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Vertical City Toolkit - Energy Analytics

What if condominium boards or property managers were able to accurately track of how much energy they were consuming? And what if they could uncover when the amount of energy used was higher than it should be? This is exactly what our toolkit aims to give condominiums. When this toll was originally built by the founder, a board member and owner in his condominium, it identified an existing energy issue that had been undetected for over two months and had cost the corporation and it's owners over $100,000. Before leveraging an analytical process, the corporation had no systematic way of identifying issues. High consumption levels were typically accepted by assuming they were the result of changes in weather.

Building Utilities Management 101

Utility costs are typically a significant cost for a corporation. And with utility prices the seems to always be rising, it will always remain a significant cost. When monthly costs rise, alarms will often be raised and investigations will often be initiated to hopefully learn about the root cause. Investigations are typically limited to looking through historical bills. This alone will never be sufficient to evaluate changes in utility costs and consumption. Moreover, historical utility bills are often collected in PDFs or physical paper invoices, that can make systematic analysis a nightmare.

A progressively minded corporation and/or property manager may track and record utility history electronically on a spreadsheet. Systematic data collection is necessary towards a better solution but, without the right tools, will still leave the potential issues hidden. Corporations can track consumption changes over billing cycles and visualize the history. (In the image below, the yellow line plots the consumption of each monthly bill).

If a month has an excessive amount of utility consumption, observers will often accept the weather during the period was abnormal. Often with people sharing anecdotal perspectives. By justifying an increase in consumption, and resulting in the increased costs, any potential to identify real issues are lost.

The Impact of Weather

How do we confirm if an anecdotal story regarding weather over the past month did truly impact any utility consumption? If we are only looking at the consumption plotted across time, it would seem that the winter of 2019 was especially cold, and we would expect especially high levels of consumption as a result of nature. It does make sense that in colder months, more energy is required to heat many common building areas. But the size of the impact is hard to fully understand.

It is common knowledge that prevailing weather is a significant factor for energy consumption. By using historical weather data, available on Government of Canada's weather database, we can align each billing period with the average daily temperature for that period. By using historical weather data we have an accurate way to compare energy consumption levels with prevailing temperature levels. It should be noted that the impact of weather is almost impossible to compute by scanning this information manually. Valuable insights are only possible by leveraging technology and a systematic process that can analyze all the data. Our toolkit allows condominiums an easy way to leverage multiple data sources and gain valuable insights.

A Little Math

Using historical energy consumption and weather data, a little math can be employed to model the relationship between weather and consumption. The generic mathematical technique that can be used here is called a polynomial regression and it allows us to quantify the relationship between the expected energy consumption for any given temperature.

The technique finds the best "fitting" line for the collection of points (as shown in the chart to the image above on the right where the blue line is "fitting" to the collection of yellow points) and also provides the accuracy of the fit that informs a reasonable range. Putting this together, we now have a tool that is able to objectively and systematically account for the weather.

The blue line indicates the expected range of consumption based on the temperature. And as we can now see, the actual consumption was much higher than the relationship of historical weather and bills say it should be. Thus, it wasn't an especially cold winter after all.

Summing It Up

After the creation of this tool, it became clear to the board that a deeper inspection of the problem was necessary. The especially large bills were discovered to be the result of a major energy leak, where two different opposing energy systems (steam and air conditioning) were heating and cooling the same area for the past two months, fighting each other to keep the temperature at baseline. It was clear that without the tool it would have taken even more time to uncover the underlying issue, costing the board and the owners dearly. It's very rare that a corporation uses these types of analytics for their utility bills which we see as a hole in the system, and which inspired us to create this tool. We hope it's as useful to you as it has been for us!


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