Small or medium-scale focused research project (STREP)
FP7-SMARTCITIES-2013
ICT-2013.6.4 Optimizing Energy Systems in Smart Cities
District Information Modeling and Management
for Energy Reduction
DIMMER
Project Duration: 2013.10.01 – 2016.09.30
Grant Agreement number: 609084
Collaborative Project
WP1 Polito
D1.3.1 Energy auditing: report
Prepared by DIMMER Collaboration Submission date Due date Nature of the deliverable R P D O
Dissemination level PU PP RE CO
Project Coordinator: Prof. Enrico Macii, Politecnico di Torino
Tel: +39 011 564 7074
Fax: +39 011 564 7090
E mail: [email protected]
Project website address: http://dimmer.polito.it
DIMMER
D1.3.1 – Energy auditing: report 2
REVISION HISTORY
Date Version Author/Contributor1 Comments
2014.03.15 V01 Polito / Iren Initial Structure for comment
2014.03.19 V02 Iren Contribution
2014.03.26 V03 Arup Contribution
2014.03.27 V04 Polito Ready for Review
2014.03.28 V05a Clicks and Links Reviewed
2014.03.28 V05b CSI Reviewed
2014.03.29 V06 Polito Comments incorpored
2014.03.30 V07 University of Manchester Reviewed, approved with minor changes
2014.03.31 V08 Polito Comments incorpored.
2014.04.01 V09 Polito Ready for comments
2014.04.02 V10 Polito Final version
1 Partner, Name Surname
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D1.3.1 – Energy auditing: report 3
COPYRIGHT
This project has received funding from the European Union’s Seventh Framework Programme for research, technological
development and demonstration under grant agreement n° 609084.
© Copyright 2013 DIMMER Consortium consisting of
This document may not be copied, reproduced, or modified in whole or in part for any purpose without written
permission from the DIMMER Consortium. In addition to such written permission to copy, reproduce, or modify this
document in whole or part, an acknowledgement of the authors of the document and all applicable portions of the
copyright notice must be clearly referenced.
All rights reserved.
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TABLE OF CONTENTS
Revision History .............................................................................................................................. 2
Copyright ........................................................................................................................................ 3
Table of Contents ............................................................................................................................ 4
List of Figures .................................................................................................................................. 5
List of Tables ................................................................................................................................... 5
Abbreviations ................................................................................................................................. 6
Definitions ...................................................................................................................................... 6
Executive summary ......................................................................................................................... 7
Introduction .................................................................................................................................... 8
1. Measurements in the Turin District ........................................................................................... 9
1.1. Goals of the analysis ................................................................................................................................................. 9
1.2. Measurements at the heat exchangers ................................................................................................................... 9
1.3. Measurements at building level ............................................................................................................................. 11
1.3.1. Analysis of the buildings ................................................................................................................................ 11
1.3.2. Measurement of internal temperature ......................................................................................................... 13
1.4. Measurements in the network ............................................................................................................................... 16
2. Measurements in the Manchester District .............................................................................. 19
2.1. Goals of the analysis ............................................................................................................................................... 19
2.2. Measurements ....................................................................................................................................................... 20
3. Links to Subsequent WP1 Tasks .............................................................................................. 21
4. Conclusions ............................................................................................................................ 21
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LIST OF FIGURES
Figure 1 – Schematic of the measurements at the heat exchanger in a thermal substation .................................................... 9
Figure 2 – Evaluation of the product UA for two heat exchangers .......................................................................................... 10
Figure 3 – Thermal request profile of a user ............................................................................................................................ 11
Figure 4 – Thermal request profile of a user ............................................................................................................................ 12
Figure 5 – Transient behavior of the system ............................................................................................................................ 12
Figure 6 – View of the building – via Braccini 63 ..................................................................................................................... 14
Figure 7 – Building map – via Braccini 63 ................................................................................................................................ 15
Figure 8 – Sensors in rooms ..................................................................................................................................................... 16
Figure 9 – Schematic of the Turin district heating network ..................................................................................................... 17
Figure 10 – Heat load of the thermal plants in a typical winter day ........................................................................................ 17
Figure 11 – Manchester Oxford Road Corridor selected buildings (shaded blue) and electricity network (red cables and
yellow infrastructure) .............................................................................................................................................................. 19
Figure 12 – Example single converged data network: Representative of the University of Manchester ................................. 20
LIST OF TABLES
Table 1 – List of measurements required to evaluate the operating conditions of the heat exchangers ................................ 10
Table 2 – List of measurements required to evaluate the behavior of a building .................................................................... 13
Table 3 – List of measurements required to evaluate primary energy consumptions and savings ......................................... 18
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ABBREVIATIONS
Acronym/Symbols Full name
A
c
DH
Heat transfer area
Specific heat
District heating
k
kV
Global heat transfer coefficient of building
kilovolt
m
t
T
U
V
Mass flow rate
time
Temperature
Global heat transfer coefficient
Volume
Φ Heat flux
DEFINITIONS
Term Full name
District Subject or pilot area of enquiry
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D1.3.1 – Energy auditing: report 7
EXECUTIVE SUMMARY
Milestone M1.3 aims at measuring the quantities that are necessary to characterize the energy performance of the
selected buildings as well as the possible savings. In particular, this deliverable presents the selection of the various
quantities to be measured and the methodology to perform the measurements. Some preliminary measurements that
have already been operated are presented.
The document is organized in two main sections:
• The first one describes the measurements performed in the buildings considered in the Turin district.
Measurements refer to the heat consumption of buildings connected with the district heating network as well as
internal temperatures in the buildings. Measurements in the network are also operated in order to obtain and
evaluate of primary energy consumptions.
• The second one describes measurement in the Manchester districts. These measurements refer to consumption
of gas, heat and electricity.
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INTRODUCTION
The DIMMER project considers districts characterized by heterogeneous buildings and users: public (schools, university
campus, office, etc.) and private (mainly house). The energy demand in this area is variable in time and depends on the
type of buildings and the type of users. Real-time sensors are crucial to characterize the behavior of buildings and enable a
more efficient distribution of the district heating/cooling energy. In addition, the real time information about users’
behavior and energy consumption profiles allows the implementation of strategies aiming at shifting the energy
consumption to periods when a large share of renewables is available or when more efficient use of fossil fuel is possible
(e.g. large share of cogeneration). Finally, this information allows to suggest possible personalized best practices related to
the installation/use of renewable energy or devices such as thermal storage systems.
Measurements are therefore crucial for the implementation of the DIMMER project. The measurement system in the two
districts consists of sensors that were previously installed and others that will be installed in the next few months. In this
document, the measurements that will be operated are described. The application of measurements to the evaluation of
some of the quantities that describe the buildings’ behavior or their energy performance is also discussed.
In the next sections, measurements that will be operated in the two districts are discussed. In the Turin district,
measurements mainly refer to the heat request of the buildings connected to the district heating network. In the
Manchester district, measurements refer to the consumption of gas, heat and electricity. Data acquisition in the
Manchester district presents additional difficulties and further discussion is necessary. For this reason, details will be
provided in the successive deliverables in M1.3.
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1. MEASUREMENTS IN THE TURIN DISTRICT
1.1.Goals of the analysis
The main goals of the analysis that are operated in the Turin District are listed below:
1) Evaluation of the degree of fouling of the heat exchangers in the various substations. This piece of information is
particularly important to increase the effectiveness of the heat exchanger, in fact fouling causes increase in the
water temperature exiting the heat exchanger on the DH network side, therefore lower efficiency of the thermal
plants. In addition, effective implementation of some of the actions that are discussed hereafter requires efficient
heat exchangers.
2) Evaluation of the thermal behavior of the buildings connected with the network and possible implementation of
variation in the thermal request profiles. Buildings will be characterized in terms of global heat transfer
coefficient and time response constant. An evaluation of the thermal distribution inside some of the buildings will
be also performed and will be related with the geometry of the buildings. These pieces of information will be
included in a compact model of the buildings, which will be used to identify the buildings where possible changes
in the thermal request profile may be operated. These changes include variation in the set points of the
substation (values and/or start time and stop time) and installation of local heat storage devices.
3) Evaluation of the effects of variation of thermal profiles on the primary energy consumption. This involves
thermo fluid dynamic simulation of the network in order to obtain how variations of the thermal request of the
users affect the operation of thermal plants.
1.2.Measurements at the heat exchangers
Heat exchangers in the district heating network are equipped with appropriate sensors to measure the water mass flow
rate that is supplied to the user on the secondary network together with three temperatures: the inlet (T1) and outlet (T2)
temperatures on the secondary network and the temperature of water supplied to the heating devices (T3). A fourth
thermal sensor, which measures the temperature of water entering the heat exchanger on the building network side, has
been already installed in various users and its installation is currently progressing.
Figure 1 – Schematic of the measurements at the heat exchanger in a thermal substation
Using the first three measurements it is possible to obtain the heat flux Φ that is requested by the user, assuming the heat
losses in the heat exchanger as negligible:
( )21 TTcm −⋅⋅=Φ
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D1.3.1 – Energy auditing: report 10
where c is the water specific heat. The mass flow rate mb on the building network is obtained as
( )43 TTcmb −⋅
Φ=
The fouling grade of the heat exchanger can be evaluated starting from the analysis of the heat exchange at the
substation, namely given by the product of the heat transfer surface A times the global heat transfer coefficient U, which
is calculated as:
log,mTUA
∆Φ=
where
( ) ( )( )( )42
31
4231log,
lnTT
TTTTTT
Tm
−−
−−−=∆
The evaluation of the terms UA for two similar users connected with the network for the purposes of assessing the effect
of potential fouling in the heat exchanger is proposed in the next figure. User a is characterized by a larger nominal
thermal request (about 20% larger) than the user b, but the product UA is about double. This can be justified by fouling in
the heat exchanger of user b. In addition, time monitoring of these quantities is crucial to discover malfunctions and to
apply proper management strategies.
Figure 2 – Evaluation of the product UA for two heat exchangers
The following table summarizes the measurements that are necessary to evaluate the fouling grade of the heat
exchangers.
Table 1 – List of measurements required to evaluate the operating conditions of the heat exchangers
Water mass flow rate supplied by the district heating network to the examined user
(secondary network)
Temperature of water entering the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the user network
Temperature of water entering the heat exchanger on the user network
0
0.05
0.1
0.15
0 500 1000 1500 2000 2500
UA [W/K] SST 079_524
Probability density UA
0
0.02
0.04
0.06
0.08
0 1000 2000 3000 4000 5000
UA [W/K] SST 492_178
Probability density UA
a b
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1.3.Measurements at building level
This paragraph is split in two parts: the first one refers to the measurements that are performed using the sensors already
installed at the heat exchangers, while the second part refers to the installations of temperature sensors in the buildings.
1.3.1. Analysis of the buildings
Each building will be characterized by two quantities: an average internal temperature and a temperature distribution, i.e.
the difference between maximum and minimum temperature. The first quantity can be obtained from measurements that
are performed at the heat exchanger. This is used as a reference quantity to apply possible variations in the time profile of
the heat request, assuming that any variation that produces variations within the same limits that are registered without
variation is acceptable.
To evaluate the average temperature, buildings are modeled as:
t
TcVloss ∂
∂=Φ−Φ
where Φloss represents the heat losses of the building
When the afternoon operation is considered, typically steady state conditions are reached, as shown by the flat heat
demand curve in the afternoon hours in the following figure.
Figure 3 – Thermal request profile of a user
In these conditions, it is possible to write
( )extinloss TTkV −=Φ=Φ
which has two unknowns: the global heat transfer coefficient of the building k and the average internal temperature Tin.
Nevertheless, a sensitivity analysis performed using seasonal data allows one to evaluate the best value of k.
The following figure shows a linear correlation between the external temperature and the thermal request in the
afternoon, which can be used to evaluate the global heat transfer coefficient.
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Figure 4 – Thermal request profile of a user
Moreover, measurements of the internal temperatures allow one to check the resulting values of the internal
temperatures.
Concerning transient behavior of the buildings, this will be evaluated when the heating plant does not require heating
from the district heating network but the circulating pump on the user side is still operating.
In the figure, the evolution of the difference between fluid temperature in the building network returning to the heat
exchanger and the external temperature is shown (dot points). The theoretical exponential evolution is also shown. The
difference registered after 30 minutes is due to the circulating pump which is switched off.
Figure 5 – Transient behavior of the system
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The second quantity can be obtained from specific measurements inside the buildings. This is used in order to highlight
possible excess temperatures, with the idea of relating them to the structure of the buildings. The use of BIM models will
be considered in order to foresee this parameter for buildings where these measurements are not available.
Table 2 – List of measurements required to evaluate the behavior of a building
Water mass flow rate supplied by the district heating network to the examined user
(secondary network)
Temperature of water entering the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the user network
Temperature of water entering the heat exchanger on the user network
External temperature
Pump running status
Selected climatic curve
2-4 Internal temperatures in the building in rooms located on the top floor
2-4 Internal temperatures in the building in rooms located on a middle floor
2-4 Internal temperatures in the building in rooms located on the base floor
1.3.2. Measurement of internal temperature
The building considered is the kindergarten2 owned by the City of Turin, located in via Braccini 63. This building consists of
four dépendances and a main section that connects the others. All the rooms are placed at a raised ground floor.
The images shown at the end of the document represent the building’s aerial view and the building map. In particular the
numbers, reported on the second image, refer to the photos of the rooms in which the temperature sensors are installed.
At this point, our aim consists in measuring the main comfort parameter of the building: the indoor temperature.
Since in general it cannot be assumed that the rooms constituting the building are at a homogeneous temperature, the
study starts to subdivide the entire building in different parts.
There could be different kind of methods to choose the various zones of the building in terms of temperature levels, and it
is important to notice that the selection of these zones defines a key-point of the experimentation.
Looking at the building’s aerial view (figure 6), the decision is determined by the particular footprint as mentioned
previously. Three dépendances present the same area and envelope shape, except the fourth that is smaller, and the
orientation changes.
All the sections composing the building can be considered at a different temperature level. For this reason a temperature
sensor is located inside each section.
The choice of the wireless sensors is based on these reasons: easy and fast installation, and possible reallocation of the
sensors.
The temperature sensors are of the type EnOcean STM. They have a resolution of 0.15 K and an accuracy of 0.4 K. The
temperature cannot be read directly from the sensor, but the measured temperature is transmitted regularly to the
server, through a repeater located in the building. According to the datasheet for the sensors temperature measurements
should be transmitted every 100 seconds if changes are more than 0.8 K.
2 One of the 7 representative buildings that have been selected as case study for the demonstrator (see D1.1).
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Indeed the variations on time of the temperature indoor condition give the information about the dynamic of the building,
and this information is a good asset to build a model of the building.
In addition to the temperature indoor sensor, an outdoor light sensor is also installed. The sensors are of the type
EnOcean STM. They have two ranges of light intensity measure: 300-30000 Lux with a resolution of 117 Lux, and 600-
60000 Lux with a resolution of 234 Lux. The sensor can detect a variation of value every 10 seconds and transmit these
data to the server.
The specifications for these sensors is attached at the end of the document.
The temperature sensors are installed in such position that the direct irradiation of the sun doesn’t reach the sensor,
preventing in this way the distortion of real values of temperatures, and the possible children’s manipulation is avoided.
The sensors are mounted on the wall in each room, and its locations are indicated as “T” on the building map.
The outdoor solar sensor is mounted on the wall outside the building in vertical position, facing the south. This sensor is
indicated as “S” on the building map.
Figure 6 – View of the building – via Braccini 63
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Figure 7 – Building map – via Braccini 63
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Figure 8 – Sensors in rooms
1.4.Measurements in the network
A schematic of the Turin district heating network is shown below. Heat is generated in five thermal plants through three
combined cycles operating in cogeneration mode and five groups of boilers. In addition there are three installations of
storage tanks.
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Figure 9 – Schematic of the Turin district heating network
An example of the way the various systems cover a typical winter heat request is shown in the following diagram. This kind
of diagram is crucial to determine the primary energy consumption that is associated to the heat request of the users. The
same diagram is the basis to calculate the primary energy savings that is associated to any variation that is produced on
the thermal profile of the various users.
Figure 10 – Heat load of the thermal plants in a typical winter day
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Thermal request of the users and thermal demand for the plant differ, mainly because of the time delay provoked by the
network, which depends on the position of each user with respect to the generation plants. The following measurements
will be used in order to evaluate primary energy consumptions and savings.
Table 3 – List of measurements required to evaluate primary energy consumptions and savings
Water mass flow rate supplied by the district heating network to the examined users
(secondary network)
Temperature of water entering the heat exchanger on the secondary network
Temperature of water exiting the heat exchanger on the secondary network
Mass flow rate entering the heat exchanger of each thermal plant and storage tank
Temperature of water entering the heat exchanger of each thermal plant and storage tank
Temperature of water exiting the heat exchanger of each thermal plant and storage tank
Mass flow rate entering each pumping station or booster pumping station
Pressure of water entering each pumping station or booster pumping station
Pressure of water exiting each pumping station or booster pumping station
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2. MEASUREMENTS IN THE MANCHESTER DISTRICT
2.1.Goals of the analysis
The District chosen within Manchester is the Oxford Road Corridor which includes much of the University of Manchester
estate.
Of the Public Utilities serving the Corridor and University, the electricity has the highest resolution of data acquisition and
further sub-system monitoring in the case of the University. Within the Oxford Road Corridor District, the representative
buildings have been selected on the basis of the locations of the electrical monitoring currently in place and are described
in Deliverable 1.1.
The University utilizes a 6.6kV electricity network fed from the District Network Operator’s transformer ‘Manchester
University’. The University has ten 6.6kV feeders serving five ring mains with MV/LV transformers. Feeders and the LV
output of substations are metered half-hourly. This data has been recorded over a number of years and is currently
available on an ad-hoc basis from the District Network Operator.
Figure 11 – Manchester Oxford Road Corridor selected buildings (shaded blue) and electricity network (red cables and yellow
infrastructure)
The University has three distinct heat networks and energy centres, namely, the West Campus, the South East Campus
and North East Campus; further, the campus is bisected into West and East by the Oxford Road. These networks have
different characteristics summarized as:
West Campus Low pressure steam network with building steam to Low temperature Hot Water (LTHW) heat
exchangers
South East Campus Medium pressure hot water (MPHW) network with building MTHW/LTHW heat exchangers
North East Campus LTHW network with building heat interface units
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The main aim of the analysis will be to identify energy saving opportunities by examination of a selection of the buildings,
their Display Energy Certificates, their building services, and their Building Management System (BMS) operational data.
Provided that sufficient data from monitoring devices is available, studies similar to the Turin district might be carried out.
Opportunities will also be derived from detailed analysis of Energy Management System (EMS) operational data by
analyzing the electrical network and utility monitoring systems as well as by analysis of energy centres and district heating
systems.
2.2.Measurements
The University of Manchester has a data network that is converging around a single infrastructure. The Building
Management System includes control and monitoring functions of all significant building services systems.
Parameters of control and monitoring are illustrated below:
Figure 12 – Example single converged data network: Representative of the University of Manchester
In addition to integrated building services BMS data, the data network also integrates utility metering (Natural Gas and
electricity substations) along with the EMS data from district heating energy centres and distribution system meters and
environmental condition monitoring.
As part of a developing initiative there is further monitoring of one Medium Voltage ring main comprising 18 MV/LV
transformers. These have been fitted with Ethernet/broadband over power-line connections. This allows for high
resolution monitoring and recording of network behavior in terms of voltage, current, frequency and power characteristics
at high definition, typically at one second intervals. As already recalled in the introduction, the data acquisition represents
an ongoing discussion, and details will be provided in the successive deliverables.
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3. LINKS TO SUBSEQUENT WP1 TASKS
Subsequent tasks in WP1 depend on the outcomes of T1.3.1 and we have outlined these dependencies below.
• T1.2 Definition of Pervasive Sensor Network at District Level
In T1.2 we will define the number, type and position of the sensors for the energy and environmental monitoring and
control of the districts taking into account the buildings characteristics in terms of dimensions, uses, and systems features.
• T1.3 Energy Auditing and Data Collection
In this task, detailed measurement of quantities will be performed, as described in the present document. This energy
characterization will be performed extensively on the selected buildings.
• T1.4 Energy Saving Potential
In this task we will examine the energy efficiency potential in the district, buildings and grid and suggest innovative
solutions based on the use of sensors. This could include a review of the energy saving that ICT-enabled equipment across
the district could bring. One example is the possibility of coordinating the output of distributed energy such as PV and CHP
with a potential to extend the model to transport too (for instance, in the presence of electric vehicles).
4. CONCLUSIONS
This deliverable presents the selection of the various quantities to be measured.
In the Turin district, measurements of the thermal request of buildings connected to the district heating network are
performed. These measurements are operated in the buildings, at the substations and on the district heating networks.
The information is requested in order to diagnose the system (particularly the heat exchangers) as well as to identify and
quantify possible opportunities to modify the heat request profiles of the users. This is expected to significantly reduce the
primary energy cost of heat supplied to the users.
In the Manchester district, measurements are operated on the consumption of gas, heat and electricity. This opens the
door to perform interconnected actions, which makes it possible to optimize the energy system by operating at various
levels. This also creates additional difficulties that require further discussion on the data acquisition system. For this
reason, details will be provided in the successive deliverables in M1.3.
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