Modelling real-time control of WWTP influent flow feeding ... · [email protected]. Title:...
21
Stefan Kroll Geert Dirckx Marjoleine Weemaes Patrick Willems Modelling real-time control of WWTP influent flow feeding based on scarce data
Transcript of Modelling real-time control of WWTP influent flow feeding ... · [email protected]. Title:...
Stefan Kroll
Geert Dirckx
Marjoleine Weemaes
Patrick Willems
Modelling real-time control of WWTP
influent flow feeding based on scarce data
Scope: RTC as mitigation for WWTP
overloading?
455 l/s
Q in l/s 2007
Leihoekstr. 67
Herderstr. 42
Neerhoek 70
Leiestr. /
Heuvelhoekstr. /
Σ 180
PS Leiestraat78 l/s
PS Leihoekstraat67 l/s
PS Herderstraat42 l/s
PS Neerhoek70 l/s
375 l/s
2010
67 (59)
42 (33)
70 (67)
78 (79)
/
260 (240)
2011++
89
42
70
78
190
≈ 460
Peak load
Overload(Overload)
PS Heuvelhoekstraat190 l/s WWTP
Available data: hydrodynamic model
PS Herderstraat
PS Neerhoek
PS Leiestraat
PS Leihoekstraat
PS Heuvelhoekstraat
WWTP
non-existing data
Available data: dimensions & time
series
overflow
to WWTP
RTC -
h
Qout
Modelled processes: sewer system
static storage V
overflow
dynamic
storage
to WWTP
h
Qin,1Qin,2
Qin,3 Qin,4 Qout
QCSO
RTC -
Qin = ΣQin,i Qout = ΣQpump,i dV/dt = Qin – Qout
h = f(V) Qpump,i = f(h) QCSO = f(h)
Modelled processes: input data
• Qin
• Reverse
modelling:
Qin = dV/dt + Qout
where V = f(h)
• h
• Monitored
• Scaled based on
existing data
RTC -
Modelled processes: pumps
RTC -
• Switch on/off delay
• Dependence of pump flow on water level in pump pit
25-Mar-2009
tijd
wate
rpeil
in m
00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 00:00:004
5
6
7
8
25-Mar-2009
tijd
debie
t in
l/s
00:00:00 04:00:00 08:00:00 12:00:00 16:00:00 20:00:00 00:00:000
20
40
60
time
wat
er le
vel i
n m
flo
w i
n l/
s
time
05:26:41 06:06:41 06:46:42 07:26:42 08:06:43 08:46:430
20
40
60
80
100
120
19-Jun-2011
tijd
pom
pdebie
t in
l/s
metingen
sim (f(h))
sim (f(Qin
))
Modelled processes: validation
RTC -
monitored
time
flo
w in
l/s
• Option 1: switching pump 1 on when switching pump 2 off
• Capacity is never
exceeded
• mean total flow < WWTP
capacity (“loss” V)
• Option 2: switching optimised for mean total flow
• Capacity is exceeded
every cycle
• mean total flow = WWTP
capacity (V1 + V2 = 0)
V V …
V2
V1
V2
V1
…
Q
Q
t
t
RTC -
Control: time slot based (local)
• Qmax: max WWTP capacity
• fdi: filling degree (V/Vmax)
• Qrem: remaining WWTP capacity
• Qi: PS capacities
• Qi,red: reduced PS capacities :
– use 1 pump at 2+1
installations
– frequency control
• spi: set-points for desired flow
per PS
• n: number of PS
dd
no
d
Qmax, Qi, fdi
sort Qi by fdi
i = 0
Qrem = Qmax
Qi ≤ Qrem ?yes
i = i+1
Qi,red ≤ Qrem ?yes
spi = Qi,red
Qrem = Qrem – Qi,red
no
spi = 0
spi = Qi
Qrem = Qrem – Qi
i > n ?
nospi
yes
RTC -
Control: global
Results: pump activity - no control
RTC -
WWTP capacity
Results: pump activity - time slots 1
RTC -
WWTP capacity
Results: pump activity - time slots 2
RTC -
WWTP capacity
Results: pump activity - global
RTC -
WWTP capacity
Results: total CSO volume
RTC -
0
2
4
6
8
10
12x 10
4
scenario
tota
l C
SO
volu
me in m
³
current situation
(unlimited)
const. timeslots
(375 l/s)
opt. timeslots
(375 l/s)
global
(375 l/s)
global
(unlimited)
no control
Model sensitivity: total CSO volume
• 42 factors + 1 dummy
• Morris screening (multiple One-at-A-Time scenarios)
• eFAST (extended Fourier Amplitude Sensitivity Test)
RTC -
Model sensitivity: convergence
RTC -
• Morris screening • eFAST
8800 55900
08:00:00 12:00:00 16:00:00 20:00:00 00:00:00 04:00:00 08:00:00
27-07-2013
0
200
400
600
800
1000
1200
1400
1600
18000224 -
RW
ZI
Ols
ene_H
T_10580 -
Tota
al in
fluentd
ebie
t
[m�
/h]
0
200
400
600
800
1000
1200
1400
1600
1800
0224 -
RW
ZI
Ols
ene_H
T_15170 -
Debie
t eff
luent
[m
�/h
]
0
200
400
600
800
1000
1200
1400
1600
1800
0224 -
RW
ZI
Ols
ene_H
T_10580 -
Tota
al in
fluentd
ebie
t
[m�
/h]_
filtere
d
0
200
400
600
800
1000
1200
1400
1600
1800
0224 -
RW
ZI
Ols
ene_H
T_15170 -
Debie
t eff
luent
[m
�/h
]_filtere
d
Implementation: follow-up after 1 year
RTC -
WWTP capacity
Implementation: follow-up after 1 year
• Modified control dynamically adapts to variable pump capacities
RTC -
Conclusions
• Model
• Acceptable accuracy
• Desirable: time-dependent pump capacities
• Sensitivity
• Location-dependent
• Very comparable ranking (Morris vs eFAST)
• Implementation
• RTC is a viable option
• Long-term follow up pays off
RTC -
Stefan Kroll
Geert Dirckx
Marjoleine Weemaes
Patrick Willems
Modelling real-time control of WWTP
influent flow feeding based on scarce data
