WO2014198475A1 - Procede de prevision d'instant de nettoyage de membrane et systeme associe - Google Patents

Procede de prevision d'instant de nettoyage de membrane et systeme associe Download PDF

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Publication number
WO2014198475A1
WO2014198475A1 PCT/EP2014/059766 EP2014059766W WO2014198475A1 WO 2014198475 A1 WO2014198475 A1 WO 2014198475A1 EP 2014059766 W EP2014059766 W EP 2014059766W WO 2014198475 A1 WO2014198475 A1 WO 2014198475A1
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WO
WIPO (PCT)
Prior art keywords
membrane system
output parameters
membrane
forecasting
instant
Prior art date
Application number
PCT/EP2014/059766
Other languages
English (en)
Inventor
Amit Purohit
Srnivas MEKAPATI
Vinay KARIWALA
Original Assignee
Abb Ag
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Abb Ag filed Critical Abb Ag
Publication of WO2014198475A1 publication Critical patent/WO2014198475A1/fr

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01D—SEPARATION
    • B01D65/00—Accessories or auxiliary operations, in general, for separation processes or apparatus using semi-permeable membranes
    • B01D65/02—Membrane cleaning or sterilisation ; Membrane regeneration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01D—SEPARATION
    • B01D61/00—Processes of separation using semi-permeable membranes, e.g. dialysis, osmosis or ultrafiltration; Apparatus, accessories or auxiliary operations specially adapted therefor
    • B01D61/02—Reverse osmosis; Hyperfiltration ; Nanofiltration
    • B01D61/12—Controlling or regulating
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F1/00—Treatment of water, waste water, or sewage
    • C02F1/008—Control or steering systems not provided for elsewhere in subclass C02F
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F1/00—Treatment of water, waste water, or sewage
    • C02F1/44—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis
    • C02F1/441—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis by reverse osmosis
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01D—SEPARATION
    • B01D2321/00—Details relating to membrane cleaning, regeneration, sterilization or to the prevention of fouling
    • B01D2321/40—Automatic control of cleaning processes
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F1/00—Treatment of water, waste water, or sewage
    • C02F1/44—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis
    • C02F1/442—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis by nanofiltration
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F1/00—Treatment of water, waste water, or sewage
    • C02F1/44—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis
    • C02F1/444—Treatment of water, waste water, or sewage by dialysis, osmosis or reverse osmosis by ultrafiltration or microfiltration
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2103/00—Nature of the water, waste water, sewage or sludge to be treated
    • C02F2103/08—Seawater, e.g. for desalination
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2209/00—Controlling or monitoring parameters in water treatment
    • C02F2209/001—Upstream control, i.e. monitoring for predictive control
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2209/00—Controlling or monitoring parameters in water treatment
    • C02F2209/005—Processes using a programmable logic controller [PLC]
    • C02F2209/006—Processes using a programmable logic controller [PLC] comprising a software program or a logic diagram
    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F2303/00—Specific treatment goals
    • C02F2303/16—Regeneration of sorbents, filters

Definitions

  • This invention for forecasting instant of membrane cleaning is applicable for semi-permeable membrane system and in particular relates to semi-permeable membrane system operating on Programmable Logic Controller (PLC).
  • PLC Programmable Logic Controller
  • Semi-permeable membrane system is used for purification, separation and decontamination of aqueous solutions containing water as a solvent. Such system is used for desalination of brackish or sea-water, demineralization of water, treatment of water and waste-water.
  • Semi-permeable membrane system includes reverse osmosis membrane system or nano-filtration membrane system or ultra-filtration membrane system or the like.
  • a reverse osmosis membrane system involves process of reverse osmosis, in which solvent moves across a semi-permeable membrane against concentration gradient.
  • Reverse osmosis membrane system diffuses water molecules across a semi-permeable membrane from higher solute concentration side to lower solute concentration side with pressure applied on higher solute concentration side.
  • feed water is passed through a semi-permeable membrane leaving solid particles trapped across the surface of membrane.
  • Fouling results in decreased performance of membrane system due to accumulated solid particles on the membrane surface in turn resulting in decreased filtrate flow rate and increased pressure drop across membrane.
  • higher pressure is required to be applied at the feed solution chamber resulting in higher energy consumption.
  • the use of higher pressure can increase the rate of fouling and may even damage the membrane.
  • Membrane cleaning removes accumulated salt and/or solid particles on the membrane surface. Membrane cleaning is a crucial maintenance activity to increase efficiency and reduce the energy consumption of the semi-permeable membrane systems or in other words, to regain the performance lost due to membrane fouling.
  • a modification of the above referred earlier known method employs proprietary correction factors in normalizing output variables such as permeate flow rate.
  • the modified method may still be inaccurate due to the empirical normalization process involved, even though there is an improved accuracy over the previously referred method.
  • a method for forecasting instant of membrane cleaning is based on first principles model and has better accuracy than the above mentioned methods. This is suitable only for deployment on computer or server and not on PLCs since PLCs have lower memory and processing capability which does not support complex computations involved in this method.
  • the present invention addresses the above need by implementing a method and a system for forecasting instant of membrane cleaning in semi-permeable membrane systems operating on PLCs.
  • This invention for forecasting instant of membrane cleaning in semi-permeable membrane system more particularly relates to semi-permeable membrane system operating on PLCs.
  • the semi-permeable membrane system is modeled based on mathematical model such as first principles based steady state model.
  • the design values of the output parameters of the membrane system model i.e the membrane system model output, are calculated by solving mathematical equations, where the output parameters of the membrane system model include product flow rate, product concentration, and reject pressure of the membrane system.
  • the measured values of output parameters of the membrane system are obtained by measuring the output parameters such as product flow rate, product concentration and reject pressure of the membrane system.
  • the deviation between design values of output parameters of the membrane system model for current/actual input values and measured values of the membrane system is computed.
  • the deviation computed is forecasted by time series forecasting technique such as Additive Holt Winters technique.
  • the forecasting helps in determining the instant at which the deviations that are forecasted cross an appropriately selected threshold value. These deviations of each of the output parameters of the membrane system may not cross their respective threshold value at the same instant.
  • a Key Performance Indicator (KPI) is computed based on each of the deviations of the output parameters of the membrane system that are forecasted.
  • the KPI computed is used to forecast instant of membrane cleaning to reduce the effect of fouling on the performance of the membrane system.
  • Fig. 1 shows the reverse osmosis membrane system for desalination of saline water described merely as an example of a semi-permeable system.
  • Fig. 2 shows the system for forecasting instant of membrane cleaning in a semi-permeable membrane system operating on PLC.
  • Fig. 3 shows the non-linear characteristics of deviations of the output parameters of the membrane system with respect to time.
  • RO membrane system 11 for desalination of saline water as shown in Fig. 1 is described as a non-limiting example of the semi -permeable membrane system.
  • the RO membrane system 11 consists of two chambers: feed water chamber 7 and product chamber 10 separated by a semipermeable membrane 6.
  • the semi-permeable membrane 6 comprises of a separation layer 4 and a support layer 5.
  • Feed water 1, which is saline water is fed into the feed water chamber 7 and high pressure is applied across the feed water chamber 7.
  • Semi-permeable membrane 6 at such high pressure typically in the range of 60-70 atm, allows passage of water molecules from the feed water chamber 7 into the product chamber 10.
  • the remaining unfiltered feed water is ejected out as reject water 3.
  • Salt and/or solid particles 8 present in the feed water 1 get accumulated on the surface of the membrane 6 resulting in fouling 9 of the semi-permeable membrane 6. Due to the effect of fouling 9, the semi-permeable membrane 6 is blocked and the desired permeate flow rate of the product 2 decreases.
  • the system 12 for forecasting instant of membrane cleaning in a semi-permeable membrane system is as shown in Fig. 2.
  • the RO membrane system 11 is modeled based on mathematical model such as first principles based steady state model. This modeling is performed to separate the effect of fouling on the output parameters such as product flow rate, product concentration and reject pressure of the membrane system.
  • the design values of the output parameters of the membrane system model are calculated by solving mathematical and data modeling equations for actual feed conditions.
  • the output parameters of the membrane system is measured which constitute the measured values of output parameters of the membrane system.
  • the deviation of output parameters of membrane system between design values of output parameters of the membrane system model and measured values of output parameters of the membrane system is computed.
  • a deviation computing unit 13 computes these deviations of output parameters of the membrane system at regular time intervals.
  • the deviations of output parameters of the membrane system exhibit non-linear characteristics with respect to time.
  • Each of these deviations of output parameters of the membrane system such as product flow deviation, salt passage deviation, pressure drop deviation move non-linearly with time as depicted in Fig. 3.
  • This non-linear characteristic of these deviations necessitates forecasting the instant of membrane cleaning by applying time series forecasting technique.
  • Each of the deviations of the output parameters of the membrane system are forecasted by deviation forecasting unit 14 using time series forecasting technique such as Additive Holt Winters technique.
  • time series forecasting technique such as Additive Holt Winters technique.
  • Each of these deviations of output parameters that are forecasted may not cross their respective threshold values defined by manufacturer at the same instant.
  • KPI computing unit 15 computes a single KPI, based on each of the deviations of output parameters of the membrane system that are forecasted, to determine the instant at which the KPI crosses the specified threshold, which in turn determines the time at which membrane cleaning is to be performed.
  • KPI include weighted sum of deviations and maximum or minimum values among all the deviations.
  • This invention is computationally less complex and hence requires lesser memory capacity than the earlier known methods.
  • This invention is not limited to desalination of saline water, but is applicable in other purification, separation and decontamination processes of aqueous solutions such as demineralization of water, treatment of water and waste-water.

Abstract

La présente invention concerne un procédé et un système pour la prévision d'instant de nettoyage de membrane dans un système de membrane semi-perméable fonctionnant sur un ​​Contrôleur Logique Programmable (PLC). Le système comprend une unité de calcul d'écart-type, une unité de prévision d'écart-type et une unité de calcul KPI. Un système de membrane semi-perméable est modélisé sur la base d'un modèle mathématique comme le modèle d'état d'équilibre fondé sur les premiers principes. L'écart-type des paramètres de sortie du système de membrane entre des valeurs de conception de paramètres de sortie du modèle de système de membrane et des valeurs mesurées du système de membrane est calculé par une unité de calcul d'écart-type. Ces écarts-type des paramètres de sortie du système de membrane sont prévus par une unité de prévision d'écart-type utilisant une technique de prévision en séries temporelles comme la technique Holt Winters additive. Une unité de calcul KPI calcule l'indicateur de performance clé (KPI) pour déterminer l'instant où le KPI passe la valeur seuil, qui à son tour détermine l'instant où le nettoyage de membrane doit être effectué pour améliorer l'efficacité du système de membrane semi-perméable.
PCT/EP2014/059766 2013-06-14 2014-05-13 Procede de prevision d'instant de nettoyage de membrane et systeme associe WO2014198475A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IN710KO2013 2013-06-14
IN710/KOL/2013 2013-06-14

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WO2014198475A1 true WO2014198475A1 (fr) 2014-12-18

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104609610A (zh) * 2015-03-06 2015-05-13 淄博泰禾实业有限公司 全膜法处理反渗透浓水及循环排污水的方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007006153A1 (fr) * 2005-07-12 2007-01-18 Zenon Technology Partnership Commande de processus pour un systeme a membrane immergee
WO2008132186A1 (fr) * 2007-04-27 2008-11-06 Vlaamse Instelling Voor Technologisch Onderzoek (Vito) Systeme et procede de commande de surveillance pour nettoyage de membrane
JP2009000580A (ja) * 2007-06-19 2009-01-08 Hitachi Ltd 膜ろ過処理装置の運転支援装置
WO2009104035A1 (fr) * 2008-02-19 2009-08-27 Abb Research Limited Gestion en ligne des performances d'un processus de séparation à membrane
WO2010109265A1 (fr) * 2009-03-27 2010-09-30 Abb Research Ltd Procédé et système pour une optimisation en ligne d'un processus de filtration sur membrane
WO2011153625A2 (fr) * 2010-06-10 2011-12-15 Ramila Hishantha Peiris Procédé de prévision de colmatage basée sur la fluorescence et optimisation des opérations de filtration sur membrane

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007006153A1 (fr) * 2005-07-12 2007-01-18 Zenon Technology Partnership Commande de processus pour un systeme a membrane immergee
WO2008132186A1 (fr) * 2007-04-27 2008-11-06 Vlaamse Instelling Voor Technologisch Onderzoek (Vito) Systeme et procede de commande de surveillance pour nettoyage de membrane
JP2009000580A (ja) * 2007-06-19 2009-01-08 Hitachi Ltd 膜ろ過処理装置の運転支援装置
WO2009104035A1 (fr) * 2008-02-19 2009-08-27 Abb Research Limited Gestion en ligne des performances d'un processus de séparation à membrane
WO2010109265A1 (fr) * 2009-03-27 2010-09-30 Abb Research Ltd Procédé et système pour une optimisation en ligne d'un processus de filtration sur membrane
WO2011153625A2 (fr) * 2010-06-10 2011-12-15 Ramila Hishantha Peiris Procédé de prévision de colmatage basée sur la fluorescence et optimisation des opérations de filtration sur membrane

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104609610A (zh) * 2015-03-06 2015-05-13 淄博泰禾实业有限公司 全膜法处理反渗透浓水及循环排污水的方法

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