Uses MATLAB to speed up development and deployment of predictive energy optimization algorithms
BuildingIQ, a highly recognized leader in the industry, has recently been titled as the winner of a 2014 National Energy Efficiency Industry Award for Best Commercial Energy Efficiency Project, 2013 Bloomberg New Energy Pioneers Award, Fierce Innovation Awards’ “Best in Show”, a 2013 Cool Vendor in Green IT and Sustainability by Gartner and listed on the 2014 Global Cleantech 100 and AlwaysOn Going Green Global 200.
Therefore, a product of MathWorks, which is a leading provider of advanced energy management software that actively predicts and manages HVAC loads in commercial buildings, as the only supplier of patent-pending Predictive Energy Optimization™ technology.BuildingIQ is a cloud-based solution, powering energy and operational savings in buildings across the globe with reductions in HVAC energy costs by as much as 25 percent. BuildingIQ delivers measureable results and has received backing from tier one industry leaders including Aster Capital (backed by Schneider Electric, Alstom and Solvay), the Venture Capital unit of Siemens Financial Services (SFS VC), Paladin Capital and the Energy Division of the Commonwealth Scientific and Industrial Research Organization (CSIRO).
BuildingIQ uses data analytics capabilities in MATLAB to speed up the development and deployment of proactive, predictive algorithms for HVAC energy optimization. BuildingIQ engineers have developed Predictive Energy Optimization™ (PEO), a cloud-based software platform that reduces HVAC energy consumption in large-scale buildings by 10%-25% during normal operation.
BuildingIQ needed to develop PEO as a real-time system that would help minimize HVAC energy costs in large-scale commercial buildings via proactive, predictive optimization. The team used MATLAB algorithms integrated in a production cloud environment to optimize occupant comfort while minimizing energy costs. BuildingIQ engineers used Signal Processing Toolbox to filter data, Statistics for algorithms to model contributions of gas, electric, and solar power to heating and cooling processes, and Optimization Toolbox to continuously optimize energy efficiency in real time. To integrate the resulting algorithms into the production systems the team used MATLAB Compiler for deployment, saving time and resources from translating MATLAB algorithms into Java or C.
“We use MATLAB because it is the best tool available for prototyping algorithms and performing advanced mathematical calculations,” said BorislavSavkovic, lead data scientist at BuildingIQ. “MATLAB enabled us to transition our prototype algorithms directly into production-level algorithms that deal reliably with real-world noise and uncertainty.”
Paul Pilotte, technical marketing manager, MathWorks, specified, that “While companies look for more intelligence from their data, they often lack the resources and expertise in analyzing and visualizing gigabytes of data, quickly developing algorithms, and finding the best suited algorithmic approach,” He further added, “BuildingIQ is setting a benchmark with its ability to analyze and visualize big data sets, deploy these advanced optimization algorithms, and run them in a production cloud environment.”
