An exciting project called 'Smart Energy @ Home' is underway in the
Danish municipality of Middelfart, where access to data - including
public data - plays a key role.
The focus of the project is to develop scalable methods to help
homeowners save energy without sacrificing comfort.
This is done by examining how much energy 2-300 homes can save by
installing intelligent energy management and receive remote counseling.
Denmark has a political target that electricity and heat in 2035 will
be produced with 100 % renewable energy. In this context, it is a base
assumption that the total requirement for heating - in spite of new
buildings - must be cut in half by 2050.
But even if we look twenty years ahead from now more than 70% of the
building stock will consist of homes that are already built today.
These buildings have a much higher consumption energy than the
buildings that we build today and that will be built in the future. It
is therefore in the established housing the largest energy savings are
to be realized in order to achieve the goal of full phase-out of
The Danish Building Research Institute has estimated that 200 billion
Danish kroner must be invested to halve heat consumption in existing buildings.
To nudge homeowners volunteer to make the necessary investments in
order to halve energy consumption for heating there is a need for very
active and educational counseling and a wide range of credible energy
efficiency services offerings.
Against this background, the project goal is to develop and
demonstrate new concepts and offers to homeowners which proves that
smart energy in the home for the measurement and control of heating
systems in combination with a resource efficient customer dialogue and
counseling to homeowners provides:
- Verifiable and sustained "automatic" savings and
- Activate homeowners and increases their desire to change
consumption behavior and implement new energy investments.
Intelligent energy management
The home automation system used in the project is called PassivLiving
and is developed by PassivSystems, a leader in energy optimization of
PassivLiving lowers the temperature in the house when the occupants
are not at home during the day, when they are on vacation, or when
they go to bed. And the system also ensures that the temperature is
turned up again when needed.
In contrast to standard time control of heating systems the residents
do not have to guess how many hours the heating systems must be on for
their house to reach the desired temperature, when they get up in the
morning and come home in the afternoon. This adjusts PassivLiving
itself, so all that’s needed is to specify the temperature desired in
the house at which time. PassivLiving is being installed in 2-300
houses in Middelfart municipality.
The remote counseling will try out new IT-based concepts for user
involvement and resource-efficient advice, where measurements and
advanced algorithms provide energy advisors and homeowners a
particularly good basis for assessing possible measures for energy
optimization of the property.
The goal is to make it better and cheaper than traditional energy consultancy.
- Better - because there is access to specific and detailed data on
the condition of the building and its dynamic energy consumption.
- Cheaper - because there is no requirement for an an expensive
consultant to inspect the property on-site.
From data to value
The diagram below illustrates the relationship between the individual
homes, the various data sources and the remote counseling service in
A wide range of data concerning home energy consumption are measured, including
- Energy input to the home heating system (remotely read in
conjunction with the relevant utility where possible)
- Amount of heating water produced
- Hot water consumption
- The homes temperature
These measurement data are supplemented by a number of other data
that are relevant to the home including
- Weather-measurements and forecasts – made available to the project
by the Danish Meteorological Institute
- Building and Housing Register (BBR), public data about building
size, type of accommodation, historical energy consumption, etc.
- Additional master data for the property, such as number of
occupants and their age, already completed renovations such as
window replacements, etc. - This data is gathered through
questionnaires or from other registries
By combining these data sources much useful information can be
derived about each individual property, eg
- The thermal profile of the house
- The efficiency of the heating system
- Key figures for heating consumption of kWh per square meter and
kWh per occupant and comparison with the average for homes of
- Household behavior in relation to family life, housing type, etc.,
which can be used to consider different customized smart energy
solutions to various segments of residents and types of buildings.
- The heating or cooling rate for the house, in conjunction with
The last bullet can give specific information about which parts of
the house that can benefit from forms of insulation – for example if
it is determined that the house is cooling faster than usual by strong
easterly winds, it appears beneficial to insulate the cavity wall or
replace the windows on the east side of the house.
Similarly, knowledge of the heating rate by sunlight combined with
weather forecasts can be used to control heating - so the heat
production is turned down when there is a prospect of sunshine.
The above examples provide a good illustration of the possibilities
that arise from being able to combine different detailed data sources
with an hourly or daily granularity.
Note - this is not just interesting knowledge, this is information
that motivates and provides actionable knowledge to homeowners about
what kind of improvements and behavioral changes that can reduce
energy consumption in the home of this individual home owner.
In the above example, access to public data in the form of weather
reports and forecasts is critical to provide the necessary basis for
cost-effective decision making.
Similarly, there are many other public data sources such as the BBR
registry and other registry information which in conjunction with easy
access to home consumption data, enables the creation of new
innovative greentech solutions.
The ‘smart energy @ home’ project kicked off in 2012 and will run
through three heating seasons until 2015.
The project is made possible through a grant from Realdania - a
philantropic association supporting projects in the built environment
– and supplemented by investment from the project partners in terms of
hours and/or money. The project partners are beyond Realdania:
- Middelfart Municipality, pursuing an ambitious strategy for green growth
- PassivSystems provides the leading edge home automation system used
- Bolius – The homeowners Knowledge Center is responsible for for
the remote counseling and ongoing knowledge transfer to the
- Danish Building Research Institute (SBi) process and analyze the
data collected in the project from a research perspective.
You can read more – in Danish – about smart energy @ home at www.seih.dk