CONTROL OF INDOOR SWIMMING POOLS WITH
POTENTIAL FOR DEMAND RESPONSE
E. Ribeiro
1,4
, H. M. Jorge
2,4
and D. A. Quintela
3,5
1
School of Technology and Management, Polytechnic Institute of Leiria, Leiria, Portugal
2
Department of Electrical Engineering and Computers, University of Coimbra, Coimbra, Portugal
3
Department of Mechanical Engineering, University of Coimbra, Coimbra, Portugal
4
Institute for Systems and Computers Engineering of Coimbra (INESCC), Coimbra, Portugal
5
Association for the Development of Industrial Aerodynamics (ADAI), Coimbra, Portugal
Keywords: Indoor Swimming Pools, Building Energy Management System, Smart Grid, Demand Response.
Abstract: Buildings with indoor swimming pools are recognised as very high-energy consumers and present a great
potential for electrical and thermal energy savings. A building energy management system (BEMS) could
be conceived in order to optimize the building energy demand and with smart grid interaction. This paper
presents the condition and potential contract-based demand side response in indoor swimming pools
context. The BEMS designed by the authors implements control strategies for HAVAC and pumping system
in order to reduce the electricity demand during peak hours or in response to a emergency signal from the
system operator in critical times. These strategies can carry out a significant reduction on power demand
both in HVAC and pumping systems.
1 INTRODUCTION
In Portugal, the number of sport complexes with
Indoor Swimming Pools (ISP), with an intensive
use, has increased significantly during the last
decades. The growing of such facilities has shown
the necessity to promote the evaluation and control
of the indoor environment variables in order to
minimise the energy consumption, according to the
measures proposed by the European Community
Directive 2006/32/EC (EC, 2006). By this directive,
all buildings must be classified from an energy point
of view, using de Energy Efficiency Index (EEI),
have to implement measures leading to the Rational
Use of Energy (RUE), and install a Building Energy
Management System (BEMS).
A BEMS was designed integrating some control
strategies in order to optimize the building energy
demand, being able to reduce electric energy
consumption during peak periods or in response to
an emergence signal send by the utility requesting
power demand reduction.
There are some roles and responsibilities of
actors involved in the Smart Grids (SG) deployment,
defined by the European Community task force for
SG (EC, 2011). The focus of these roles is the
Demand Response (DR). Developments in DR vary
substantially across Europe reflecting national
conditions and are triggered by different sets of
policies, programmes and implementation schemes
(Jacopo et all, 2009). Currently in Portugal the
electric pricing relies on time of use (ToU) tariffs
that penalize the consumption of electricity in the
peak periods.
In addition to control strategies for reducing
power demand the full study also deals with the
optimization use of energy in all main ISP process:
Heating, Ventilation and Air Conditioning system
(HVAC), Pumping System (PS), Water heating for
baths, Lighting (Lig).
2 METHODOLOGY
The DR essence is to manage customer electricity
consumption in response to supply conditions, for
example: reduce consumption at critical times (CT)
or in response to market prices (RMP).
The first topic (CT) normally occurs in shorts
periods of time when it is necessary flexibility of
power consumption at the client’s side to allow
supplier selection. For this situation it is required
145
Ribeiro E., M. Jorge H. and A. Quintela D..
CONTROL OF INDOOR SWIMMING POOLS WITH POTENTIAL FOR DEMAND RESPONSE.
DOI: 10.5220/0003952301450148
In Proceedings of the 1st International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2012), pages 145-148
ISBN: 978-989-8565-09-9
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
that the supply contract allows the reduction of
energy consumption to the consumer.
The second topic (RMP) is used in longer
periods of time, during the peak hours where the
price of energy is higher. In the near future the
utilities will offer real time pricing tariffs, where the
peak hours are dynamic, not fixed.
Subsequently are defined the conditions that the
consumer can reduce energy bills, but for that he
should have capacity to reduce power demand in the
process without exceeding the minimum threshold
of safety or comfort.
In ISP can by identify three main energy process
(Rodrigues, 2007) that are responsible for almost
90% of the overall electric energy consumption
(Figure 1).
PS
45%
Lig
17%
HVAC
38%
Figure 1: Electric Energy consumption by topic.
The HVAC and PS could have greater potential
to reduce electricity consumption, but it must be
guaranteed certain conditions related to the level of
water quality and comfort.
For HVAC the environmental conditions of ISP
are regulated by the standard NP EN 15288-1(IPQ,
2009), where it is defined besides other parameters
that relative humidity (
RH) could change between
40% and 80%, preferably less than 60%.
In CT case, the environmental variables
threshold for RH could be adjusted to achieve 80%
for a maximum period of 30 minutes so that to have
no excessive degradation of the environmental
conditions. After period of control the environmental
thresold must be go back to the normal value.
In RMP case, the environmental thresold should
be adjusted with RH to reach 60% as long as we
want.
In the PS the control conditions are strongly
dependent of the quality of water determined by
determining Langelier Index (Langelier, 1936),
(Perkins, 2000) also known as Saturation Index (SI).
In these case the SI is considered satisfactory when
it remains between -0.5 and +0.5 (DHHS, 2005).
During the CT case, the flow rate could be
reduced to
13 of the nominal flow until 0.5SI > .
When |SI|> 0.5thenthe flow rate must return to the
nominal value.
In RMP case, the flow rate could be reduced to
12 of the nominal flow, and checked the IS in
regular periods of 15 minutes. If
0.5SI > we must
increase the flow rate by 10% until the nominal flow
is reached, or otherwise reduce the flow by the same
value.
A BEMS, using a network of direct digital
controllers, controls all process presented with
specific control strategies described below. In the
HVAC system the control model proposed is based
on real time determination of the environmental
variables that optimize the energy consumption,
bearing in mind the regulation and the aim. In the PS
an expedite approach to the control model was
elaborated using variable flow rate operation.
3 CHARACTERIZATION OF
CASE STUDY
According to a case study analysis of energy
consumption during the year 2006, the total of
electrical energy was 1580 MWh/year and natural
gas was 223799 m
3
(Rodrigues, 2007). The HVAC
system and PS can be estimated an average electric
power of 58kW and 69kW, respectively,
corresponding to 70% of electricity consumption.
The building under analysis is a sports complex
with 15200 m
2
which incorporates an Olympic Pool
(OP) of 50x25 m
2
, a Children Pool (CP) of
25x12.5m
2
and a multi-sports pavilion of 30x50m
2
.
Ventilation
27%
Others
3%
Evaporation
70%
Figure 2: ISP HVAC energy balance.
SMARTGREENS2012-1stInternationalConferenceonSmartGridsandGreenITSystems
146
The HVAC at pool level is ensured by Air
Handling Units (AHU) with dehumidifying and
heating capacities in continues work. The use of the
AHU is necessary to maintain de air quality and the
comfort conditions. The most important objective of
control is to minimise the high evaporation rates
which asks for electric energy for dehumidifying,
and which are the largest source of energy losses
(Figure 2).
In this case the latent energy associated to the
pool evaporation is the must important variable of
the control process (USDE, 2009). Recent studies
(Shah, 2003) identify an empirical formula to
determine the pool evaporation and that takes into
consideration the environmental variables and the
influence of users.
Taking into account the complexity of the
parameters involved in HVAC system, the choice of
energy simulation programs is actually the better
way, to quantify the benefits that can be achieved by
different control strategies (Pedrini, 2003).
A rigorous choice of environmental variables (
a
t
-
air temperature and RH) reduce the evaporation of
pool and decrease energy consumption (Ribeiro,
2011). The ESP-r program was used throughout the
present work, and the simulation gives the latent
energy (
lat
P ) needed to maintain the
φ
level. We
can determine the electric power (
_ep lat
P ) spend
knowing the HVAC coefficient of performance
(
COP ) by:
_
lat
ep lat
P
P
COP
=
(1)
The OP and CP PS are composed by five and
three centrifugal pumps in parallel with nominal
water flow rate of have 650
3
mh and 188
3
mh
respectively, and pool water treatment equipments.
The introduction of variable-speed drive in
hydraulic systems is current practice in systems with
variable flow rate promoting significant reductions
in energy consumption (Akayleh at all, 2009).
With water quality monitoring, it is possible to
identify operation patterns at variable flow rate, that
are depending on the number of pumps in use on the
system ( n ) and the number of pumps with variable
speed (
f
), which provide significant electricity
savings (Ribeiro, 2010).
4 RESULTS
In the HVAC the electric power used to reduce the
latent load of the building is quantified by
simulation. Three simulations (Real, CT and RMP
case) were performed considering the respective
environmental variables (Table 1).
Table 1: HVAC environmental variable.
Variable
OP CP
Real CT RMP Real CT RMP
a
t (ºC)
28.3 23.5 26.7 30.5 25.5 28.9
RH (%) 52.3 80 60 52.7 80 60
_ep lat
P (kW)
22.2 10.08 18.38 3.84 1.83 3.6
For the PS the conditions are strongly dependent
on the quality of water determined by the SI, but in
this case assuming that
SI is always less then 0.5.
Applying the expedite formula developed by the
author is possible to determine the (
n
,
f
) which
minimizes the installation electric power (Figure 3 to
6) with the flow rate considered (Table 2).
Table 2: PS´s flow rate and electric power demand.
OP CP
m
3
/h kW m
3
/h kW
Real 650 46.40 188 9.96
CT 216 22.05 62 4.90
RMP 325 33.15 94 8.90
27
29
31
33
35
37
260
2
70
280
29
0
3
00
310
32
0
3
30
34
0
Flow (m3/h)
Eletric Power (kW)
n=3 e f=0
n=3 e f=1
n=3 e f=2
CT case
Figure 3: OP – CT case.
15
17
19
21
23
25
27
1
40
14
8
155
163
17
0
178
18
5
193
2
00
208
215
2
23
23
0
2
38
24
5
Flow (m3/h)
Eletric Power (kW)
n=2 e f=0
n=2 e f=1
RMP case
Figure 4: OP – RMP case.
CONTROLOFINDOORSWIMMINGPOOLSWITHPOTENTIALFORDEMANDRESPONSE
147
7,0
7,5
8,0
8,5
9,0
9,5
10,0
10,5
11,0
81
82
83
8
4
85
8
6
8
7
88
8
9
90
91
9
2
93
94
95
Flow (m3/h)
Eletric Power (kW)
n=2 e f=0
n=2 e f=1
CT case
Figure 5: CP – CT case.
3,0
3,5
4,0
4,5
5,0
5,5
6,0
6,5
7,0
7,5
5
0
5
2
5
4
56
58
6
0
6
2
6
4
6
6
68
7
0
72
7
4
7
6
7
8
Flow (m3/h)
Eletric Power (kW)
n=1 e f=0
RMP case
Figure 6: CP – RMP case.
For HVAC and PS the results for the power
reduction potentials are determined and presented in
Table 3.
Table 3: Potential power reduction (kW).
HVAC PS
CT 14.13 24.5% 29.41 42.9%
RMP 4.06 7.0% 14.3 20.9%
It is remarkable the enormous reduction of
power demand in the case of PS and the substantial
decrease in HVAC.
5 CONCLUSIONS
According to the present results the potential for
application of DR concept in this pool is important.
The BEMS designed by the author’s implements
some control strategies applied to HAVC system and
PS to reduce electricity demand during peak hours,
which represents a significant reduction in the power
demand of 7.0 % and 20.9% in the HVAC system
and the PS system, respectively. In a situation of
emergency to the grid, the maximum reduction in
power demand that can be obtained is 24.5 % and
42.9% in HVAC and PS, respectively.
It is expected a promising future for DR in these
kinds of buildings taking into account the large
number of such sport complexes in Portugal.
The authors believe that the present contribution
underlines the importance of sport complexes with
Indoor Swimming Pools for contract-based DR, of
using
adapted Building Energy Management System.
This work has been partially supported by FCT
under project grant PEst-C/EEI/UI0308/2011.
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