Peachtree

Green with a Payback

The Problem

An existing office location has an existing infrastructure to control climate. The challenge faced was to save power consumption for heating and cooling by introducing a predictive presence schedule, and to proove a reasonable payback time by re-using existing infrastructure and limiting any new investments in hardware.

Workflow Solution

By adding a single presence sensor, the office hours were predicted on a daily basis. Based on this predicted schedule, the office heating and cooling are set from night mode to eco-mode an hour ahead of the predicted arrival and increased to setpoint temperature at the actual moment of entering. The office users can see the predicted arrival time and change it if needed.

Graphical User Interface

The user can set his preferred setpoints and always monitor his expected arrival time. If he has regular office hours he will not need the mobile app anymore. In case he plans to go to office early he can always change the schedule for the single day and telling the system he will arrive an hour early. In addition for maintenance purpose, he can report if the data he sees is incorrect.

System Intelligence

The main logic implemented is a rules set which adjusts the office hours schedule based on actual presence on a daily basis. For each individual day a new arrival time and departure time is defined, ignoring short absence periods. The predicted schedule is based on an weighted average over the last couple of weeks, ignoring holiday periods.

Connected Data

The building already had an existing BMS system and therefore didn’t require any hardware investment accept for a server running OpenRemote. The BMS offered an HTTP based API. OpenRemote added the predictive model as well as transparent communication to the office user, allowing an additional energy saving while remaining satisfaction levels of the user.

How We Helped

We supported the installation of the OpenRemote manager, defining the rules for the schedule prediction and the calculations to determine the additional cost savings. The front-end application was designed, implemented and tested with the office users.

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