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Monitoring energy consumption in real-time
- Collecting and storing data on energy consumption, climatic parameters and facility activity on a per second basis
- Recognition of typical power consumption profiles based on machine learning methods
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Analysis of gathered data
- Automatic detection of abnormal and atypical equipment behavior
- Search for the most promising optimization options (based on data accumulated at previous facilities)
- Building a prediction model to forecast the dynamics of consumption throughout the day/week/season
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Construction of a two-level automatic load control system
- The internal control loop is based on a PID regulator, provides an acceptable level of control and remains operational in the absence of an internet connection
- The outer control loop is based on Deep reinforcement learning and adjusts the parameters of the inner control loop to maximize equipment performance
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Technology EnCM
is a complex hardware and
service solution for managing
energy consumption of varying facilities.
Our system works in the ideology of IoT -
the Internet of Things, allowing
a facility’s network of physical
devices equipped with communication
technologies to interact with
each other and with the surrounding
environment without the need
for manual control.
is a complex hardware and
service solution for managing
energy consumption of varying facilities.
Our system works in the ideology of IoT -
the Internet of Things, allowing
a facility’s network of physical devices
equipped with communication
technologies to interact with
each other and with the surrounding
environment without the need
for manual control.
EnCM system components
How it works:
Data is collected at a facility to establish the
state of devices, climate and activity. EnCM uses
the Modbus data transfer protocol, implemented
through physical twisted pair wire or a wireless
connection based on WiFi, ZigBee, Z-wave and other protocols.
Big Data – hundreds of the parameters of the object
Voltage
Amperage
Power output
Phase Angle
Frequency
Status of the devices
Temperature
Humidity
Illumination level
CO2
Heat dissipation of devices
Temperature
Pressure
Forecast
Humidity
Solar radiation
Cloud cover
Motion sensor
Noise sensor
Gas consumption
Water consumption
Thermal energy consumption
Air flow in the ventilation system
Data from a CRM or accounting system
Data is transferred to our MQTT broker,
processed, sorted and stored with timestamps
at a maximum resolution frequency.
Multiple backups are organized in a cloud
database hosted in secure data centers.
