Steer Sustainable Buildings With Proactive Energy Management

Xempla identifies building energy consumption patterns and inefficiencies so that you never miss out on opportunities to help your customers save energy and improve energy performance to better execute their sustainability goals.

energy management

Gain full visibility into your building’s energy consumption

Get a clear picture of key performance indicators in one location with a simple and easy to use energy dashboard. Visualize insights and stats on energy consumption, cost, intensity, and carbon footprint across different areas in a variety of graphical formats.

energy performance

Track down and optimize energy guzzling assets

Grab an instant overview of all assets, locations and energy meters using Xempla’s asset mapping capabilities. Help energy managers and facility management teams pinpoint and optimize assets or spaces consuming the highest amount of energy, as well as assets that are consuming more energy than they should.

Run proactive energy saving and efficiency programs

Through workflows that alert on potential overuse of energy across assets, facilitate faster resolution and continued impact. Move closer to your portfolio sustainability and net zero targets by proactively saving energy and boosting your building’s energy performance, one asset at a time.

proactive energy management

Energy Management Case Studies

See how Xempla helps you optimize your energy performance for different assets through these micro case studies.

Micro case study

Increased Thermal Energy (Heating And Cooling)

This algorithm checks for consumption of thermal energy across an AHU on the basis of ambience and in-room conditions. It uses forecasting models to determine if thermal energy consumption is in line with expected values. If not, it triggers an alert.

Asset Class: AHU

Upon investigation it was found out that the Supply RH Sensor was faulty, causing the AHU to operate under a false “high humidity” alarm and fully opening chilled water valves, resulting in over 60% increase in thermal energy consumption.

energy optimization
Increase thermal energy
Micro case study

Cooling Tower Fan

This algorithm uses a backcasting method to determine the control speed feedback to CT Fan and alerts teams if there is an optimization possibility, resulting in energy savings.

Asset Class: Cooling Tower

Investigation revealed that the way the BMS controls were set, even a minor change in CT Water Outlet Temp would cause the CT Fan to work at max levels.

FM O&M Team is now working on further tweaking the control strategy, without impacting thermal comfort which would yield electrical energy savings of around 20% on each CT Fan.

Additional Resources

cooling tower fan

Predictive analytics for energy management and sustainable building operations

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operations & maintenance

Are FMs prepared for proposed Minimum Energy Efficiency Standards in the UK?

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Condition based maintenance

Sustainable buildings: A Magnet for investors and tenants as well

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