Demand.ninja
A customisable model for hourly heating and cooling demand applicable globally at all spatial scales, created by the team behind Renewables.ninja.
We launch this model with a paper in the Nature Energy journal: A global model of hourly space heating and cooling demand at multiple spatial scales, which is free for all to read open-access.
The paper describes the model's methodology and data sources, and provides extensive validation of its ability to model real-world demand measured from thousands of buildings and 40+ countries and regions spanning across four continents.
The paper also demonstrates the Demand.ninja model in two case studies: looking at how much natural gas can be saved by reducing building thermostat temperatures across Europe and the US, and looking at how climate change has increased the global demand for space cooling over the last forty years.
We model the gas demand from 2,000 homes in the UK and find on average they would save 1,750 kWh of gas by lowering their internal temperature by 1°C. Given how high gas prices have been since last winter, this amounts to a £200 saving per household.
Since Russia's invasion of Ukraine, Europe has been racing to reduce gas consumption to avoid shortages. If all buildings across Europe lowered their temperature by 1°C, Europe would save 240 TWh (or 840 billion cubic feet) of natural gas per year. This would cut the cost of imports by €22 billion per year, and cut CO2 emissions by nearly 50 million tonnes per year: a win-win-win for energy security, affordability and the climate.
We also look at how rising global temperatures is pushing up the demand for air conditioning. Cooling demand is rising fastest in northern Europe, by up to 5% year-on-year in places like the London and the UK south-east. Back in the 1980s it was rarely hot enough to need space cooling, but with hotter summers and intense heat waves, air conditioning is becoming a more common feature.
Even without growing uptake of air conditioners, the fact summers are warmer than they used to be means countries around the world have to consume more electricity to keep buildings comfortable. The US is consuming 66 TWh more per year for air conditioning than it did a generation ago because of hotter summers.
To build upon the Demand.ninja paper, we are developing open-access tools to help you build simulations of current and future energy demand.
The core code of the Demand.ninja model is made freely-available on GitHub. Then, we are developing two interfaces to interact with the model: a 'building' mode where you can simulate energy demand for a building anywhere in the world, and a 'region' mode where you can explore the total energy demand across countries, states and provinces.
All of the data that featured in the paper is released as Supplementary Information and Source Data, which you can access on the Nature Energy website. In addition, we are releasing an extended dataset of daily temperatures and degree days for all regions of the world, plus energy demand estimates for those regions where we have been able to already calibrate the model.
We have added a new module to the popular Renewables.ninja website that allows you to calculate degree days and model energy consumption for buildings located anywhere in the world.
We are developing an interactive front-end to the Demand.ninja that will allow you to easily customise the model parameters and explore time-series of projected demand.
For example, you will be able to assess the impact of aircon and heat pump uptake on electricity demand, or changing consumer preferences for thermal comfort.
We have calculated average temperatures and degree days for every world region, which you can download from the links below. Each file gives raw temperatures, our Building Adjusted Internal Temperature (or BAIT) which is a measure of how warm it would feel inside a building, given solar gains, wind chill and humidity, heating and cooling degree days that are derived from BAIT. These all use our general global average model parameters, which are given in Figure ED1 in the paper. We provide 43 years of data at daily resolution, under a CC BY-NC 4.0 license.
We specifically modelled the electricity demand in 43 national and regional power markets in the Demand.ninja paper. We calibrated the model for each of these markets, so we are also in the process of compiling temperature, degree days, and electricity demand for each region, covering 43 years at daily resolution. The electricity demand simulations give an estimate of what each country or region would consume if the population, building and technology stock of today experienced the weather of the past. These simulations are built using our bespoke calibrated parameters.
Temperatures and degree days. Daily data 1980-2022.
Individual country files contain all sub-regions plus national aggregates. Smaller countries are grouped together in a seperate file.
Country | Temperature | Building Adjusted Internal Temperature | Heating Degree Days (HDDs) | Cooling Degree Days (CDDs) |
---|---|---|---|---|
Canada | CA_Temp.csv.gz | CA_BAIT.csv.gz | CA_HDD.csv.gz | CA_CDD.csv.gz |
Mexico | MX_Temp.csv.gz | MX_BAIT.csv.gz | MX_HDD.csv.gz | MX_CDD.csv.gz |
United States | US_Temp.csv.gz | US_BAIT.csv.gz | US_HDD.csv.gz | US_CDD.csv.gz |
32 other countries | NAM_Temp.csv.gz | NAM_BAIT.csv.gz | NAM_HDD.csv.gz | NAM_CDD.csv.gz |
Temperatures and degree days. Daily data 1980-2022.
Individual country files contain all sub-regions plus national aggregates. Smaller countries are grouped together in a seperate file.
Temperatures and degree days. Daily data 1980-2022.
Individual country files contain all sub-regions plus national aggregates. Smaller countries are grouped together in a seperate file.
Temperatures and degree days. Daily data 1980-2022.
Individual country files contain all sub-regions plus national aggregates. Smaller countries are grouped together in a seperate file.
Country | Temperature | Building Adjusted Internal Temperature | Heating Degree Days (HDDs) | Cooling Degree Days (CDDs) |
---|---|---|---|---|
Argentina | AR_Temp.csv.gz | AR_BAIT.csv.gz | AR_HDD.csv.gz | AR_CDD.csv.gz |
Bolivia | BO_Temp.csv.gz | BO_BAIT.csv.gz | BO_HDD.csv.gz | BO_CDD.csv.gz |
Brazil | BR_Temp.csv.gz | BR_BAIT.csv.gz | BR_HDD.csv.gz | BR_CDD.csv.gz |
Chile | CL_Temp.csv.gz | CL_BAIT.csv.gz | CL_HDD.csv.gz | CL_CDD.csv.gz |
Colombia | CO_Temp.csv.gz | CO_BAIT.csv.gz | CO_HDD.csv.gz | CO_CDD.csv.gz |
Peru | PE_Temp.csv.gz | PE_BAIT.csv.gz | PE_HDD.csv.gz | PE_CDD.csv.gz |
Venezuela | VE_Temp.csv.gz | VE_BAIT.csv.gz | VE_HDD.csv.gz | VE_CDD.csv.gz |
6 other countries | SAM_Temp.csv.gz | SAM_BAIT.csv.gz | SAM_HDD.csv.gz | SAM_CDD.csv.gz |
Temperatures and degree days. Daily data 1980-2022.
Individual country files contain all sub-regions plus national aggregates. Smaller countries are grouped together in a seperate file.
Temperatures and degree days. Daily data 1980-2022.
Individual country files contain all sub-regions plus national aggregates. Smaller countries are grouped together in a seperate file.
Country | Temperature | Building Adjusted Internal Temperature | Heating Degree Days (HDDs) | Cooling Degree Days (CDDs) |
---|---|---|---|---|
Australia | AU_Temp.csv.gz | AU_BAIT.csv.gz | AU_HDD.csv.gz | AU_CDD.csv.gz |
8 other countries | OCE_Temp.csv.gz | OCE_BAIT.csv.gz | OCE_HDD.csv.gz | OCE_CDD.csv.gz |