. 307(C).
    17. Cristofari, C. & Carutasiu, M.B. & Canaletti, J.L. & Norvaišienė, R. & Motte, F. & Notton, G., 2019. "Building integration of solar thermal systems-example of a refurbishment of a church rectory," Renewable Energy, Elsevier, vol. 137(C), pages 67-81.
    18. Park, Hyo Seon & Koo, Choongwan & Hong, Taehoon & Oh, Jeongyoon & Jeong, Kwangbok, 2016. "A finite element model for estimating the techno-economic performance of the building-integrated photovoltaic blind," Applied Energy, Elsevier, vol. 179(C), pages 211-227.
    19. Every, Jeremy & Li, Li & Dorrell, David G., 2017. "Leveraging smart meter data for economic optimization of residential photovoltaics under existing tariff structures and incentive schemes," Applied Energy, Elsevier, vol. 201(C), pages 158-173.
    20. Koo, Choongwan & Si, Ke & Li, Wenzhuo & Lee, JeeHee, 2022. "Integrated approach to evaluating the impact of feed-in tariffs on the life cycle economic performance of photovoltaic systems in China: A case study of educational facilities," Energy, Elsevier, vol. 254(PB).
    21. Hong, Taehoon & Kim, Jimin & Lee, Minhyun, 2019. "A multi-objective optimization model for determining the building design and occupant behaviors based on energy, economic, and environmental performance," Energy, Elsevier, vol. 174(C), pages 823-834.
    22. Tingting Hou & Rengcun Fang & Jinrui Tang & Ganheng Ge & Dongjun Yang & Jianchao Liu & Wei Zhang, 2021. "A Novel Short-Term Residential Electric Load Forecasting Method Based on Adaptive Load Aggregation and Deep Learning Algorithms," Energies, MDPI, vol. 14(22), pages 1-21, November.
    23. Lee, Minhyun & Hong, Taehoon & Yoo, Hyunji & Koo, Choongwan & Kim, Jimin & Jeong, Kwangbok & Jeong, Jaewook & Ji, Changyoon, 2017. "Establishment of a base price for the Solar Renewable Energy Credit (SREC) from the perspective of residents and state governments in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1066-1080.
    24. Salata, Ferdinando & Ciancio, Virgilio & Dell'Olmo, Jacopo & Golasi, Iacopo & Palusci, Olga & Coppi, Massimo, 2020. "Effects of local conditions on the multi-variable and multi-objective energy optimization of residential buildings using genetic algorithms," Applied Energy, Elsevier, vol. 260(C).

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