How can T@ENERGY industrial energy management systems help companies identify abnormal electricity usage?

 

Industrial enterprises power consumption is more complex and their electricity management is generally more chaotic. How to find abnormal electricity is more headache for business managers. Some are due to equipment failure, some are due to special production needs, and a large part is caused by personnel habits. So is there any good way to quickly identify abnormal power usage?
 
Here is a case study on how to use the "operation analysis" function of the T@ENERGY industrial energy management system to detect abnormal power consumption during non-working hours.
 

 

Set up statistical rules. Set up different time periods for energy use analysis according to the actual working hours of industrial enterprises (you can also create multiple statistical rules according to actual needs).
 

 (The working hours are set from 6:00 to 24:00, and the closing hours are set from 0:00 to 5:00)
 

Observe data changes. In the "Consumption Unit - Operation Analysis" module, select the daily data to observe the change of data in the last week.
 

 

 

Find the anomalies. The histograms and charts can be used to find that the off-work hours energy consumption on September 23 is greater than the week's average energy consumption: 
 

Search along the way. Determine the abnormal energy use sector by the change of energy consumption ranking before and after two days. The power consumption ranking of the embedded team of R&D department, which was ranking in the 4th on the Sept. 22nd and rose to 2nd on the Sept. 23rd, with about 5kWh more. By comparing the energy consumption by the embedded team of R&D department, it was found that the energy used for the lab was about 6kWh more than the previous day, and then further analyzing the energy consumption of the lab, it was found that the air conditioner for the lab was 6kWh more than the previous day. It could be initially confirmed that the air conditioner for the lab was not turned off during non-working hours.
 

Confirmation of abnormal energy use. According to "Energy Monitoring-Historical Data" to further confirm the abnormal power consumption node. The abnormal energy consumption on Sept. 23rd was indeed caused by the equipment of "Embedded team-Lab-Air Conditioner" which was not turned off. After pulling the data from Sept. 22nd to September 23rd, it was found that the air conditioner in the embedded R&D lab was turned on at 10:00 a.m. on Sept. 22nd and turned off at 17:35 p.m. on Sept 23rd. 

Current Amp data of Sept. 22^nd and 23^rd

Determine the person to be responsible. After the problem is found, the company can implement the relevant responsibility to the relevant person in charge of that lab according to the relevant management system.