Calculating the REAL impact of nanogrids on GHG emissions
Use case - Greenhouse in Ontario, Canada
May 20, 2021
Greenhouse and greenhouse gas, a global approach for quantification
In the fall of 2020, vadiMAP completed a prescription for a greenhouse located in Ontario, whose heating and ventilation consume more than 700,000 kWh per year. Based on information collected from the online questionnaire, geolocated system data (solar resources, equipment prices, etc.) and market data (electricity tariffs, incentives, etc.), vadiMAP simulated the energy behavior of 916 nanogrids. The comparison of their performance for the objectives of savings, resilience and GHG reductions enabled the selection of the optimal configuration according to the customer's needs.
In this case, the solar PV installation is ground-mounted with an installed power of 120 kW. Annually, it generates 30% of the energy needs, $ 29,700 of savings as well as a reduction of 19 tCO2e, for a payback period of 10 years.
One of vadiMAP’s specificities is its comprehensive approach for calculating the impact of nanogrids on GHG emissions. With respect to the greenhouse in question, the installation of solar panels will reduce the electricity consumption from the grid, thus reducing the emissions associated with the generation of this electricity. The estimations of most competing solutions are typically limited to this extent. However, to be complete, it is important to add the emissions linked to the installed equipment lifecycle (production, transport, installation, end of life, etc.), because they would not have occurred in the absence of the project. Consequently, this omission only provides a partial picture of the total impact of nanogrids on GHG emissions. Where applicable, vadiMAP also quantifies the direct GHG reductions (scope 1) generated by the decrease in fuel consumption.
In addition, vadiMAP has selected the marginal approach over the average approach for the quantification of reductions linked to electricity. The latter estimates the carbon intensity of the entire energy mix of a grid, while the marginal method focuses on the production of electricity affected by variations in demand. For example, in Ontario, the decrease in greenhouse consumption will affect the production of gas or hydroelectric power plants, because they respond to demand changes, but such decrease will not affect the production of nuclear power plants. Thus, the marginal approach enables to quantify the GHG reductions linked to the production decrease from the power plants effectively affected by this consumption drop. It allows a more detailed assessment of the real impact of nanogrids on GHG emission as well as the dramatic effect of their location. While the average GHG intensity of electricity is lower in British Columbia than in Ontario, the marginal approach indicates that the same installation will generate nearly 4 times more GHG reduction in the western part of the country.
The annual GHG reductions of the Ontarian greenhouse are broken down into 29 tCO2e reduction linked to electricity consumption and 10 tCO2e emission from the equipment life cycle, for a total of 19 tCO2e.