Traditionally, energy management in the residential and civil industry using ICT focuses on consumption assessment. In this experiment, an analysis and management of energy consumption in buildings through CPS is carried out. Furthermore, a dynamic control of the physical machines in the field is being implemented to increase the efficiency of the energy usage.

Evogy, with its Building Energy Management System (BEMS)  platform (SimonLab), aims to optimize buildings energy consumption,  maintaining at the same time the occupants’ comfort. SimonLab is a cloud-based software platform built on IoT and AI technologies.

In this experiment, a CPS for an outpatient polyclinic is being developed. Temperature, humidity and the CO2 concentration sensors, as well as electrical metering devices, have been installed inside the building to collect the instantaneous comfort condition and current energy consumption respectively. Through a gateway, the sensor readings are sent to the IoT platform in the cloud database, where they are enriched with third parties data, like weather forecasts and the energy prices.

SimonLab offers a flexible dashboard for dynamic and a real-time data analysis. Several features are expected to be embedded with the overall CPS implementation, such as monitoring, anomaly detection, remote machine configuration and ultimately the dynamic control of the equipment.

Currently, the data are being analysed to model and simulate the building thermal behaviour and study anomaly detection algorithms.  Based on these models, a controller will be designed to optimize the energy usage, reducing wastes.