Our cloud-based Predictive Energy Optimization™ (PEO) platform is a paradigm-shifting technology used to reduce energy consumption in commercial, academic, and government buildings.  The optimization process involves three basic steps:

  • Learning the thermal dynamics of the building;
  • Refining the model through the slow convergence between parameter prediction and actual readings from the building; and
  • Optimization, in terms of both energy efficiency and cost.

This paper focuses on the important process of collecting meter data and feeding it into the PEO model.