Beyond Energy Efficiency – Using the Power of Data to Find the Cleanest Hours of the Day
By Rob Bernard, Josh Henretig, TJ DiCaprio — Microsoft
Originally posted on the Microsoft Green Blog
On an average morning, you turn off your alarm, turn on the lights, power on your smartphone that was charging overnight, take a hot shower, make a cup of coffee, all while watching the local news. This morning routine is all powered by electricity. The green-minded citizen will turn those lights and appliances off quickly, take a shorter shower, and make sure everything is off before leaving the house. Taking those energy-efficient steps is helpful.
But what if you wanted to do more to help the environment by changing not only how much energy you consume, but what kind of energy you consume? That’s a bit more challenging. At present, most households have no choice or ability to directly influence their individual energy mix—but thanks to big data that’s all about to change.
The Smart Energy Azure Demonstration platform is a user-friendly platform available to anyone with an Azure subscription. The solution builds on the tremendously innovative work done by WattTime. Their API provides data on generation mix down to the megawatts generated from each fuel source; average carbon emissions; and marginal carbon emissions, which is the part of the carbon footprint that you can actually affect by using or conserving energy at a particular place and time. And because the grid’s energy mix changes based on the weather, the platform also pulls in global weather data and forecasts from the Wunderground API.
With data sets customized to their local power grids, consumers can make much more informed decisions about how to adjust their energy consumption and cut energy costs. But knowing this information is just the beginning. By combining these insights with a Microsoft IoT suite that will enable users to sync their home devices with the system’s data, users will soon be able to optimize the energy use of their homes in real time. (The steps for getting the system up and running are clearly detailed in the GitHub page for the solution.) By doing this, households can leverage new solutions, like smart thermostats and smart home apps, to tailor their individual energy use even further and proactively align with times of the day when more clean energy is available on the grid.
These small changes can make a big impact. According to the Rocky Mountain Institute (RMI), enabling water heaters and air conditioners to adjust their timing just slightly could reduce carbon emissions in the United States by over six million metric tons per year—the equivalent of taking one million cars off the road. In addition, RMI found that carbon emissions from loads connected to the PJM grid in Chicago, IL, can be reduced by 5 to 15 percent simply by prioritizing energy usage for periods when coal plants are not on the margin.
To put this theory into practice, we’re working to test the Smart Energy Azure Demonstration platform in enterprise-level applications, like universities. This year, we’re teaming up with Princeton University on a “Marginal Carbon Emissions Project” to see how the platform performs in a larger, multi-building campus setting and to co-develop new projects, including one that would allow the university to measure the CO2 emissions of using the grid compared to tapping Princeton’s onsite power generation at any given time. This will allow the university to further customize its energy utilization and drive daily efficiency.
At Microsoft, our goal is to empower our customers with the tools and technology to achieve more, sustainably. We’re excited by the potential of this and other new technology to help consumers make more informed energy decisions by bringing data to their fingertips—so that running a greener home is as easy as making your morning coffee.