If the planet doesn’t burn out soon, by the time we celebrate 2050 new year’s eve we’ll see:

  • 50% increase of the global population 
  • 5x global economic activity
  • 3x global energy consumption
  • 3x global manufacturing activity

Balancing sustainability against conventional manufacturing production creates conundrums for business. One of the largest issues is how to spread the benefits of industrialization worldwide, without creating unsustainable impacts on the environment.

Building owners are already beginning to feel the pressure: rising energy costs and concerns about global warming are forcing facilities managers to seek ways to optimize the energy efficiency of their buildings to reduce overall costs and energy usage. One of the least talked about and often overlooked contributors to this overall problem are the inefficient heating, ventilation and air conditioning systems. They’re present in every office building, manufacturing facility, or warehouse. 

Incredibly, for any type of building, HVAC and lighting systems contributes to as much as half of the energy consumption.

Improving the control of HVAC operations and the efficiency of the buildings systems can save significant energy, increase thermal comfort, and contribute to improved indoor environmental quality.  Fortunately, saving money and improving the environment is a happy byproduct of optimizing HVAC systems to reduce energy consumption and costs. Just by improving the efficiency of a building’s central plant (a large part of the HVAC system), including automating components for real-time optimal performance, can cut water use by thousands of gallons, and save a large percentage of the yearly costs associated with operating a facility or building.  

So, can these algorithms that were developed to automate reasoning or calculate outcomes help a commercial climate control system system? I am sure that you can guess that the answer is “Yes, of course”  In many studies it has been shown that most AI-assisted HVAC programs will have a significant effect on a buildings energy footprint, saving between 5% to 15% on water usage and up to 25% on costs*.

*Keep reading 😉

In the case of HVAC systems, there are a number of factors that change the temperature of a room. A typical system uses cold air to decrease the ambient temperature. The activities and number of tenants and naturally, solar radiation all heat up the interior of a building.  When there is a balance between these different factors, temperature is maintained and no more cold air is introduced.

To put this into a real world example that we can all hopefully relate to, imagine that you are running a marathon with a hilly course. You will go faster going downhill, and slower uphill, but at the end, you have hit your target time. Considering this, it makes sense to give a range of times that are acceptable per mile.  By giving a range to the buildings thermostat, rather than a specific, fixed temperature, HVAC systems have more flexibility to maximize their efficiency and comfort, throughout the day

Harnessing the power of a combination of optimized settings, predictive controls, distributed AI, and anomaly detection together, a temperature “comfort range” is determined based on all the available data. By sensing real time weather, occupancy rate patterns, energy usage by tenants, time of day, and many others, the algorithms learn and predict the best settings, balancing comfort and cost savings.

Energy savings can be achieved manually by widening the “deadband”, but without optimization, the room temperature may go against the dynamics of the room, wasting energy by overcooling or overheating.

So a combination of optimized settings, predictive controls, distributed AI, and anomaly detection together will make a building more “climate friendly”?  That sounds complicated, but it is child’s play for SmartCat’s Optimus Power HVAC optimization solutions.

Optimus Power solves three problem areas for building owners: it infers base load profiles and does load prediction, detects multiple types of anomalies which could make systems run less efficiently and does optimal control.  All together, this gives reliable predictions, which change based upon users behavior as well as changes in weather patterns, is scalable, thanks to the chosen tech-stack and developed algorithms, and saves money and energy, up to 35% compared to non-optimized solutions (See, aren’t you glad you kept reading!! 😀)

Since our mission is to “Make a difference with data”, SmartCat helps our partners develop meaningful data solutions to real problems. We created a dream team of bright people who, together, finds novel ways to solve complex data problems for carefully selected projects. 

The result? Our solutions will have a positive and measurable impact on everyday life, society, and business.  For us, Optimus Power is a perfect example where a solution we developed can save money, save the environment and make people happier, all with data and our knowledge.