EP2616600A1 - Method and device for controlling a waste water network - Google Patents
Method and device for controlling a waste water networkInfo
- Publication number
- EP2616600A1 EP2616600A1 EP11773041.6A EP11773041A EP2616600A1 EP 2616600 A1 EP2616600 A1 EP 2616600A1 EP 11773041 A EP11773041 A EP 11773041A EP 2616600 A1 EP2616600 A1 EP 2616600A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- network
- rain
- setpoints
- instructions
- list
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 239000002351 wastewater Substances 0.000 title claims abstract description 16
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 27
- 238000005457 optimization Methods 0.000 claims description 17
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 4
- 230000006870 function Effects 0.000 description 6
- 238000007726 management method Methods 0.000 description 6
- 230000006399 behavior Effects 0.000 description 5
- 238000005054 agglomeration Methods 0.000 description 3
- 230000002776 aggregation Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 239000000872 buffer Substances 0.000 description 2
- 230000002950 deficient Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000000746 purification Methods 0.000 description 2
- 238000006424 Flood reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 238000004377 microelectronic Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
- 238000010200 validation analysis Methods 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03F—SEWERS; CESSPOOLS
- E03F7/00—Other installations or implements for operating sewer systems, e.g. for preventing or indicating stoppage; Emptying cesspools
Definitions
- the invention relates to the general field of waste water networks.
- the invention relates in particular to the real-time management of such a network.
- a waste water network typically includes transport works, for example pipelines, intended to bring water to a treatment plant and storage facilities such as storm basins.
- the network may also include automation and actuators such as pumps and valves, to influence the flow of water in the network.
- a pump can be controlled depending on the level of water in a tank.
- the control commands of the actuators have an influence on the performance of the network.
- a high trigger level for a discharge pump of a storm basin limits the amount of water discharged into the downstream network and thus limits the risk of flooding or spilling into the natural environment in the downstream network.
- a high level also limits the amount of water that can still be stored in case of heavy rain. The risk of spilling into the natural environment upstream of the storm basin is thus increased.
- the real-time management of a waste water system consists in adapting actuator control instructions to a rain event, in order to improve network performance.
- the performances are for example characterized by the location of urban floods and the quantity of spill in the natural environment or the quantity of energy implemented during this management.
- it is known to adapt the control commands of the actuators to predicted or measured rain.
- the Seine-Saint-Denis sewerage network described in the document "Real-time operation of the Seine-Saint-Denis sewerage network", JM Delattre, presented at the "Avanzada management of / drenaje” conference unrbano ", Barcelona, 2004, is based on a scenario approach.
- a typical rain approaching as close as possible to the actual and future rain in the area is selected from a sample of 27 rains.
- each rain-type corresponds a set of instructions of the actuators of the network.
- These sets of setpoints were predetermined, using a network modeling. It is also known to use an optimization algorithm to predetermine an optimum set of setpoints for a given rain-type, according to a model of the network.
- a wastewater system may include many structures and actuators.
- the inventors have found that in practice, a network almost always included at least one structure or an actuator unavailable or operating at reduced capacity.
- the unavailability may be due for example to a default or to a jobless for maintenance.
- the sets of setpoints are predetermined according to a model of the network which represents the nominal state of the network.
- the setpoints used can lead to an underperformance of the network when its state is not the nominal state.
- the aim of the invention is to provide a method of controlling a waste water network, having improved performance.
- the invention aims to use a set of instructions that leads to improved performance.
- the invention relates to a method for controlling a wastewater network, said network comprising actuators able to influence water flow rates in the network, the behavior of the actuators depending on instructions, the method comprising;
- control method further comprising
- the deposit set is selected not only according to the type of rain but also according to the current state of the network.
- the list of sets of set contains a set of instructions allowing to obtain improved performances, whatever the state of the network.
- the step of determining at least one new set of setpoints includes determining a new set set for each type of rain in the list of rain types.
- the step of determining at least one new set of instructions may comprise the execution of an optimization algorithm.
- the step of determining at least one new set of setpoints includes determining the network model based on a nominal network pattern and second status information.
- the network model used is an updated model.
- control method comprises:
- a simulated performance evaluation stage of the network based on a rain hyetogram of the rain event and the setpoint set selected during the rain event,
- control method comprises:
- a step of evaluating the first simulated performances of the network as a function of a rain hyetogram of the rain event and the setpoint set selected during the rain event, a step of evaluating second simulated performances of the network, as a function of said hyetogram of rain and of a setpoint set selected according to said hyetogram of rain,
- control method comprises:
- a simulated performance evaluation step of the network as a function of a rainfall hyetogram of the rain event and a setpoint set selected according to said hyetogram of rain,
- the invention also proposes a control device for a wastewater network, said network comprising actuators able to influence water flow rates in the network, the behavior of the actuators depending on setpoints, the control device.
- a control device for a wastewater network said network comprising actuators able to influence water flow rates in the network, the behavior of the actuators depending on setpoints, the control device.
- first state information representative of a current state of the network
- set of setpoints being selected from the list of predetermined set of sets according to the type of rain selected and the first state information
- the invention also provides a wastewater network comprising actuators capable of influencing water flow rates in the network, the behavior of the actuators depending on setpoints, and a control device according to the invention.
- the invention also relates to a computer program comprising instructions for executing the steps of the above-mentioned control method when said program is executed by a computer.
- This program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other form desirable shape.
- the invention also relates to a recording medium or information carrier readable by a computer, and comprising instructions of a computer program as mentioned above.
- the recording media mentioned above can be any entity or device capable of storing the program.
- the medium may comprise storage means, such as a ROM, for example a CD-ROM or a microelectronic circuit ROM, or magnetic recording means, for example a floppy disk or a disk. hard.
- the recording media may correspond to a transmissible medium such as an electrical or optical signal, which may be conveyed via an electrical or optical cable, by radio or by other means.
- the program according to the invention can be downloaded in particular on an Internet type network.
- the recording media may correspond to an integrated circuit in which the program is incorporated, the circuit being adapted to execute or to be used in the execution of the method in question.
- FIG. 1 represents a wastewater network enabling the implementation of a control method according to one embodiment of the invention
- FIG. 2 represents a control law of a pump of the network of FIG. 1,
- FIG. 3 represents a device for controlling the network of FIG. 1,
- FIG. 4 represents steps of a control method implemented by the control device of FIG. 3,
- FIG. 5 represents other steps of a control method implemented by the control device of FIG. 3, and
- FIG. 6 represents other steps of a control method implemented by the control device of FIG. 3.
- FIG. 1 represents a network 1 of wastewater intended to convey rainwater from an agglomeration to a purification station 4.
- the agglomeration is divided between a north zone 2 and a south zone 3.
- the network 1 comprises tanks S7 to S7, pumps
- Each tank S7 to S7 also includes a level sensor for measuring the height of water h in the tank.
- circles 5, 6 and 7 represent discharge points towards the natural environment, respectively in a first stream A5, a second stream A6 and a third stream A7.
- FIG. 2 is a graph which shows the behavior of the pumps PI to
- the flow rate Q of a pump is controlled according to the height h of water in the associated reservoir, measured by a sensor. Thus, if the height h is less than h stop / the pump is stopped. The water level will then rise until it reaches hstart. The pump then starts at flow Q mjn . Two possibilities then arise.
- the flow of waste water entering the tank is less than Q mtn and the water level will drop until h stop , which will cause the pump to stop. If the weather is rainy and the wastewater flow is greater than Q mfn , the water level will continue to rise and the pump will then increase its flow, until it stabilizes at the incoming water flow, or until reaching its maximum flow Q max .
- the water height h max at which the pump reaches its maximum flow rate Q max constitutes a control setpoint which indicates the tendency which one has to store in the tank (if h max is high) or to pump rapidly towards the downstream to avoid storage (if h max is low).
- the value of h max influences the performance of the network. Indeed, a high value of h max limits the amount of water discharged in the downstream network and therefore to limit the risk of flooding in the downstream network. However a high value of h max also limits the amount of water that can still be stored in case of heavy rain. The risk of spilling into the natural environment is therefore increased.
- the control device 8 is for example located in a control room of the network manager 1.
- Figure 3 shows the control device 8 in more detail. It presents the architecture of a computer and comprises in particular a processor 9, a non-volatile memory 10, a random access memory 11, and a communication interface 12.
- the processor 9 allows the execution of a control program of the network 1 stored in the memory 10, using the RAM 11.
- the memory 10 is an information carrier within the meaning of the invention and the control device 8 constitutes a control device within the meaning of the invention.
- the control device 8 stores, in the memory 10, a list of rain types, a list of states of the network, and a plurality of setpoints for the pumps PI to P10.
- the list of types of rain includes a homogeneous rain called "PLHO", and a stronger rain on the south zone 3 called "PLFS”.
- the state list of the network comprises a nominal state EN, in which the tanks S1 to S7, the pumps P1 to P10, the buffers T1 to T15 and the mains of the network 1 all function normally, and a first state of unemployment EC1. in which an intervention on the network requires to limit the flow rate Q m3X PI pumps and P2 at half their nominal flow Q max .
- the list of sets of setpoints includes a set of setpoints associated with each pair of rain type and network status, as shown in Table 1 where C1 to C4 represent sets of setpoints.
- the sets of instructions C1 to C4 have been predetermined in a manner to be described later.
- FIG. 4 represents steps of the control method implemented by the control device 8.
- the control device 8 obtains information on the current or expected rainfall on the agglomeration, for example from a weather station.
- the control device 8 also obtains information representative of the current state of the network 1, for example by consulting an intervention planning system or by consulting sensors capable of generating such information, for example a fault sensor of a pump.
- step E20 the control station 8 selects a type of rain from the list of rain types that best matches the rain determined in step E10.
- the control station 8 also selects, in the state list of the network, the state that best corresponds to the state determined in step E10.
- step E30 the control device 8 selects, in the list of set sets, the set of setpoints corresponding to the type of rain and the state of the network selected in step E20. For example, if the rain PLSF and the nominal state EN have been selected in step E20, the controller 8 selects the set of set C2 in step 30.
- step E40 the control device 8 sends the pumps P1 to P10 messages indicating the instructions to be used, that is to say the instructions of the set of set C2 in the case mentioned above.
- Steps E10 to E40 can be repeated.
- a new set of instructions which is better adapted to the conditions can be selected in step E30.
- the new set of setpoints selected will then provide better network performance, given the current or expected rain and network condition.
- FIG. 5 represents other steps of the control method implemented by the control device 8.
- the controller obtains state information representative of a current or intended state of the network, called state EC2.
- the status information may for example indicate a work that is unemployed or operating at a reduced capacity.
- the control device 8 can consult an intervention planning system or sensors capable of generating such information, as in step E10. It is assumed here that none of the states EN and EC1 of the list of predetermined states corresponds to the state information obtained. The state EC2 is therefore a new state of the network.
- step E60 the control device 8 determines an updated model of the network 1.
- the control device 8 updates a nominal model of the network 1, stored for example in the memory 10, depending on the information of state obtained in step E50.
- the updated model of network 1 reflects the current or expected EC2 state of the network.
- the control device 8 determines in step E70, for each type of rain of the list of types of rain, a set of instructions using the updated model.
- a reference set C5 is determined for the rain PLHO and the state EC2
- a set of set point C6 is determined for the rain PLFS and the state EC2.
- the control device 8 implements an optimization algorithm in order to determine the set of setpoints which optimizes the performance of the network 1, for a given rain and using the updated model.
- the implementation of the optimization algorithm can for example be performed as in the document cited in the introduction.
- the performance of the network 1 can be represented by a performance function defined by the network manager 1.
- the optimization algorithm then provides a set of instructions that minimizes the FP performance function.
- the optimization algorithm may be a multi-objective optimization algorithm that provides a plurality of solutions minimizing VA5, VA6 and VA7, followed by a selection among the solutions found according to the relative criticality of the rivers.
- the optimization algorithm can take into account constraints, for example boundaries between which must be the instructions to optimize,
- the sets of instructions C1 to C4 above have been predetermined in a similar way, using the optimization algorithm and the nominal model of the network 1 (games C1 and C2) or an updated model according to the state EC1 (games C3 and C4).
- step E80 the games C5 and C6 are added to the list of set sets, in correspondence with the types of rain PLHO and PLFS and the state of the network EC2.
- the list of sets of setpoints comprises a set of setpoints associated with each pair of rain type and network status, including the EC2 state of step E50. as shown in Table 2.
- step E80 is preceded by a step (not shown) of validation of the sets of instructions C5 and C6 by an operator.
- the optimization of the step E70 concerns only part of the setpoints of the network 1.
- the setpoints h max of the pumps P9 and P10 directly connected to the purification station 4 may be judged too much critical to be optimized.
- the optimization algorithm relates only to the h max setpoints of the other pumps PI to P8.
- the steps of FIG. 5 are executed for example periodically or in response to an order introduced by an operator.
- the steps of FIG. 5 can also be performed when the control device 8 detects, in step E10, a state of the network that does not correspond to any of the states of the predetermined state list.
- steps E50 to E80 when a new state of the network 1 is provided or detected, new sets of corresponding instructions are added to the list.
- the list of sets of setpoints contains sets of instructions allowing to obtain improved performances, whatever the state of the network.
- FIG. 6 represents other steps of the control method implemented by the control device 8. The steps of FIG. 6 are executed after a significant rain event.
- step F10 the control device 8 obtains data representative of the operation of the network 1 during the rain event. These data include, for example, the water levels in the tanks S1 to S7, the flows of the pumps P1 to P10 and the volumes or flows of the discharges A5 to A6. The control device 8 also obtains data representative of the rain that has actually fallen, for example a hyetogram of rain measured during the rain event. Finally, the controller 8 is aware of the set of setpoints selected for the rain event, as well as the type of rain selected and the corresponding selected network state.
- the controller 8 evaluates different values of the performance function FP of the network 1.
- step F20 the control device 8 evaluates the real performances FP (1) of the network 1.
- the value FP (1) is calculated as a function of the data representative of the operation of the network 1 during the rainy event, obtained in step F10.
- step F30 the control device 8 evaluates simulated performance FP (2) of the network 1 without reclassification of the rain.
- the control device 8 calculates the value FP (2) according to the hyetogram of rain obtained in step F10 and the set of set used during the rain event.
- step F40 the control device 8 evaluates simulated performance FP (3) of network 1 with reclassification of the rain.
- the control device 8 calculates the value FP (3) according to the hyetogram of rain obtained in step F10 and a set of instructions corresponding to the type of rain that should have been selected from the list of types of rain. , considering the rain actually fell.
- step F50 the control device 8 determines an optimum setpoint set for the rain actually fell, and in step F60 evaluates the optimal simulated performance FP (4) of the network 1.
- the control device 8 calculates the FP (4) value as a function of the rain hyetograph obtained in step F10 and the optimal set point set determined in step F50.
- the model of network 1 used is the model updated according to the network state selected for the rain event. Then, during the steps F70 to F100, the values FP (1) to FP (4) are compared and, in the steps F110 to F140, conclusions are established according to these comparisons.
- step F70 FP (1) is compared to FP (2). If a significant difference is found, it indicates that a device of the network 1 is defective.
- step F110 the comparison of measured and simulated flows and levels makes it possible to identify the equipment that failed. For example, if the measured flow rate of a pump peaks at a given level lower than the simulated flow rate of the pump, it indicates that the pump is defective. The control device 8 can then display a maintenance recommendation for this pump to the network manager 1.
- step F80 FP (2) is compared to FP (3). If a significant difference is found, it indicates that the rain-type selected for the rain event was far from the rain actually falling. In other words, rain detection and forecasting needs to be improved to better select the rain-type. Thus, in step F120, the control device 8 displays a recommendation for improving the detection and prediction of rain.
- step F90 FP (3) is compared to FP (4). If a significant difference is found, this indicates that the set of setpoints selected for the rain event was suboptimal.
- step F130 the controller 8 displays a recommendation to add a rain-type to the list of rain types, with the corresponding optimal setpoints.
- the control device 8 determines, for the new standard rain and for each network state of the network status list, a new set of instructions. For this purpose, the control device 8 implements an optimization algorithm, as explained above with reference to step E70.
- a significant difference means for example a difference greater than a predetermined threshold.
- step F100 FP (4), which represents the optimized performance of the network 1 for the fallen rain, is compared to a performance threshold. If the optimized performance is considered insufficient, then in step F140 the controller 8 displays a recommendation to study the improvement of the structure of the network 1 or its real-time management.
- the steps of FIG. 6 therefore make it possible, after a rain event, to diagnose the causes of a possible underperformance of the network 1, and to indicate the improvement tracks to be studied.
- the invention has been described above with reference to an embodiment in which the actuators of the network are pumps and the control instructions are heights h max .
- the invention may relate to other types of actuator, for example valves, and other types of control setpoint.
- the control law of the pumps may be different from that shown in Figure 2.
- the network status list initially comprises only the nominal state EN.
- the steps shown in FIG. 5 make it possible to add one or more additional states if necessary.
- the list of types of rain can be initially empty. In this case, if the control device 8 has sufficient computing power to implement the optimization algorithm in the time interval between the rain forecast and the actual occurrence of the rain, a first type of rain corresponding to the expected rain can be added to the list of types of rain with the determined set of instructions, before the appearance of the rain. The determined instructions can then be applied.
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR1057272A FR2964674B1 (en) | 2010-09-13 | 2010-09-13 | METHOD AND DEVICE FOR CONTROLLING A RESIDUAL WATER NETWORK |
PCT/FR2011/052043 WO2012035235A1 (en) | 2010-09-13 | 2011-09-07 | Method and device for controlling a waste water network |
Publications (2)
Publication Number | Publication Date |
---|---|
EP2616600A1 true EP2616600A1 (en) | 2013-07-24 |
EP2616600B1 EP2616600B1 (en) | 2017-10-04 |
Family
ID=43827685
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP11773041.6A Active EP2616600B1 (en) | 2010-09-13 | 2011-09-07 | Method and device for controlling a waste water network |
Country Status (5)
Country | Link |
---|---|
US (1) | US8660703B2 (en) |
EP (1) | EP2616600B1 (en) |
FR (1) | FR2964674B1 (en) |
HU (1) | HUE036544T2 (en) |
WO (1) | WO2012035235A1 (en) |
Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11183843B1 (en) | 2011-05-26 | 2021-11-23 | J. Carl Cooper | Power source load control |
US11522365B1 (en) | 2011-05-26 | 2022-12-06 | J. Carl Cooper | Inverter power source load dependent frequency control and load shedding |
US10879727B1 (en) * | 2011-05-26 | 2020-12-29 | James Carl Cooper | Power source load control |
CA2895061C (en) * | 2012-12-19 | 2021-10-19 | Jon Erik RASMUSSEN | Method, system, and apparatus for flood control |
WO2015030097A1 (en) * | 2013-08-28 | 2015-03-05 | 株式会社堀場エステック | Flow-rate control device and flow-rate control program |
US10501925B1 (en) | 2015-03-20 | 2019-12-10 | Christopher Conway Lavenson | Notifications for reducing overflows from combined sewer systems and sanitary sewer systems |
CN106599451B (en) * | 2016-12-12 | 2020-06-12 | 西安交通大学 | Multi-objective optimization method for RV reducer main bearing |
IL251373A0 (en) * | 2017-03-23 | 2017-07-02 | Jet Line Infrastructure Ltd | Sewer bypass system and method |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE4016373A1 (en) * | 1990-05-19 | 1991-11-21 | Vollmar Oskar Gmbh | Monitoring sewage network, esp. water mixing and removal network - by measuring data at numerous positions, storing, displaying and processing data |
WO2002095149A2 (en) * | 2002-05-17 | 2002-11-28 | Ads Corporation | Method and system for analyzing the effect of inflow and infiltration on a sewer system |
US20020170350A1 (en) * | 2001-05-18 | 2002-11-21 | Schutzbach James S. | Method and system for analyzing the effect of inflow and infiltration on a sewer system |
US7289923B2 (en) * | 2005-07-21 | 2007-10-30 | Nagare | System and method for fluid distribution |
US8293097B2 (en) * | 2008-03-17 | 2012-10-23 | Bowers Jr Gregory Scott | System for continuous optimization of wastewater treatment |
-
2010
- 2010-09-13 FR FR1057272A patent/FR2964674B1/en not_active Expired - Fee Related
-
2011
- 2011-01-26 US US13/013,951 patent/US8660703B2/en active Active
- 2011-09-07 WO PCT/FR2011/052043 patent/WO2012035235A1/en active Application Filing
- 2011-09-07 EP EP11773041.6A patent/EP2616600B1/en active Active
- 2011-09-07 HU HUE11773041A patent/HUE036544T2/en unknown
Non-Patent Citations (2)
Title |
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None * |
See also references of WO2012035235A1 * |
Also Published As
Publication number | Publication date |
---|---|
HUE036544T2 (en) | 2018-07-30 |
FR2964674A1 (en) | 2012-03-16 |
WO2012035235A1 (en) | 2012-03-22 |
FR2964674B1 (en) | 2012-10-12 |
EP2616600B1 (en) | 2017-10-04 |
US8660703B2 (en) | 2014-02-25 |
US20120065786A1 (en) | 2012-03-15 |
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