Predict the Load Required to Heat a Building

Can the heating load of a building-to-be be estimated?

Europe spends 50% of its energy for heating and cooling purposes. Most of it in Europe is produced by fossil fuels, i.e., 66%, and only 13% comes from renewable energy sources.
TADA can help architects predict and quantify the heating load of a building before it is even built.

**Industry**

Environment

**Project Duration and Effort**

One week

**Type Of Prediction**

Regression

**Customer Benefits**

Calculate a building heating and cooling load before the building is built

Get an excellent accuracy in these estimates

Evaluate in seconds the heating impact of doubling the window surface on a new building

**Problems to solve**

The typical US household pays between 3 and 4% of the family’s income on heating and cooling. Single-family houses spend twice as much energy for heating as multi-family houses. In EU houses, heating and hot water alone account for 79% of total final energy use. Cooling is a comparatively small share of full final energy use, but demand from households and businesses such as the food industry is rising during the summer months. This trend is also linked to climate change and temperature increases.

We use TADA to estimate a building heating time. The dataset considered includes 538 records, and the following features are provided for each record:

heating load

cooling load

relative density

surface area

wall zone

roof zone

total height

direction

window area

window area rate

The rising demands for glass walls in hotels, airports, commercial complexes have elevated indoor temperatures leading to higher demand for cooling systems. Advanced prediction of building cooling time and heating time can help engineers and architects design energy-efficient buildings. This type of cooling load and heating load modeling permits various ‘what-if’ scenarios without even laying the first stone. The impact of a bigger glass ceiling in an airport can be modeled in a few clicks, and the resulting cooling load estimated seamlessly.

**Objectives**

Estimate a building heating and cooling load in a few clicks without the use of equations

Understand what impacts the heating and cooling load in a building design

Test architectural hypotheses concerning energy consumption

It poses the following construction question:

Can the heating load of a building-to-be be estimated?

**Solution**

The TADA predictive models provide good results: an R2 of 99%, a MAPE of 5%, and a RMSE of 1,04 for a mean of 22,13. Effectively managing the thermal behaviors of a building is a complex process. These behaviors are expressed in a collection of thermal energy equations, which, once calculated, will not change over time for a building unless significant renovations are carried out. TADA is a simple alternative to the use of these complex equations.

TADA has selected the following six main criteria out of the ten available in the dataset:

the relative density, with a weight of 21% in TADA’s decision,
the surface area, with a weight of 21% in TADA’s decision,
the wall zone, with a weight of 20% in TADA’s decision,
the roof zone, with a weight of 16% in TADA’s decision,
the total height, with a weight of 14% in TADA’s decision,
the window area, with a weight of 7% in TADA’s decision

An R2 of 99% means that the predictions are very accurate. It is interesting to note that the building’s relative density is a significant criterion in TADA’s decision, before the window area with three times the weight in TADA’s decision.
It is also possible to dynamically evaluate the impact of increasing the window area on the heating or cooling load by using our live predict feature.

Customer Benefits

In one week, architects gained significant support in their energy consumption estimates for buildings-to-be:

Calculate a building heating load before the building is built with an R2 of 99%
Evaluate in seconds the heating impact of doubling the window surface on a new building