Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.

  

Management Controller for Room Automation of a Real Building

Student(en):

Betreuer:

Georgios Darivianakis, Raphael Schaer, Angelos Georghiou, Annika Eichler
Beschreibung:

Overview

An increase in energy use efficiency is a key to reducing our dependency on fossil fuels and limiting of worldwide CO2 emissions. Approximately 40% of the global used energy is consumed in buildings, of which roughly half is used for Heating, Ventilation and Air Conditioning (HVAC). At the same time, most investments in building energy efficiency can be expected to pay back through reduced energy bills.

Improved HVAC control is particularly interesting because of the relatively low cost of improved control solutions as compared to other refurbishments in buildings, the comparatively short (10-15 years) lifetime of HVAC systems, and, last but not least, thanks to advances in sensor networks and information technologies that open up entirely new opportunities for advanced building control. Challenges relate to the uniqueness of many buildings, the possible complexity of their technical systems, and the building industry’s fragmentation.

Project Description

For research purposes, SAUTER has equipped one of the company buildings called Bau 10 with several sensors and data acquisitions equipment for system identification. The building consists of two seminar rooms where both are equipped with radiators and an air conditioning system. In a previous Master Thesis, the heating system of this building has been identified and an MPC has been designed and successfully applied.

The aim of this Master Thesis is to design an MPC that is located on the management level according to the automation pyramid. The controller computes the set points for the heating system and room control, which are designed as PI controllers. The set point is based on the current and future condition of the rooms (presence, temperature, solar radiation etc.)



Weitere Informationen
Professor:

Roy Smith
Projektcharakteristik:

Typ:
Art der Arbeit:
Voraussetzungen: Model Predictive Control, System Identification, MATLAB, LabVIEW
Anzahl StudentInnen: 1
Status: done
Projektstart: Spring Semester 2016
Semester: