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A visual tool to calculate optimal control strategy for non-identical pumps working in parallel, taking motor and VSD efficiencies into account


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A simple graphical tool was developed, that finds the optimal combination of pumps and their rotational speeds for all possible working points for a pump battery. The tool was integrated into EPANET as well as EPA SWMM simulation packages. The tool allows us to analyse and optimize operation non-identical parallel pumps with different minimum and maximum frequencies for all possible working points. Pump characteristics and efficiency curves can be given in tabular format or as analytical functions of flow. Degradation of pump efficiency at lower rotational speed is taken into account, as well as motor and variable speed drive efficiencies at partial loads. The optimal solution provided by the tool was compared to measurements in two case studies. Our case studies showed 6.1-8.5% reduction in energy usage using the optimal parallel pumping control strategy compared to the currently used strategy, where all running pumps have the same frequency.
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A visual tool to calculate optimal control strategy for
non-identical pumps working in parallel, taking motor and
VSD efciencies into account
Markus I. Sunela and Raido Puust
A simple graphical tool was developed, that nds the optimal combination of pumps and their
rotational speeds for all possible working points for a pump battery. The tool was integrated into
EPANET as well as EPA SWMM simulation packages. The tool allows us to analyse and optimize
operation non-identical parallel pumps with different minimum and maximum frequencies for all
possible working points. Pump characteristics and efciency curves can be given in tabular format or
as analytical functions of ow. Degradation of pump efciency at lower rotational speed is taken into
account, as well as motor and variable speed drive efciencies at partial loads. The optimal solution
provided by the tool was compared to measurements in two case studies. Our case studies showed
6.18.5% reduction in energy usage using the optimal parallel pumping control strategy compared to
the currently used strategy, where all running pumps have the same frequency.
Markus I. Sunela (corresponding author)
Raido Puust
FCG Design and Engineering Ltd,
Tampere 33200,
Tallinn University of Technology,
Tallinn 19086,
E-mail: markus.sunela@fcg.
Key words |case study, EPANET, EPA SWMM, optimization, parallel pumping, variable speed drive
Pumping presents up to 80% of the energy demand of water
supply systems (Brandt et al. ). Good design can save
30% of this energy demand. Its not enough, however, to
consider just the pumpsefciency, but the pumping
system must be considered as a whole. The optimal design
should also account for the specics of the system, such as
variable ow and head. (Kaya et al. ).
Tools for optimizing the pump station design and oper-
ation have been lacking, especially when differently sized
pumps are to be used. While recently some work in this
eld has been done: the research by Costa Bortoni et al.
(),Yang & Borsting (),Wu et al. ()and Koor
et al. (). The methods for optimization were genetic
algorithm, non-linear programming, mixed integer non-
linear programming and dynamic programming, respect-
ively. The earlier research has focused on identical pumps
or characteristic curves which can be presented in second
order polynomial formulation, and only a little attention is
paid to degradation of pump hydraulic efciency at lower
rotational speed, or motor and variable-speed drive (VSD)
efciencies at reduced loads.
In this research paper, a tool was developed to solve the
aforementioned limitations. The tool was applied in two
case studies showing its feasibility for both identical and
non-identical pumps. The efciency model and the tool
were implemented also in EPANET (Rossman ) and
EPA SWMM (Rossman ).
The pump battery is described as a set of pumps. Each pump
is given a characteristic curve, an efciency curve, minimum
and maximum allowed frequency, nominal motor power
1115 © IWA Publishing 2015 Water Science & Technology: Water Supply |15.5 |2015
doi: 10.2166/ws.2015.069
, and either IE efciency class and number of poles,
for standard motor efciency values based on IEC-
(), motor efciency values at both 100% and 75%
load, η
and η
, respectively, or tabular motor
efciency curve as a function of load.
The pump characteristic curve can be expressed either
in tabular format as (Q,H) pairs, which is then linearly
interpolated, or in analytical power curve format as in
EPANET (Rossman )
H(Q)¼ω2Hmax ω2στQσ, (1)
where ω¼(f2=f1)¼(N2=N1) is the relative rotational speed,
and σand τare ow exponent and ow coefcient, obtained
by curve tting. A separate pump specic parameter Q
determining the maximum ow at the nominal speed can
be specied.
Flow and head at different rotational speeds are calcu-
lated using afnity laws (Volk )
The pump efciency curve can be given either in tabular
format, which is then linearly interpolated, or as a func-
tional, second order polynomial curve with either one or
two points. For one point, the best efciency point, BEP,
) the efciency curve is
η(Q)¼aQ2þbQ, (4)
2aQBEP þb¼0
and for two points (Q
) and (Q
), Q
curve is
ηQðÞ¼ aQ2þbQ,Q<QBEP
where aand bare solved as described in Equation (5) and
BEP þb2QBEP þc2ηBEP ¼0
2a2QBEP þb2¼0
Pump hydraulic efciency at different rotational speed
(Sârbu & Borza )
ηP¼ηP,2 ¼1(1 ηP,1)N1
¼1(1 ηP,1)1
While there are more general, friction factor (Strub et al.
) or Reynolds number (Wiesner ) based methods,
Equation (8) is accurate for medium sized pumps and
reasonable variation of rotational speed (Simpson &
Marchi ).
Hydraulic power
PH¼ρgQH, (9)
and pump shaft power (Volk ):
Motor load (US Department of Energy ):
(PNOM=ηM,100 ), (11)
where η
is the motor efciency at rated load.
IEC- ()standard provides an equation to
calculate an approximation of motor efciency at any partial
load based on the motors rated and 3/4 load efciencies
and η
0:75 1
1116 M. I. Sunela & R. Puust |A visual tool to calculate optimal control strategy for non-identical pumps Water Science & Technology: Water Supply |15.5 |2015
Wallbom-Carlson ()proposes usage of an idealized
VSD efciency factor that would include losses from the
VSD itself and losses generated in the motor by the VSD.
However, experiments presented in Burt et al. (), and
Brandt et al. ()support that the motorsefciency does
not change much if a VSD is used. This work assumes
that modern VSDs can mostly compensate generated
losses in motors. The VSD efciency is taken from a
lookup table based on load calculated as in Equation (11),
rotational speed and VSDs nominal power as per
IEC- ().
Motor power becomes
, (13)
pump train electrical power
, (14)
and the total pump train efciency (Bernier & Bourret
Table 1 shows an example, how load and different ef-
ciency components change; when the pumps rotational
speed is reduced in a zero static head system. The motor
presented in the table is a 55 kW motor, with 4/4 load ef-
ciency of 85.0% and 3/4 efciency of 85.5%. The VSD is
also 55 kW. The pumps BEP is 80% at nominal rotational
speed at 50 Hz. While the pumps BEP decreases from
80.0 to 78.6% when the rotational speed is reduced from
50 to 25 Hz, motorsefciency reduces from 85.0 to 65.6%
and VSD efciency from 97.9 to 95.7%. This results in a
total efciency of 66.6% at 50 Hz and only 49.3% at 25 Hz.
Algorithm development
The optimization is done for every working point the pump
battery can produce, using user specied resolution Q
. The step size depends on the wanted accuracy, and
it affects the computational time and amount of memory
The optimization problem for each working point
(Qi,Hj) becomes
, (16)
fi,jis a vector of each pumps frequency, and the
search space Xi,jincludes all allowed combinations that
result in total ow and head of (Qi,Hj). The optimization
is done using direct search, thus all possible solutions are
compared, and a global optimum for each working point
is guaranteed. (Hooke & Jeeves ).
The algorithm and user interface were developed using
Java programming language 1.8 and Swing toolkit,
JFreeChart 1.0.19 charting library and Apache POI 3.10.1
library for Excel le access. The programming language
was chosen for rapid development cycle, good industry
acceptance and penetration, and good multi-thread pro-
gramming features. The calculation is parallel and utilizes
all available threads at the computer.
First each pumps working regime is optimized. Mini-
mum and maximum allowed head, and maximum allowed
ow are calculated based on the pump characteristic curve
and the allowed frequency range. The code loops over
allowed frequencies using a step size of 0.01 Hz. Each result-
ing pump frequency combination is pushed to a queue, from
which one of the processor threads picks it up and calcu-
lates all possible ow and head combinations for the given
Table 1 |Different efciency components at various loads and rotational speeds
Hz Load (%)
Motor (%) VSD (%) Pump (%) Total (%)
50.0 100.0 85.0 97.9 80.0 66.6
45.4 75.0 85.5 97.9 79.8 66.8
39.7 50.0 84.5 97.3 79.5 65.4
31.5 25.0 77.9 96.5 79.1 59.4
25.0 12.5 65.6 95.7 78.6 49.3
18.4 5.0 43.8 95.0 77.9 32.4
14.6 2.5 28.1 94.7 77.4 20.6
10.8 1.0 13.5 94.3 76.7 9.8
1117 M. I. Sunela & R. Puust |A visual tool to calculate optimal control strategy for non-identical pumps Water Science & Technology: Water Supply |15.5 |2015
frequency. If multiple frequencies result in overlapping
working points in the Q
resolution, the frequency
that produces the highest total efciency is chosen for that
particular working point.
The results of the working regime calculation are stored
in the two pump specic lookup arrays shown in Equation
(17). The rst, F, contains the optimal frequency and the
other, H, contains the total pump train efciencies for all
working points. Array elements that present invalid working
points are set to 0.
fQ1,HnfQ2,Hn... fQm,Hn
ηQ1;HnηQ2;Hn... ηQm;Hn
Next, all the possible non-identical pump combinations
are considered. The combinations are presented as a binary
string, S, where 1 signies the pump is on and 0 the pump is
off. Minimum and maximum head is calculated for each
combination so that each pump running in the combination
can work within the limits:
Hmin ¼max Hmin;1;Hmin;2;...;Hmin;n
Hmax ¼min Hmax;1;Hmax;2;...;Hmax;n
where nis the number of pumps running in the
For each combination the algorithm iterates over the
allowed heads in the range [H
] using the head
step size. Head H
and combination string S, are added to
a queue, where one of the processor threads picks it up
for calculation.
A processor thread calculates all possible combinations
of ows for the pumps running in Sthat result in a head of
. Each pumps total efciency is looked up from the
pumps working regime array H. The total efciency for
the total ow Q
is calculated. If its less than the previous
best value for the same working point (Q
), the combi-
nation and efciency are stored in the result arrays Cand R.
The end result is two arrays that cover the full possible
working regime of the whole pump battery. Each element
represents an area dened by Q
and H
. Results array
Ccontains the numerical presentation of the optimal combi-
nation binary string and Rcontains the optimal total pump
train efciencies:
cQ1,HncQ2,Hn... cQm,Hn
ηQ1,HnηQ2,Hn... ηQm,Hn
Two naive algorithms were implemented too, to facili-
tate easier comparison of various control strategies. Naive
1 algorithm drives all running pumps with equal frequency,
and naive 2 algorithm adjusts only the lastly added pumps
frequency while the other pumps run at their respective
maximum frequencies. The naive algorithms store the
results the same way as the optimizator, so the algorithms
can be used interchangeably.
The program contains a graphical user interface, for
inputting the pump battery information, and for presenting
the results graphically, shown in Figure 1. Colour scheme
is selected by the user: specic energy, total efciency,
number of pumps running, or pump combination number
(i.e. decimal representation of the combination binary
string). All the other parameters are shown in a tool-tip,
and in a separate panel, if the user clicks on the chart.
The user can optionally import a set of working points
and their relative probabilities to the program. Working
points can be imported from an Excel le, comma or tab
separated les, or from EPANET or EPA SWMM results.
If the le contains no probability information, the points
are considered to be equally probable. The program then
shows the working points on the chart, and calculates
total annual energy consumption for the set of points.
The result array and the working points including their
total efciencies, if available, can be saved to an Excel le
for further processing and analysis. The saved le can be
1118 M. I. Sunela & R. Puust |A visual tool to calculate optimal control strategy for non-identical pumps Water Science & Technology: Water Supply |15.5 |2015
reopened in the program saving the need to recompute the
The efciency model was integrated into EPANET
(Rossmann ) and EPA SWMM (Rossmann ) simi-
larly to Simpson & Marchi ()to enable better energy
analysis and pump battery control strategy optimization in
hydraulic models. A new pump battery element
was developed for both simulators, which uses the tool to
calculate pump and frequency combinations and
The tool was used for evaluating the current performance
and optimizing the control strategy of network pumping
from the freshwater tank of two different ground water
sources of two different, major Finnish water utilities. The
rst case has three identical pumps and the second case
has four pumps of two different types. The pump character-
istic curves for the new pumps were used in both cases.
In both cases, the pump battery was modelled in the
pump battery analysis tool, and the optimal combinations
for all possible working points were calculated. The aver-
aged ow and head combinations calculated from
Supervisory Control and Data Acquisition (SCADA) were
imported into the tool as working points, and later exported
back to Excel with the optimal efciency and power values.
The computed optimal efciency and power values were
compared with the values collected from the VSDs by the
The SCADA systems collect VSD power and frequency,
and pump ow and head. Data from the year 2013 were pro-
cessed and the hourly averages were used in the rst case
and ve minute averages in the second case.
The case optimizations were performed on an Intel Core
i7-4800MQ @ 2.70 GHz laptop, with 32 Gb of RAM,
Windows 7 operating system and Java runtime version
1.8.0_31. Calculation times are reported as average for ve runs.
Case study 1 identical pumps
The pump battery has three identical pumps of which at
most two can run in parallel. About 1.5 million m³ is
pumped from the source into the network annually. The
median ow is about 200 m³/h, and the median total head
is about 62 m of water.
Figure 1 |The user interface showing optimization results (the full colour version of this gure is available in the online version of this paper, at
1119 M. I. Sunela & R. Puust |A visual tool to calculate optimal control strategy for non-identical pumps Water Science & Technology: Water Supply |15.5 |2015
The pumps are Pleuger 50 kW QN83-7a submersible
pumps with Pleuger 55 kW M8-480-2 motors. Each pump
has its own 55 kW VSD. The pumps have a BEP of 80%,
and the motors4/4 load efciency is 85.0% and 3/4 load
efciency is 85.5%.
The optimal annual energy consumption with the cur-
rent pump conguration is 421,227 kWh/year, which is
8.5% lower compared to the measured energy consumption
460,302 kWh/year. Figure 2 shows how the optimized total
efciency compares to the measured efciencies as a func-
tion of ow. Optimization took 2.7 s to complete.
The current control strategy seems to use always two
pumps in parallel regardless of the ow and the head.
Even the naive 1 algorithm, which resembles the currently
used control algorithm very closely, results in 7.8% savings
compared to the current strategy, mainly because it uses
only one pump when the requested ow is small.
Case study 2 non-identical pumps
The pump battery has two pairs of pumps: the older pumps,
number 3 and 4, are Grundfos80 kW NK100-200/219 with
110 kW ABB HXR 280MC 2 B3W motors with full load ef-
ciency of 95.1% and 3/4 load efciency of 95.0%, and the
new pumps, number 1 and 2, are Flygts 80 kW L150-
400U3SN-7504 pumps with 75 kW FFD SEE 280 S4
motors with full load efciency of 95.2% and 3/4 load ef-
ciency of 94.9%. The Grundfos pumps have BEP of 84.3%
and the Flygt pumps 86.4%. Each pump has its own VSD.
About 3.8 million m
is pumped from the source
annually. The median ow is about 425 m
/h, and the
median head about 35.5 m of water.
The optimal annual energy consumption with the cur-
rent pump conguration is 515,561 kWh/year which is
6.1% lower compared to the measured energy consumption
of 548,486 kWh/year. Figure 3 shows how the optimized
total efciency compares to the measured efciencies as
a function of ow. Optimization took 40 seconds to
From Figure 3 it is apparent, that the current control
algorithm results in one pump pumping only with too high
ows and two pumps pumping with too low ows. The opti-
mal ow to switch from one to two pumps and vice versa, is
about 130 l/s, depending on the exact head required.
The developed tool provides interesting insight into pump
battery working behaviour, such as the available working
regime, specic energy usage and efciency. The calculated
optimal pump combinations and their frequencies for differ-
ent ow and head regimes provide a good basis for
developing more optimal pump control strategies and com-
paring different sets of pumps for the case at hand.
The developed tool can handle non-identical pumps that
can also be described by non-analytical methods. Both fea-
tures are quite common in practical engineering work, but
Figure 2 |Comparison between the measured (diamonds) and optimized (rectangles) efciencies as a function of ow (the full colour version of this gure is available in the online version
of this paper, at
1120 M. I. Sunela & R. Puust |A visual tool to calculate optimal control strategy for non-identical pumps Water Science & Technology: Water Supply |15.5 |2015
so far, little research has been done on the optimization of
the pump battery with non-identical pumps.
The problem with the tool is that doing an exhaustive
search on a large number of pumps, results in exponential
growth in computational time as the number of concurrently
running pumps increases. The algorithm implementation
optimizes calculation for identical pumps and combi-
nations, and up to four or ve concurrently running non-
identical pumps can easily be calculated in a short time on
modern workstation computers, but a larger number of con-
current pumps can quickly result in a long calculation time.
However, the search method is guaranteed to nd a global
optimum, thus the presented method can be used as a refer-
ence benchmark for computationally more efcient
optimization methods.
The case studies show that the tool gives efciency that
is comparable to the values measured from VSDs, but opti-
mizing the pump battery control can still lead to savings in
the range of 510%. The savings depend largely on the cur-
rent control strategy, pump specics and working points. In
some cases it may be benecial to install differently sized
pumps as this leaves more room for optimization.
However, implementing the optimal strategy into the
control system can be troublesome. One possibility is to
use the optimization results as a lookup table, but as the
pumps degrade there must be a compensation for the lost
capacity. An easier way is to use the tool to calculate the
optimal pump combinations for different regions in the
working regime, and implement an algorithm that chooses
the combination based on predened ow and head
This work was supported by the institutional research
funding IUT (IUT19-17) of the Estonian Ministry of
Education and Research.
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First received 2 December 2014; accepted in revised form 18 May 2015. Available online 4 June 2015
1122 M. I. Sunela & R. Puust |A visual tool to calculate optimal control strategy for non-identical pumps Water Science & Technology: Water Supply |15.5 |2015
... Optimal pump scheduling in real time with or without near-optimal tank water levels has been studied in [177] and [31]. O ine calculations are common for some particular network components that do not change in time, for example, optimal pump working combinations that can be selected during an online calculation step so that the energy use will be optimal [254]. Any kind of real-time optimization needs also real-time measurements. ...
... The method is valid when the pump runs at its nominal speed, but otherwise it gives wrong results. [254,165] Water treatment costs are only rarely included in the objective function. Few articles, such as Farmani et al. [90], [44], [169], [247], [50] and [205], include any production costs. ...
... The problem with most VSP approaches present in the literature is that motor and VSD e ciencies at lower speeds are typically not considered, even though they have a major e ect on the total e ciency [254,255,237], and frequency scaling is not taken into consideration [244]. Neglecting the e ects, the accuracy of the published results considerably if no extra measures are taken to ensure that the pumps work close to the nominal speed (e.g. ...
Full-text available
A novel, general framework for performing whole-cost optimization of water production and distribution in real-time was developed in this dissertation. Optimization enables significant savings in energy and chemical costs. Optimization resulted in near optimal settings for all pump, valve and source stations, and optimal frequencies for all pumps in the water supply system as a function of time for the next 24 hours in near real-time. This dissertation developed a novel way to formulate the design variables of the optimization problem in order to minimize the size of the search space, a novel way to pre-optimize operation of pump batteries, a novel way to model pressure or flow controlled variable-speed driven pumping and a novel method to model complex control strategies in the hydraulic simulator. The optimization algorithm used is a modified version of greedy, meta-heuristic, single-solution Hybrid Discrete Dynamically Dimensioned Search (HD-DDS), that has not been applied in operational optimization of water supply systems before. According to the author's review of previous studies, this research is the first where real-time operative optimization of a large-scale water supply system (WSS) is performed using a non-simplified and non-surrogate model covering all pipes in the system, and where the raw water production, conveyance and treatment are also included in the model and optimization. In the case study (Tampere Water) the proposed optimization framework resulted in 20 % savings in the production and distribution costs, while ensuring better quality of service than before. Real-time aspect is ensured by the optimization run taking about two hours of computation time.
... Optimal pump scheduling in real time with or without tank near-optimal tank water levels has been research by [14] and [15]. Offline calculations are common for some particular network components that do not change in time, for example optimal pump working combinations that can be selected during online calculation step [16] so that the energy use will be optimal. Any kind of real-time optimization needs also real-time measurements. ...
... One final component that is missing from the earlier formulations, is the actual electrical energy used. Using the methodology developed in [28] and [16], accurate estimates for pump shaft energy, motor energy and variable-speed drive energy are calculated and included in the balance. Figure 2 shows schematically the different components of the balance. ...
... The latest update in January 2015 added raw water extraction, conveyance and water treatment processes into the model. In addition all pumping stations with variable-speed controlled parallel pumping were replaced with pump batteries [31], and motor and variable speed drive efficiencies were properly modeled as per Sunela and Puust [16]. ...
Full-text available
This paper presents a real time water supply system hydraulic and quality modeling framework that is applied in a case study. The simulated quality parameters include age, traced water source, temperature, pH, hardness and free chlorine. A full-scale and well-calibrated hydraulic model of the whole water supply system is built using an extended version of EPANET, allowing storing and restoring the state of plug flow in links. Once an hour, the simulator is updated with the previous hour's hydraulic and quality state from the utility's supervisory control and data acquisition (SCADA) system and a simulation is performed. The results are stored both in GeoJSON format for geographic information systems (GIS) and in a relational database for later use. Some results are presented to the general public in a geographically aggregated form over a web user interface and as open data using Representational State Transfer (REST) web service interface.
... The second part of the battery component is implemented partly via callback mechanism to check whether the resulting flow and head combination is valid for the pump battery, and partly via post-processing which calculates the energy usage, each pump's rotational speed and flow. The second part, both validity checks and post-processing analysis, relies fully on the lookup table generated by using methods presented in [8] and [9]. The second part is only necessary, if analysis of pump performance and energy is needed -the first part alone can solve the system state and hydraulic behaviour. ...
... We took lookup table based approach described in [8] and [9]. The chosen method allows to model pump battery with non-identical pumps with different allowed frequency ranges and different parallel pump control strategies: equal frequencies for all running pumps (naïve 1), only last pump's frequency is controlled (naïve 2) or globally optimal control strategy. ...
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This paper introduces a control system model framework built into EPANET simulator. The control system model extends the current possibilities offered by EPANET to model the exact, dynamic behavior of the water distribution system working under complex or high-level control system. Besides the control system model, a novel method for modelling parallel pumping stations in EPANET was developed. The new methodology allows varying the control type (pressure, flow) and setting to dynamically change during the simulation. The new pump battery component was utilized in the control system modelling. The new modelling tools were demonstrated in a case study.
... Up to 70 % of energy can be saved by using Variable Frequency Drive (VFD) instead. Variations in VFD are generated using a Proportional-Integral-Differential (PID) controller, which is a generic closed-loop control scheme that attempts to maintain the setpoint of a process variable with certain corrections to the control process (Sunela and Puust, 2015;Rai et al., 2017). Case study of Sewer Pumping Station (SPS) "Ušće Nova" in Belgrade is used in this paper to demonstrate variable speed pump modeling using PID control. ...
Conference Paper
Recently, industrial practices have bloomed, and the consumption of resources has drastically increased. The oil and gas industries are large consumers and producers of water, yielding a huge amount of oily wastewater with every oil barrel produced. Such samples contain a variety of contaminants that ought to be removed before discharging or reutilization. Phenol compounds are amongst the most occurring contaminants in petroleum-based oily wastewater and they pose a great risk on the aquatic life. Oily wastewater has proven to be recalcitrant and persistent to the conventional treatment methods. Advanced treatments are sought to remove the small-sized oil emulsions and meet environmental regulations or limits for reutilization practices. Even advanced processes would suffer from some drawbacks pertaining to the high energy consumption, technical issues that risk the integrity of the technology, and lack of applicability. A proposed solution is to hybridize technologies into a single treatment system to achieve the desired treatment. In this work, an electrochemical cell (mainly electrocoagulation – EC), ceramic microfiltration membrane, and ozonation have been combined in a one-pot reactor (Khalifa et al. Journal of Cleaner Production 289 (2021) 125764). Different parameters have been studied on the effect of phenol removal, including the hydraulic residence time (HRT), aeration, frequency of power supply, current density (CD), initial pH, and ozonation. Several experiments have been conducted using the hybrid reactor, which is designed with a continuous flow mode of operation. Some experiments were conducted with aeration and other with ozonation. Part of the foam, sludge, and electrodes were characterized using scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS). Maximum removal of phenol reached ~99% using the ozonation-assisted electro-membrane hybrid reactor.
... Although not explicitly mentioned in most published research, the performance of pumps, including VSPs, may be evaluated from the abundance of historical records which is often available in WDSs that have Supervisory Control And Data Accusation (SCADA) systems [5,36]. To produce the FSP's curves, one needs the flow, suction and discharge pressures (in fact only the difference is needed), and power readings for the pump. ...
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Water distribution systems (WDSs) deliver water from sources to consumers. These systems are made of hydraulic elements such as reservoirs, tanks, pipes, valves, and pumps. A pump is characterized by curves which define the relationship of the pump’s head gain and efficiency with its flow. For a new pump, the curves are provided by the manufacturer. However, due to its operating history, the performance of a pump deteriorates, and its curves decline at an estimated rate of about 1% per year. Pump curves are key elements for planning and management of WDSs and for monitoring system efficiency, to determine when a pump should be rehabilitated or replaced. In practice, determining pump curves is done by field tests, which are conducted every few years. This leaves the pump’s performance unmonitored for long time periods. Moreover, these tests often cover only a small range of the curves. This study demonstrates that in the era of IoT and big data, the data collected by Supervisory Control And Data Acquisition (SCADA) systems can be used to continuously monitor pumps’ performance and derive updated pump characteristic curves. We present and demonstrate a practical methodology to estimate fixed and variable speed pump curves in pumping stations. The proposed method can estimate individual pump curves even when the measurements are given only for the pumping station as a whole (i.e., total flow, pumping station head gain). The methodology is demonstrated in a real-world case study of a pumping station in southern Israel.
... To solve this problem, rainwater storage tanks and pumping stations need to be installed at locations in the rainwater pipe network where the drainage capacity is insufficient. Peak flooding can be reduced with the use of storage tanks, and the drainage pressure within the pipe network can be relieved [4]. ...
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The pumps in multistage drainage pumping stations are often subject to frequent start-up and shutoffs during operation because of unreasonable start-up depths of the pumps; this will reduce the service lives of the pumps. To solve this problem, an optimization method for minimizing pump start-up and shutoff times is proposed. In this method, the operation of pumps in pumping station was optimized by constructing a mathematical optimization model. The storm water management model (SWMM) and particle swarm optimization (PSO) method were used to solve the problem and the optimal start-up depth of each pump is obtained. Nine pumping stations in Beijing were selected as a case study and this method was applied for multistage pumping station optimization and single pumping station optimization in the case study. Results from the case study demonstrate that the multistage pumping station optimization acquired a small number of pump start-up/shutoff times, which were from 8 to 114 in different rainfall scenarios. Compared with the multistage pumping station optimization, the single pumping station optimization had a bigger number of pump start-up/shutoff times, which were from 1 to 133 times, and the pump operating time was also longer, from 72 min to 7542 min. Therefore, the multistage pumping station optimization method was more suitable to reduce the frequency of pump start-up/shutoffs.
... Markus I., [28] have developed a tool that provides interesting insight into pump battery working behavior, such as the available working regime, specific energy usage, and efficiency. The study shows that the tool efficiency is equivalent to the values measured from VSDs but adjusting the pump battery control can save 5-10% of energy. ...
An energy crisis is one of the major aspects that the world is facing today. There is a mismatch between the energy supply and demand which keeps on increasing every year. It is necessary to reduce the consumption of energy without disturbing the performance of the system. A number of researches have been carried out on various experiments in this field in order to find out energy-efficient electro-hydraulic circuits used in CNC machine tools. In the present paper, a detailed literature survey was carried out on the recent works in the field of an electro-hydraulic system to find out the methods that researchers have adopted to reduce the energy consumption and increase the system efficiency. Attempts were made to understand and incorporate the concepts of fuzzy logic, VFD in the hydraulic circuit to achieve the goal. A detailed literature survey was carried out on drive technology in hydraulic circuits for energy efficiency, control strategies of open loop hydraulic system with a closed loop intelligent control system and design modification in electro-hydraulic circuits for leakage losses.
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This paper concentrates on an algorithm for steady running prediction of all identical variable speed pumps (VSP) in group close to the best efficiency point (BEP) given by pump manufacturer. Prediction of starting or stopping pumps based on the pressure and variable demand required is also covered. Additional pumps will be activated when the required pressure or demand cannot be met. Optimal pump working (Q, H) areas, most efficient combination between Q, H and different number of pumps and boundaries between them are calculated and visualized. Results provide simple and easy programmable input to adjust pumping station control systems. The usage of the proposed algorithm is illustrated by a case study based on an existing pumping station.
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Affinity laws relate to the characteristics of pumps operating at different speeds, and in a water distribution context, are usually used to predict the pump curve of variable speed pumps (VSPs). VSPs can adjust the pump curve to meet the network requirements more efficiently with resultant savings of energy. The estimation of the effectiveness of a VSP is based on hydraulic simulations, in which the behavior of VSPs is described using the affinity laws. The affinity laws, however, contain approximations because they do not take into account factors that do not scale with velocity. In particular, the approximation inherent in the affinity law that computes power and efficiency can produce a misleading result, especially for small-size pumps. The research reported in this paper estimates the error in efficiency for a wide range of pump sizes and tests the use of a previously proposed formula as an alternative to the affinity law. Results show that a better estimation can be achieved for the efficiency of small- and medium-size pumps. Moreover the formula can be easily implemented in hydraulic solvers.
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In applications where demand on a water supply system changes frequently and widely, the operating conditions of pumps always deviate from the design conditions, and this error leads to poor efficiency and reliability. For energy saving and longer service life, a parallel pump system was supplied, with the valves and rotational speed controls approximating the system’s operating conditions closer to the designed conditions for different consumer loads. The developed optimization model employs a genetic algorithm (GA) aiming at the pumps’ maximum efficiency. A theoretical solution based on the Lagrange multiples method was proved. Experiments on two identical pumps were carried out. The presented model gives optimal input data for the pumps’ rotational speed and valve positions. The results show that control valves are especially helpful for improvement of a single pump’s efficiency and reliability. However, in the system of parallel pumps, throttling losses in the valves caused a significant decline in system efficiency. Therefore, the developed optimization model provides balance between efficiency and reliability by offering the suitable operating mode.
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The paper presents some different solutions for the functional optimization of pumps in big water distribution systems. These solutions lead to an increasing of power efficiency and a correlation of the pumped flow with the real consumption in the system, which will result in an energy saving up to 30%, an important fact in the present energy conditions.
This work is the result of an investigation based on numerous test data supplied by major compressor manufacturers in USA and in Europe. The main objective of the work is to propose improved formulae for the correction of the efficiency, the head, and the flow as influenced by the Reynolds number variation between workshop tests and specified conditions, carried out with the same machine. Tests on hand have shown that a sufficiently good correlation between measured and predicted values can be obtained with the proposed formulae. In addition a proposal is made for the allowable range, taking into account the inherent limitations for accurate testing at low Reynolds numbers.
After manpower, energy is the highest operating cost item for most water and wastewater companies. Over the last decade, energy consumption by the sector has increased considerably as a consequence of the implementation of new technologies to meet new potable water and effluent treatment quality standards. The price of energy has also increased substantially in the same period. These increases will be compounded by the need to meet future changes to regulations and standards that will require additional energy intensive processes to achieve more exacting requirements. High energy consumption will affect the water industry world wide and is inextricably linked to the issue of Climate Change. This international research project has focused on identifying current energy efficient best practices and technologies in the efficient design and operation of water industry assets for the whole water cycle from abstraction to discharge, including water treatment and distribution, wastewater conveyance and treatment; water reuse; sludge treatment and disposal and water conservation. Opportunities have also been identified for hydraulic energy recovery from turbines and generation from waste and sludge through CHP technology. The study output is a Compendium of global best practices covering the water cycle matrix and includes variations between regions and continents, large urban and small rural systems and complex high and simple low technical solutions. International case studies are used to illustrate best practices. On behalf of Global Water Research Coalition (GWRC) partners world-wide as represented by four Continental Coordinators in the US, Europe, Singapore and Australasia, and South Africa, the project was managed by UK Water Industry Research (UKWIR). This presentation will give the background to the project and use case studies to illustrate the study findings and future opportunities to help deliver both incremental improvements in energy efficiency through optimisation of existing assets and operations and more substantial improvements in energy efficiency from the adoption of novel but proven technologies.
This paper summarizes the results of an investigation into the effects of Reynolds number on the performance of centrifugal compressor stages, using a computer program for the detailed prediction of component and overall performance characteristics. This investigation included wide variation of stage geometries, speeds, and fluid conditions, resulting in diffuser inlet absolute Reynolds number variations over the range from 500 to 500,000,000. The computer results indicate that variations in Reynolds number and in relative roughness will produce variations in all significant performance parameters: the flow coefficient, the work coefficient, and the efficiency. Correlations of these results with various sources of test data on single and multistage centrifugal compressors produce very satisfactory comparisons. As a result of this study, improved empirical methods are recommended for making practical adjustments of compressor performance with variation in Reynolds number. These recommendations should be taken into account in the modernization of all centrifugal compressor performance test codes such as those formulated by ASME and ISO.
The cumulative effects of deteriorating values of motor and variable frequency drives (VFD) efficiencies are examined as the speed of the pump is reduced in a closed fluid distribution system. Using published values of efficiencies, it was shown that the power required at the inlet of a pump-VFD configuration is significantly higher, especially for oversized motors, than the power predicted by the classic pump law. Non-dimensional power curves were constructed to calculate power requirements, relative to the shaft power at nominal operating conditions, as a function of flow rate. Yearly energy consumptions were evaluated for four different utilization scenarios.