Design and Optimization of an Energy Manager for an Office Building

Majetta, Kristin; Clauß, Christoph; Haufe, Jürgen; Seidel, Stephan; Blochwitz, Torsten; Liebold, Edgar; Hintzen, Ullrich; Klostermann, Volker

doi:10.11128/sne.25.tn.10297

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This knowledge about the durations for heating up and cooling down the room is used by the predictive controller to determine the points in time for turning the heating system on and off in order to achieve a certain room temperature. Details about the functioning of the predictive controller can be found in [14].…”

Section: Controller Modelsmentioning

confidence: 99%

Provision of Data to Use in Artificial Intelligence Algorithms for Single Room Heating

2021

Self Cite

View full text Add to dashboard Cite

This paper describes a way to generate a great amount of data and to use it to find a relation between a room controller and a certain room. Therefore, simulation scenarios are defined and developed that contain different room, location, usage and controller models. With parameter variation and optimization of the corresponding controller parameters a data basis is created with about 5300 entries. On the basis of this data, machine learning algorithms like artificial neural networks can be used to investigate the relation between rooms and their best suited controllers.

show abstract

Section: Controller Modelsmentioning

confidence: 99%

Provision of Data to Use in Artificial Intelligence Algorithms for Single Room Heating

2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…As discussed in section 4.2 a possible solution would be an intelligent controller or BEMS algorithm. An approach to find a solution to this task was developed in this project as well and is discussed in (Majetta, 2015). 3.…”

Section: Combined Energy and Building Modelmentioning

confidence: 99%

Modelica based Design and Optimisation of Control Systems for Solar Heat Systems and Low Energy Buildings

Seidel

Clauß

Haufe

et al. 2015

Linköping Electronic Conference Proceedings

Self Cite

View full text Add to dashboard Cite

The goal of the research project enerMAT is the reduction of energy consumption and CO2 emissions of buildings. Especially solar heating systems are installed in more and more buildings. This paper introduces a novel approach for simulation and optimisation that aims to improve the performance of building controllers and especially solar heating controllers by simulation and model-in-the-loop tests. A new generation of energy-aware optimised building energy management systems (BEMS) will be discussed and its advantages over the older controllers highlighted. The energy-aware optimisation will be shown on a model-based approach with an overall building system model enabling the assessment of the energy performance for different design and operation alternatives of the building automation system in interaction with the building. This system model will allow a simulation-based, energy-aware, global, dynamic, multi-criterial optimisation of BEMS. In this paper, the idea, the approach, and the actual state of the project research is presented with a focus on solar heating controllers.

show abstract

Design and Optimization of an Energy Manager for an Office Building

Abstract: dynamic, multi-criterial optimization of the energy manager. In this paper, the idea, the modeling of an office building and its energy manager and different optimization studies and their results are presented.

Cited by 2 publications

References 0 publications

Provision of Data to Use in Artificial Intelligence Algorithms for Single Room Heating

Provision of Data to Use in Artificial Intelligence Algorithms for Single Room Heating

Modelica based Design and Optimisation of Control Systems for Solar Heat Systems and Low Energy Buildings

Contact Info

Product

Resources

About