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Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems in Buildings with Prior Design-Variable Screening

Author

Listed:
  • Paolo Conti

    (Department of Energy, Systems, Technology, and Construction Engineering (DESTEC), University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

  • Giovanni Lutzemberger

    (Department of Energy, Systems, Technology, and Construction Engineering (DESTEC), University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

  • Eva Schito

    (Department of Energy, Systems, Technology, and Construction Engineering (DESTEC), University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

  • Davide Poli

    (Department of Energy, Systems, Technology, and Construction Engineering (DESTEC), University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

  • Daniele Testi

    (Department of Energy, Systems, Technology, and Construction Engineering (DESTEC), University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

Abstract

This work presents an optimization strategy and the cost-optimal design of an off-grid building served by an energy system involving solar technologies, thermal and electrochemical storages. Independently from the multi-objective method (e.g., utility function) and algorithm used (e.g., genetic algorithms), the optimization of this kind of systems is typically characterized by a high-dimensional variables space, computational effort and results uncertainty (e.g., local minimum solutions). Instead of focusing on advanced optimization tools to handle the design problem, the dimension of the full problem has been reduced, only considering the design variables with a high “effect” on the objective functions. An off-grid accommodation building is presented as test case: the original six-variable design problem consisting of about 300,000 possible configurations is reduced to a two-variable problem, after the analysis of 870 Monte Carlo simulations. The new problem includes only 220 possible design alternatives with a clear benefit for the multi-objective optimization algorithm. The energy-economy Pareto frontiers obtained by the original and the reduced problems overlap, showing the validity of the proposed methodology. The No-RES (no renewable energy sources) primary energy consumption can be reduced up to almost 0 kWh/(m 2 yr) and the net present value ( NPV ) after 20 years can reach 70 k€ depending on the number of photovoltaic panels and electrochemical storage size. The reduction of the problem also allows for a plain analysis of the results and the drawing of handy decision charts to help the investor/designer in finding the best design according to the specific investment availability and target performances. The configurations on the Pareto frontier are characterized by a notable electrical overproduction and a ratio between the two main design variables that goes from 4 to 8 h. A sensitivity analysis to the unitary price of the electrochemical storage reveals the robustness of the sizing criterion.

Suggested Citation

  • Paolo Conti & Giovanni Lutzemberger & Eva Schito & Davide Poli & Daniele Testi, 2019. "Multi-Objective Optimization of Off-Grid Hybrid Renewable Energy Systems in Buildings with Prior Design-Variable Screening," Energies, MDPI, vol. 12(15), pages 1-25, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:3026-:d:255140
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    References listed on IDEAS

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    Cited by:

    1. Cao, Yan & Taslimi, Melika S. & Dastjerdi, Sajad Maleki & Ahmadi, Pouria & Ashjaee, Mehdi, 2022. "Design, dynamic simulation, and optimal size selection of a hybrid solar/wind and battery-based system for off-grid energy supply," Renewable Energy, Elsevier, vol. 187(C), pages 1082-1099.
    2. Alessandro Franco & Carlo Bartoli & Paolo Conti & Daniele Testi, 2021. "Optimal Operation of Low-Capacity Heat Pump Systems for Residential Buildings through Thermal Energy Storage," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    3. Kumar Shivam & Jong-Chyuan Tzou & Shang-Chen Wu, 2020. "Multi-Objective Sizing Optimization of a Grid-Connected Solar–Wind Hybrid System Using Climate Classification: A Case Study of Four Locations in Southern Taiwan," Energies, MDPI, vol. 13(10), pages 1-30, May.
    4. Alessandro Franco & Lorenzo Miserocchi & Daniele Testi, 2021. "Energy Intensity Reduction in Large-Scale Non-Residential Buildings by Dynamic Control of HVAC with Heat Pumps," Energies, MDPI, vol. 14(13), pages 1-17, June.
    5. Paolo Conti & Carlo Bartoli & Alessandro Franco & Daniele Testi, 2020. "Experimental Analysis of an Air Heat Pump for Heating Service Using a “Hardware-In-The-Loop” System," Energies, MDPI, vol. 13(17), pages 1-18, September.
    6. Katheryn Donado & Loraine Navarro & Christian G. Quintero M. & Mauricio Pardo, 2019. "HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems," Energies, MDPI, vol. 13(1), pages 1-20, December.
    7. Alaa Farah & Hamdy Hassan & Alaaeldin M. Abdelshafy & Abdelfatah M. Mohamed, 2020. "Optimal Scheduling of Hybrid Multi-Carrier System Feeding Electrical/Thermal Load Based on Particle Swarm Algorithm," Sustainability, MDPI, vol. 12(11), pages 1-21, June.

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