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Home Energy Modeling and its Effect on Real Estate

By Allison Halliday | March 22, 2016

These days, consumers have access to a huge amount of information through their smart phone and can research purchases before they commit to buying. But information about any energy components is still less readily available.

However an article in points out that this is changing, particularly in the electricity sector due to cheaper energy such as solar photovoltaics and deregulation. Improvements to analytics software, metering technologies and modelling are also leading to greater transparency for energy consumers. In spite of this there are still markets where better solutions are required and Tendril is a data science and software company that is focusing on the personalization of energy in the electric sector. Over the past 10 years, the company has been applying its True Home Simulation Model to utility customer engagement initiatives and to behavioral energy efficiency programs and now this model is being used to create a library of energy content for markets with limited access to data.


One sector that can benefit is real estate and rooftop solar. Tendril is able to model home energy consumption using the physical characteristics of the home. This includes the construction materials, the square footage and the year the property was built. The information is used to calculate the energy balance and heat transfer properties of the home.

The company has already mapped all 133 million homes in North America and is beginning to map the physical characteristics of homes throughout the world using this model. With the help of local tax assessment records, they are able to compile a database with the relevant information on the property size, age and occupancy. They can simulate local weather conditions based on latitude and longitude and image analysis allows them to gather details on the orientation and shape of the home.

Being able to simulate the energy consumption of every home in this continent has allowed Tendril to create a scoring algorithm for home comparisons. The algorithm can also be used to simulate particular upgrades such as insulation or new windows, as well as the return on the investment for these upgrades. This also applies to solar generation and enables consumers to receive a personalized return on investment estimate for solar upgrades.

Tendril is particularly interested in the fact that real estate search sites allow consumers to compare homes, but frequently energy consumption isn’t included in this data. As energy costs often account for a large monthly outlay, this is often an important consideration for potential buyers.

Photo Credit: bykst via pixabay

Allison Halliday is a Realty Biz News contributing writer. She handles International Real Estate and is a seasoned blogger.
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