I’m struggling with filling out the energy consumption table for the energy savings valuation in the InVEST Urban Cooling model. I’ve read through the User Guide and am confused about a few things.
First, at one point in the User Guide, the units for consumption are stated as kWh/(m² · °C), but then elsewhere they’re stated as kWh/°C/m² and then somewhere else they’re stated as kWh/°C. Which is it?
In terms of calculated consumption per building type, I am also confused. I have two building types in my study area: Residential and Commercial/Industrial. I have the following information:
For commercial/industrial buildings, average energy use intensity is 336.1 kWh/m²
For residential buildings, average energy use intensity is 147.2 kWh/m²
Average floor area (calculated using the building footprint layer in GIS) for residential is 189.65 m². I’m assuming that residential buildings have an average of 3 floors, so total floor area for this building type would be 3*189.65 = 568.95 m².
Average floor area for commercial/industrial is 2910.18 m². Assuming these buildings have an average of 2 floors, total floor area would be 2*2910.18 = 5820.36 m².
I’ve also looked at Santamouris et al. (2015), and the percentage increase of the base electricity load per degree of temperature increase for my study area (Ontario, Canada) is 1.5%.
For more context, I am running the InVEST model for the month of July. How would I go about calculating energy consumption in the proper units given this information?
Thanks for writing in to the forum with your questions about the urban cooling model.
The unit of measure for the consumption column of the Energy Consumption Table CSV input data file is kWh per m² per °C, as listed in the User Guide. Meaning, the amount of energy required to cool one square meter of building space by one degree Celsius. I interpret both kWh/(m² * °C) and kWh/°C/m² to be equal to this. It’s just a matter of syntax, but you’re right that it would be best for us to list this unit consistently.
The mention of kWh/°C in the Appendix is simply providing qualitative guidance for parameter selection, it is not defining the required units of measure for the model’s data inputs. This is an attempt to explain that the amount of energy needed to cool buildings varies greatly, and are dependent on things like the efficiency of A/C systems, building materials, and ceiling heights.
In the building_intensity column of your Biophysical Table CSV input data file, remember to normalize all values between 0 and 1.
This model is time agnostic. So since you’re modeling the month of July, all of your input data should only reflect the average conditions in July. Further, if you’re using the daytime (factors) method, your input data values should represent the daytime only. For example, the Reference Air Temperature should be the average reference air temperature during the daytime in July.
Thank you very much for the reply! It was very helpful and cleared things up for me.
However, I am still a little bit lost on how I would go about calculating energy consumption for each building type given the data I described above. Is there any way you would be able to give me a sample calculation?
Looking at the data that you shared on December 5th, I don’t believe we have all the information we would need to perform these calculations. The missing piece is related to the change in indoor temperatures attributed to the energy use data you provided. To begin to get at that, we would need to know if those “average energy use” values cover an entire year or only the month of July, for instance. Does it include energy used for other purposes beyond cooling, such as for lighting? Further, does this include nighttime energy use that may include things like heating?
Remember, all of your input data should only apply to daytime in July, if that is indeed your period of interest. Once you’ve determined that your average energy use values by building type in kWh/m² represent only daytime in July, then you would need to know how many °C that amount of energy cools each respective type of building.
I suppose a rough way to get at that might be to subtract a reasonable and commonly desired indoor summer temperature from what the temperature would be inside without any energy use/cooling in Ontario. Perhaps the indoor temperature without cooling would be similar to the temperature of the reference air temperature plus the UHI effect. Something like ~37°C - 22°C = 15°C. So then you could do 336.1 kWh/m² / 15°C ≈ 22.4 kWh/m²/°C for commercial/industrial and 147.2 kWh/m² / 15°C ≈ 9.8 kWh/m²/°C. But please research and refine these temperatures I’ve chosen for these example calculations to make sure they are accurate and representative of Ontario! I suspect my values are too low. When I asked ChatGPT it claims:
"…a rough estimate for cooling energy requirements is about 50 to 70 kWh per square meter (kWh/m²) for cooling a space by 1 degree Celsius over a typical day in July in places like Ontario."
Of course, Ontario is a very large province with great variation in latitude and climate. Your data should represent your precise study region as closely as possible. Please remember that while this model can be used across large spatial scales, it is intended for smaller regions, namely individual metropolitan areas, cities, towns, or neighborhoods.