Applied Data Analysis in Energy Monitoring System

Software and hardware system organization is presented as an example for building energy monitoring of multi-sectional lighting and climate control / conditioning needs. System key feature is applied office energy data analysis that allows to provide each type of hardware localized work mode recognition. It is based on general energy consumption profile with following energy consumption and workload evaluation. Applied data analysis includes primary data processing block, smoothing filter, time stamp identification block, clusterization and classification blocks, state change detection block, statistical data calculation block. Time slot consumed energy value and slot time stamp are taken as work mode classification main parameters. Energy data applied analysis with HIL and OpenJEVis visualization system usage experimental research results for chosen time period has been provided. Energy consumption, workload calculation and eight different states identification has been executed for two lighting sections and one climate control / conditioning emulating system by integral energy consumption profile. Research has been supported by university internal grant №2016/PI-2 "Methodology development of monitoring and heat flow utilization as low potential company energy sources".