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A New Modeling Approach for Low-Carbon District Energy System Planning

Author

Listed:
  • Abolfazl Rezaei

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Bahador Samadzadegan

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Hadise Rasoulian

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Saeed Ranjbar

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Soroush Samareh Abolhassani

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Azin Sanei

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Ursula Eicker

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

Abstract

Designing district-scale energy systems with renewable energy sources is still a challenge, as it involves modeling of multiple loads and many options to combine energy system components. In the current study, two different energy system scenarios for a district in Montreal/Canada are compared to choose the most cost-effective and energy-efficient energy system scenario for the studied area. In the first scenario, a decentral energy system comprised of ground-source heat pumps provides heating and cooling for each building, while, in the second scenario, a district heating and cooling system with a central heat pump is designed. Firstly, heating and cooling demand are calculated in a completely automated process using an Automatic Urban Building Energy Modeling System approach (AUBEM). Then, the Integrated Simulation Environment Language (INSEL) is used to prepare a model for the energy system. The proposed model provides heat pump capacity and the number of required heat pumps (HP), the number of photovoltaic (PV) panels, and AC electricity generation potential using PV. After designing the energy systems, the piping system, heat losses, and temperature distribution of the centralized scenario are calculated using a MATLAB code. Finally, two scenarios are assessed economically using the Levelized Cost of Energy (LCOE) method. The results show that the central scenario’s total HP electricity consumption is 17% lower than that of the decentral systems and requires less heat pump capacity than the decentral scenario. The LCOE of both scenarios varies from 0.04 to 0.07 CAD/kWh, which is cheaper than the electricity cost in Quebec (0.08 CAD/kWh). A comparison between both scenarios shows that the centralized energy system is cost-beneficial for all buildings and, after applying the discounts, the LCOE of this scenario decreases to 0.04 CAD/kWh.

Suggested Citation

  • Abolfazl Rezaei & Bahador Samadzadegan & Hadise Rasoulian & Saeed Ranjbar & Soroush Samareh Abolhassani & Azin Sanei & Ursula Eicker, 2021. "A New Modeling Approach for Low-Carbon District Energy System Planning," Energies, MDPI, vol. 14(5), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1383-:d:509526
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    References listed on IDEAS

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    4. Christoph Bahret & Ludger Eltrop, 2021. "Cost-Optimized Heat and Power Supply for Residential Buildings: The Cost-Reducing Effect of Forming Smart Energy Neighborhoods," Energies, MDPI, vol. 14(16), pages 1-16, August.

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