Energy providers, real estate management companies, and other organizations looking to minimize their energy consumption and spending continue to invest in smart energy technologies at a brisk pace.
Spending in the global smart thermostat market alone is expected to jump from about $100 million today to $1.4 billion by 2020, according to a recent study by Navigant Research.
Smart energy technologies can generate a number of useful benefits for companies, including impressive cost savings that can be achieved through more efficient energy utilization as well as obtaining more accurate bills based on actual energy usage and not estimates.
Still, companies that apply predictive analytics to smart energy initiatives can maximize their benefits even further, in part by identifying the most cost-effective technologies to use based on their energy consumption patterns and energy management goals.
For its part, the Navy has established a target of making half of all its buildings net-zero energy by 2020 – meaning they will produce as much energy as they consume by that time.
The two branches of the U.S. Armed Forces contracted with Sain Engineering to conduct energy audits at specified buildings using analytics through 2014. The efforts are expecting to reduce the audit times by as much as 80%.
Analytics are helping the Army and Navy examine combinations of more than 2,000 potential energy optimization measures, including HVAC renovations and more subtle operational changes that can impact energy consumption.
The initiatives make good fiscal sense for the Army, Navy, and other federal entities. The federal government occupies roughly 500,000 buildings worldwide and spends approximately $7 billion annually just to keep the lights on.
The potential for using analytics to identify smart energy savings that can be applied to buildings is dramatic.
Buildings consume about 40% of all energy annually, according to an article in GreenBiz.com, which notes that data analytics is a less capital-intensive approach to energy management than replacing equipment or conducting building retrofits.
“Data analytics allows building owners and managers to optimize the existing building and equipment as is. While the benefits of capital-intensive retrofits are real and well-documented, the payback periods for many retrofit projects are relatively long (seven to more than 10 years) and are therefore problematic for organizations that need to drive savings within a shorter window of time,” according to the article.
By comparison, combining analytics with smart energy use in buildings can result in much faster payback periods – 12-to-24 months – through continuous monitoring and fault/exception reporting.
Meanwhile, the use of smart sensors with analytics can provide real-time monitoring of energy use to help homeowners, building owners and tenants better track usage and identify where energy waste is occurring so they can take corrective action.