MSc / BSc – internship Tauw BV
Optimizing thermal energy storage in groundwater
Contact Prof. Olsthoorn, Room 4.87 Mondays and Thursdays, t.n.olsthoorn@tudelft.nl, 06-20440256
Figure 1, TES-system
Background
Thermal energy storage (TES) in groundwater is booming in the Netherlands. Every year more and
more big and small TES-systems are (and will be) installed. From environmental and economic point
of view this is a positive development since these systems lead to a significant reduction in primary
energy consumption and thus also reduce CO2 emissions. This also explains the popularity of the
systems, it reduces costs and it has a sustainable image. Because of this the development of the TESsystems should be further encouraged.
The extracted groundwater used for heating or cooling may vary in temperature during an extraction
period. This is caused by the (combinations of) different factors; heterogeneity of aquifers,
groundwater flow, surface water and other (TES) extractions or infiltrations. The varying temperature
reduces the efficiency of the TES system. With models often predictions are made to forecast the TES
behaviour but the current modelling equipment does not perform at a suitable level of scale and
accuracy.
The plan
The efficiency of the TES system can be improved with a real-time monitoring system combined with
interpretation system. With these systems the condition (size, position, and form) of the TES can be
determined adequate and efficient. With this information the planning and use of the TES can be
adapted to get an optimal efficiency from the TES-system; you know how much energy is available at
any moment.
To be able to optimize the use of TES-systems a lot of information is needed; transmissivity, head,
different types of layers, natural groundwater flow, groundwater temperature etc. Most effective
available parameters which can be measured (almost) continuously are head and temperature around
the bore holes. Today it is possible to measure temperature with a fibreglass cable by winding the
cable around the borehole (fig. 2) a very dense observation network is established along and on every
side of the borehole.
When data is measured it should be interpreted. The measurement data must be coupled with an
operational groundwater model which contains a detailed description of the subsurface. Also Finite
Element modelling appears to be most suitable type of model. The model performance will improve
because of the continuous calibration with the data of groundwater temperature and head.
Tauw BV
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Dec 2007
Figure 2: TES well with wound
glass fibre temperature cable and
6 monitoring pipes. 3 are in the
gravel pack opposite the well
screen. 1 is above the screen and
1 below but in the aquifer to
measure the head outside the
gravel pack (to measure borehole
clogging) and one is in the
aquitard above the target aquifer
to signal well failure. In plan
view, the 3 lower observation
screens are in 120 different
compass directions to allow
measuring direction of
groundwater flow, the other 3
screens are in intermediated
compass directions without
special preference.
The challenge
In order to get this project started a research plan should be written. In this plan should be elaborated
what is needed to carry out the monitoring and interpretation as described above, which things should
be investigated first and where are the risks and/or crucial elements in this research?
Research questions monitoring system:

Design of temperature logging, theoretical and practical. How to log, register and make the
data online available as useful information to the operators as well as to the model

Design and development of mounting and securing the temperature cable and logging device.

Design and development of monitoring groundwater flow velocity and direction.

Design and development of monitoring well performance and KWO performance

Design of field data acquisition and translating to online monitoring
Research questions interpretation system:

Determine which models are presently available, feasible (cost, complexity, access to source
code) and suitable as an engine for our problem

Develop the model such that it is suitable for designing KWO systems given the detailed
subsurface information.

Develop and simulate how to calibrate and continuously improve the calibration while the
model is fed with online data from a real well.

Test the model using available information. Look worldwide.

Determine what detail of information is necessary to draw most benefit from it in a real KWO
system.
The research questions stated above can probably not all be investigated in one research. We are
looking for students who want to contribute in this research and take on one or more of the research
questions stated above.
T.N.Olsthoorn@tudelft.nl
Tauw BV
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Dec 2007