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Flexibility Assessment of Multi-Energy Residential and Commercial Buildings

Author

Listed:
  • António Coelho

    (Centre for Power and Energy Systems, INESC TEC, 4200-465 Porto, Portugal)

  • Filipe Soares

    (Centre for Power and Energy Systems, INESC TEC, 4200-465 Porto, Portugal)

  • João Peças Lopes

    (FIEEE, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal)

Abstract

With the growing concern about decreasing CO 2 emissions, renewable energy sources are being vastly integrated in the energy systems worldwide. This will bring new challenges to the network operators, which will need to find sources of flexibility to cope with the variable-output nature of these technologies. Demand response and multi-energy systems are being widely studied and considered as a promising solution to mitigate possible problems that may occur in the energy systems due to the large-scale integration of renewables. In this work, an optimal model to manage the resources and loads within residential and commercial buildings was developed, considering consumers preferences, electrical network restrictions and CO 2 emissions. The flexibility that these buildings can provide was analyzed and quantified. Additionally, it was shown how this model can be used to solve technical problems in electrical networks, comparing the performance of two scenarios of flexibility provision: flexibility obtained only from electrical loads vs. flexibility obtained from multi-energy loads. It was proved that multi-energy systems bring more options of flexibility, as they can rely on non-electrical resources to supply the same energy needs and thus relieve the electrical network. It was also found that commercial buildings can offer more flexibility during the day, while residential buildings can offer more during the morning and evening. Nonetheless, Multi-Energy System (MES) buildings end up having higher CO 2 emissions due to a higher consumption of natural gas.

Suggested Citation

  • António Coelho & Filipe Soares & João Peças Lopes, 2020. "Flexibility Assessment of Multi-Energy Residential and Commercial Buildings," Energies, MDPI, vol. 13(11), pages 1-35, May.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2704-:d:364257
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    References listed on IDEAS

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    1. Mukherjee, Ushnik & Walker, Sean & Maroufmashat, Azadeh & Fowler, Michael & Elkamel, Ali, 2017. "Development of a pricing mechanism for valuing ancillary, transportation and environmental services offered by a power to gas energy system," Energy, Elsevier, vol. 128(C), pages 447-462.
    2. Iria, José & Soares, Filipe & Matos, Manuel, 2019. "Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets," Applied Energy, Elsevier, vol. 238(C), pages 1361-1372.
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