Chiller Optimization

Patented AI/Machine-Learning energy optimization technology for large centralized HVAC, Cooling and Refrigeration Systems. ECORE actively analyzes and automatically adjusts set points and load balances, even across multiple chillers and heat-pumps, yielding 20-40% energy and cost savings - guaranteed. ECORE automatically responds to changing variables, such as load, ambient air temperature, relative humidity, system temperature and pressures and instructs the BMS/BAS system to make continuous small adjustments; recalibrating for optimal performance without any effect on manufacturer warrantees. Chillers running inefficiently also results in decreased equipment reliability, increased maintenance intervals, and shortened lifespan.

Harnessing the first law of thermodynamics and using machine learning, the ECORE platform dynamically determines and sets system parameters to obtain the lowest energy usage at prevailing ambient conditions. ECORE works within the chiller manufacturer specifications, thus not impacting warranties, but simply operating the chiller system in the most energy-efficient manner as recommended by the chiller manufacturer. The platform uses proprietary and customized algorithms that enables the chiller system to continuously adjust to changing load and ambient conditions to calibrate to the manufacturer's recommended flow, temperature, and other set-points.