Energis allows to execute automatically actions to save energy and does the optimisations continuously instead of having periodic optimisations done by specialists.

Features

• Configuration of remote commands to switch on/off devices
• Configuration of optimisation logic
• Execution of commands according to optimisation logic

Energis measures the real savings of projects and actions with high accuracy by using AI (Artificial Intelligence) techniques and by evaluating the results according to EVO’s International Performance Measurement and Verification Protocol®. With just a few clicks, the user uploads data files containing historical consumption data and other relevant variables in a predefined format. This ‘baseline’ data covers the period before energy saving measures were implemented and is used to calculate the baseline energy model. This model can be applied to different time periods to explicitly calculate the avoided energy cost due to the various energy savings actions undertaken.

Features

• Usage of diversity of energy, activity and system related data
• Identification of the best site-specific model and key independent variables that most affect energy consumption.
• Assessment of the model against the IPMVP® criteria
• Usage of the model at the required frequency i.e. hourly, daily, weekly and monthly usage
• Alerts, dashboards and reports rely on these model for permanent savings verification

Energis allows permanent monitoring of the energy performance of sites. It calculates continuously the expected consumptions of the sites and its site entities such as the heating, cooling, ventilation and lighting systems. Energis sends automatically Smart Alerts when there is over-consumption and the actual consumption differs significantly from the expected consumption. It goes further than generating simple alerts when given thresholds are reached.

Features

• Flexible collection and storage of variety of data
• Inventory of all energy related assets
• One click identification of energy efficiency models
• Proactive alerting in case of deviations from the expected consumptions
• Dashboards and views adapted to the end-users expectations and context