![](bg1.png)
Adaptive Knowledge Representation for a
Self-Managing Home Energy Usage System
Martijn Warnier
1
, Marten van Sinderen
2
and Frances M.T. Brazier
1
1
Faculty Technology, Policy and Management
Delft University of Technology, The Netherlands
2
Faculty of Electrical Engineering, Mathematics and Computer Science
University of Twente, The Netherlands
M.E.Warnier@tudelft.nl,
m.j.vansinderen@ewi.utwente.nl,F.M.Brazier@tudelft.nl
Abstract. Automated and efficient energy management has many potential ben-
efits for producers and consumers of energy, and the environment. Focusing on
energy management on the consumer side, this paper considers two forms of en-
ergy management: minimizing energy usage in single households and avoiding
peaks in energy consumption in a larger area.
A combination of context aware and autonomic computing is used to describe
an automated and self-managing system that, by analyzing context information
and adapting to its environment, can learn the behavior of household occupants.
Based on this information, together with user defined policies, energy usage is
lowered by selectively powering down devices. By powering specific thermostat-
ically controlled devices on or off energy can also be redistributed over time. This
is utilized to avoid global peaks in energy usage.
The self-managing system reasons about context and other information and acts
when required. This information is the knowledge with which it can adaptively
reason, about to take to ensure efficient energy usage. This paper explores the
requirements that hold for representing this knowledge and how the knowledge
base can continuously and adaptively be updated: to be self-managing.
1 Introduction
Efficient energy management forms an important challenge in today’s society as con-
ventional energy sources become more and more scarce and more eco-friendly alterna-
tives are not yet evaluated at a large scale. Automated approaches to efficient energy
management are currently still limited and mostly used by large power consumers such
as factories [10, 16, 17], but with the advancement of the Smart Grid [2] and other re-
cent advancements in sensor networks [1, 19], such as cognitive networks [18], this
changes rapidly.
This paper addresses this challenge at two different, and possibly conflicting, levels:
(i) at the level of a single household, where the goal is to lower energy consumption and
(ii) at the level of group of households (a neighbourhood), where the goal is to lower
peak usage in energy consumption. In [15] a new approach based on autonomic and
context aware computing is introduced. This paper extends that approach. It explores
Warnier M., van Sinderen M. and van Sinderen M.
Adaptive Knowledge Representation for a Self-Managing Home Energy Usage System.
DOI: 10.5220/0004465901310140
In Proceedings of the 4th International Workshop on Enterprise Systems and Technology (I-WEST 2010), pages 131-140
ISBN: 978-989-8425-44-7
Copyright
c
2010 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved