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.
Highlights
With the dramatic increase in the world’s population in the last two centuries, the energy demand has increased [1]
Refers to our software workflow that carries out the whole process of 3D building modeling for the energy demand analysis and the entire process of energy system modeling in an automatic manner
energy system model (ESM) determines the number of heat pumps (HP) in each iteration that cover the maximum demand, and the required number of required HPs is added to the results
Summary
With the dramatic increase in the world’s population in the last two centuries, the energy demand has increased [1]. The U.S energy information administration reported that the contribution of heating and cooling buildings to the total energy consumption is. 40%, and mostly depends on fossil fuels [1]. Utilizing renewable energy resources leads to a decrement in the consumption of fossil fuels and, the related emissions. The general attitude toward energy consumption is to lower it, and to reduce the emission of greenhouse gases. The European Council decided to reduce the EU’s energy consumption by 32.5% in 2030 compared to the 1990 levels by increasing energy efficiency [2]. Integrating renewable energy resources with different energy systems is one of the leading solutions to changing energy production systems [3,4]
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