Products :: SCIenergy

Introducing SCIenergy - Measurable and Verifiable Energy Baselining for Commercial Buildings

SCIenergy™ is a highly accurate energy measurement and optimization application module that works in conjunction with Scientific Conservation’s SCIwatch™ Automated Continuous Commissioning platform.  SCIenergy is a breakthrough solution that accurately measures and predicts a facility’s energy use under a wide range of operating conditions to help determine whether or not the building is performing at optimal energy efficiency levels.

By providing scalable, accurate baselines to measure savings across the grid, SCIenergy can assist organizations to qualify for utility rebates based on measureable and verifiable performance.  This ensures rebates are more fairly distributed.

SCIenergy is based on a methodology that has been tested on numerous types of buildings including office, retail, institutional, industrial and healthcare facilities.  In the majority of cases, the accuracy of the monthly energy use projections reached 99 percent. 

Based on years of extensive research, Scientific Conservation has developed SCIenergy by using a combination of Fuzzy Logic and Neural Networks to determine highly accurate energy baselines for any type of building.

Key attributes of the energy baseline model include:
• Extreme accuracy (> 97%)
• Scalability to thousands of sites
• Cost-effectiveness through the elimination of onsite energy audits and complex facility modeling
• Minimal data inputs
• Flexibility to determine energy savings and GHG baselines

Unlike other energy baselining tools that rely on expensive, labor-intensive and complex metered calculations, SCIenergy uses a mathematical modeling methodology to calculate energy reduction levels that can be used with equal effectiveness for either new installations or retrofits.

As an open-ended application, SCIenergy is fully compatible with virtually all building automation systems including those from Johnson Controls, Trane, Siemens, Honeywell, Siemens, Novar, Schneider Electric, Automated Logic Corporation and more.  This enables facility managers to easily leverage trend data produced by building automation systems since SCIwatch maintains sophisticated mathematical algorithms to predict problems based on trending.  And because SCIwatch does not require a site visit to perform baselining, the process is greatly streamlined and virtually transparent to facility operators.

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