April 9, 2015: BuildingIQ Uses MATLAB to Develop Predictive Algorithms for HVAC Energy Optimization
Company Creates Software Platform That Reduces HVAC Energy Consumption
NATICK, Mass. — MathWorks announced that BuildingIQ is using the data analytics capabilities in its MATLAB tool to speed the development and deployment of predictive algorithms for HVAC energy optimization. BuildingIQ engineers have developed Predictive Energy Optimization™ (PEO), a cloud-based software platform that the company says reduces HVAC energy consumption in large-scale buildings by 10-25 percent during normal operation.
BuildingIQ needed to develop PEO as a real-time system that would help minimize HVAC energy costs in large commercial buildings via 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 and Machine Learning Toolbox 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 system, the team used MATLAB Compiler for deployment, saving time and resources from translating MATLAB algorithms into Java or C.