Operating condition derivation device, operating condition derivation method, and operating condition derivation program

Abstract

To easily derive an optimum operating condition for a wastewater treatment system.SOLUTION: A method of deriving an optimal operating condition for a wastewater treatment system includes: based on a mathematical model of a wastewater treatment facility that converts treatment target water into treated water purified by biological treatment, an operational condition, and a water quality of the treatment target water, calculating a predicted value of an operating state of the wastewater treatment facility, including a predicted water quality value of the treated water; based on a mathematical model of a related facility that performs water treatment other than the biological treatment in relation to the wastewater treatment facility and at least the operating condition of the related facility, calculating a predicted value of an operating state of the related facility; and calculating an objective function value based on the predicted value of the operating condition of the related facility and the predicted value of the operating condition of the wastewater treatment facility, in which the operating condition of the related facility and the wastewater treatment facility when the objective function value is minimized within a range in which the predicted water quality value of the treated water satisfies a predetermined condition on the treated water quality are retrieved as the optimal operating condition of the wastewater treatment system.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an operating condition derivation device, an operating condition derivation method, and an operating condition derivation program for deriving optimal operating conditions of a wastewater treatment system.

Background Art

[0002] Conventionally, a wastewater treatment system has been proposed that purifies wastewater to be treated (hereinafter referred to as target water to be treated) by biological treatment using microorganisms. In the field of water treatment, biological treatment is a process of decomposing organic substances (organic pollutants) contained in the target water to be treated by a biological reaction of microorganisms. Generally, a wastewater treatment system includes wastewater treatment facilities that purify the target water to be treated by biological treatment. The wastewater treatment facility includes a reaction tank for performing biological treatment of the target water to be treated, and biologically treats the target water to be treated that has flowed into the reaction tank with various microorganisms such as activated sludge. Thereby, the wastewater treatment facility obtains water (hereinafter referred to as treated water) that has purified the target water to be treated. The treated water obtained by the wastewater treatment facility is discharged to the outside after being subjected to appropriate treatment such as removal of suspended substances and disinfection.

[0003] As a tool for exploring the optimal operating conditions of such a wastewater treatment system, a process model that simulates the biological treatment process of the target water to be treated performed in the wastewater treatment facility is used. The process model is a mathematical model based on physicochemical insights such as the activated sludge model proposed by the International Water Association (IWA). In the process model, the biological reaction of microorganisms in the biological treatment process of the target water to be treated is expressed by a plurality of mathematical formulas using model parameters as variables. By inputting observed values such as the flow rate and organic matter concentration of the target water to be treated actually observed from the wastewater treatment facility, such a process model can output predicted values useful for exploring the optimal operating conditions of the wastewater treatment system.

[0004] However, in the biological treatment process of the water to be treated described above, the biological reactions of the various microorganisms mixed in the reaction tank change complexly with changes in the treatment conditions such as the water quality and inflow rate of the water to be treated. Therefore, in order to continuously and accurately represent the above complex biological reactions by a process model, as the treatment conditions of the biological treatment process change over time, many model parameters included in the process model need to be adjusted through trial and error based on the above treatment conditions and empirical rules.

[0005] On the other hand, for example, Patent Document 1 discloses a model-reference type automatic control device for a water treatment apparatus, which includes data collection means for collecting operation data of the water treatment apparatus, a mathematical model expressing the main part of the water treatment process by a mathematical formula described by model parameters, a language model qualitatively expressing the water treatment process by integrating past empirical information, operation means for operating the water treatment apparatus, and control means for controlling the operations of these data collection means, mathematical model, language model, and operation means. In the prior art described in Patent Document 1, the mathematical model predicts the operation results of the water treatment apparatus. The language model has knowledge about the properties of the water treatment process that are not expressed by the above mathematical model, judges the operation status of the water treatment apparatus based on the operation data, and selects and calibrates the model parameters to be calibrated of the above mathematical model according to the judged operation status.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] However, in the apparatus described in Patent Document 1, in order to construct the above-described mathematical model and language model, it is necessary to collect a vast amount of data on the biological treatment process of the water to be treated. Furthermore, a great deal of effort is required for the algorithm implementation of these models. Therefore, since a great deal of time and labor (i.e., human cost) is required for model construction, there is a problem that it is difficult to utilize these models as a tool for exploring optimal operating conditions.

[0008] Also, in the field of wastewater treatment, in recent years, there has been a demand for easily exploring and deriving the optimal operating conditions of the entire wastewater treatment system, including not only the above-described wastewater treatment facilities but also related facilities for performing water treatment other than biological treatment, such as facilities for removing large foreign matters such as garbage from the water to be treated at the front stage of the wastewater treatment facilities.

[0009] The present invention has been made in view of the above circumstances, and an object thereof is to provide an operating condition derivation device, an operating condition derivation method, and an operating condition derivation program capable of easily deriving the optimal operating conditions of a wastewater treatment system.

Means for Solving the Problems

[0010] In order to solve the above-described problems and achieve the object, an operating condition derivation device according to the present invention is an operating condition derivation device that derives the optimum operating conditions of a wastewater treatment system including a wastewater treatment facility that purifies wastewater to be treated into treated water by biological treatment and an associated facility that performs water treatment other than the biological treatment in relation to the wastewater treatment facility. Based on an associated facility model that simulates the operation of the associated facility and at least the operating conditions of the associated facility, a predicted value of the operating state of the associated facility is calculated. Based on a wastewater treatment facility model that simulates the operation of the wastewater treatment facility, the operating conditions of the wastewater treatment facility, and the water quality of the wastewater to be treated, a model calculation unit calculates a predicted value of the operating state of the wastewater treatment facility including a predicted value of the water quality of the treated water. An objective function value is calculated based on the predicted value of the operating state of the associated facility and the predicted value of the operating state of the wastewater treatment facility, and the operating conditions of the associated facility and the wastewater treatment facility when the objective function value is minimized within a range where the predicted value of the water quality of the treated water satisfies the constraint conditions preset for the water quality of the treated water are searched for as the optimum operating conditions of the wastewater treatment system. It is characterized by comprising an operating condition search unit.

[0011] Further, the operating condition derivation device according to the present invention, in the above invention, a data collection unit that collects the operating conditions of the wastewater treatment system and the observed values observed from the wastewater treatment system operating according to the operating conditions, and based on each initial model of the preset associated facility model and the wastewater treatment facility model and the operating conditions of the wastewater treatment system by the data collection unit, a predicted value of the operating state of each of the associated facility and the wastewater treatment facility is derived, and the parameters of each of the initial models are adjusted so as to reduce the error between the derived predicted value of each operating state and the observed value by the data collection unit, and a model construction unit that constructs the associated facility model and the wastewater treatment facility model. It is characterized by comprising.

[0012] Further, the operating condition derivation device according to the present invention, in the above invention, further comprises a condition setting unit that receives an input of treated water quality information for specifying the water quality of the treated water and variably sets the constraint conditions according to the received treated water quality information.

[0013] Further, the operating condition derivation device according to the present invention, in the above invention, further includes an operation control unit that controls the operations of the related equipment and the wastewater treatment equipment based on the optimal operating conditions searched by the operating condition search unit.

[0014] Further, the operating condition derivation device according to the present invention, in the above invention, the operating condition search unit determines whether the predicted water quality value of the treated water satisfies the constraint conditions. If the constraint conditions are not satisfied, at least one value among the operating conditions of the related equipment and the wastewater treatment equipment and the water quality of the wastewater to be treated is changed in a direction that improves the predicted water quality value of the treated water so as to satisfy the constraint conditions. When the constraint conditions are satisfied, the at least one value is changed in a direction that reduces the objective function value. The model calculation unit repeatedly calculates the predicted value of the operating state of the related equipment and the predicted value of the operating state of the wastewater treatment equipment using the operating conditions of the related equipment and the wastewater treatment equipment including the changed values by the operating condition search unit and the water quality of the wastewater to be treated until the optimal operating conditions are searched.

[0015] Further, the operating condition derivation device according to the present invention, in the above invention, the related equipment model includes at least a power model that calculates the power consumption amount during the operation of the related equipment from the operating conditions of the related equipment as the predicted value of the operating state of the related equipment. The wastewater treatment equipment model includes a water quality model that calculates the predicted water quality value of the treated water from the operating conditions of the wastewater treatment equipment and the water quality of the wastewater to be treated, and a power model that calculates the power consumption amount during the operation of the wastewater treatment equipment from the operating conditions of the wastewater treatment equipment as the predicted value of the operating state of the wastewater treatment equipment.

[0016] In addition, the operating condition derivation method according to the present invention is an operating condition derivation method for deriving the optimal operating conditions of a wastewater treatment system including a wastewater treatment facility that treats target wastewater into treated water purified by biological treatment, and an associated facility that performs water treatment other than the biological treatment in relation to the wastewater treatment facility. In the method, a predicted value of the operating state of the associated facility is calculated based on an associated facility model that simulates the operation of the associated facility and at least the operating conditions of the associated facility. A model calculation step of calculating a predicted value of the operating state of the wastewater treatment facility including a predicted value of the water quality of the treated water based on a wastewater treatment facility model that simulates the operation of the wastewater treatment facility, the operating conditions of the wastewater treatment facility, and the water quality of the target wastewater; An objective function value calculation step of calculating an objective function value based on the predicted value of the operating state of the associated facility and the predicted value of the operating state of the wastewater treatment facility; A determination step of determining whether a constraint condition preset for the water quality of the treated water is satisfied by the predicted value of the water quality of the treated water; An operating condition search step of searching for the operating conditions of the associated facility and the wastewater treatment facility when the objective function value is minimized within a range where the constraint condition is satisfied by the predicted value of the water quality of the treated water as the optimal operating conditions of the wastewater treatment system. It is characterized by including.

[0017] In addition, the operating condition derivation program according to the present invention causes a computer to execute the above operating condition derivation method.

Effect of the Invention

[0018] According to the present invention, there is an effect that the optimal operating conditions of the wastewater treatment system can be easily derived.

Brief Description of the Drawings

[0019]

Figure 1

Figure 2

Figure 3

Best Mode for Carrying Out the Invention

[0020] Hereinafter, with reference to the drawings, preferred embodiments of the operating condition derivation device, the operating condition derivation method, and the operating condition derivation program according to the present invention will be described in detail. Note that the present invention is not limited by this embodiment. Also, the drawings are schematic, and it should be noted that the dimensional relationships between elements, the ratios of the elements, etc. may be different from the actual ones. There may also be parts where the dimensional relationships and ratios are different between the drawings.

[0021] FIG. 1 is a block diagram showing a configuration example of an operating condition derivation device according to an embodiment of the present invention. In FIG. 1, in addition to the operating condition derivation device 1 according to this embodiment, a wastewater treatment system 100 to which the operating condition derivation device 1 is applied is shown. In this FIG. 1, the flow of substances is indicated by solid arrows, and the flow of signals is indicated by broken arrows. Hereinafter, first, the wastewater treatment system 100 will be described, and then the operating condition derivation device 1 will be described.

[0022] (Wastewater Treatment System) First, the wastewater treatment system 100 will be described. The wastewater treatment system 100 is a system for treating sludge containing wastewater (also referred to as sewage) from various places such as homes and factories, and purifying the wastewater in the sludge. For example, as shown in FIG. 1, the wastewater treatment system 100 includes a sludge dewatering facility 110 that extracts wastewater to be treated (water to be treated) from the sludge, and a wastewater treatment facility 120 that purifies the water to be treated by biological treatment.

[0023] The sludge dewatering facility 110 is an example of related equipment that performs water treatment other than biological treatment in relation to the wastewater treatment facility 120. Specifically, as shown in FIG. 1, the sludge dewatering facility 110 includes a solid-liquid separator 111 for extracting water to be treated from the sludge, and is arranged at the front stage (inflow end side) of the wastewater treatment facility 120.

[0024] The sludge dewatering equipment 110 receives the sludge flowing in from the outside (hereinafter sometimes referred to as the inflowing sludge), and the received sludge flows into the solid-liquid separator 111 through pipes or the like. The solid-liquid separator 111 is composed of a filter, a centrifugal separator, or the like, and separates the above-mentioned inflowing sludge into dewatered sludge and drainage by water treatment such as filtration or centrifugation. The dewatered sludge referred to here is a solid substance after extracting the drainage from the sludge before water treatment (sludge containing drainage), and is a substance unsuitable for the drainage treatment (that is, biological treatment of the water to be treated by microorganisms) in the subsequent drainage treatment equipment 120. Examples of such unsuitable substances (hereinafter referred to as unsuitable substances) include substances such as garbage such as plastic containers and papers, which do not contribute to the biological treatment of the water to be treated and cause an increase in the load on the drainage treatment equipment 120. The dewatered sludge removed from the inflowing sludge by the solid-liquid separator 111 as described above is discharged from the sludge dewatering equipment 110 and disposed of by an external facility or the like. On the other hand, the drainage from which the dewatered sludge has been removed is sent as the drainage (water to be treated) to be treated by the drainage treatment equipment 120 from the solid-liquid separator 111 to the drainage treatment equipment 120 by a conveying device (not shown) such as a pipe.

[0025] The drainage treatment equipment 120 is a facility (plant) that purifies the water to be treated received from the sludge dewatering equipment 110 into treated water by biological treatment. In the present embodiment, the drainage treatment equipment 120 uses microorganisms to biologically treat the water to be treated by a method such as the anaerobic anoxic aerobic method, thereby purifying the water to be treated. Such a drainage treatment equipment 120 includes, for example, as shown in FIG. 1, a primary sedimentation tank 121, a reaction tank 122, and a final sedimentation tank 126.

[0026] Initially, the primary sedimentation tank 121 is arranged at the inflow end side of the water to be treated in the wastewater treatment facility 120, as shown in FIG. 1 for example, and receives the water to be treated (hereinafter sometimes referred to as influent water) flowing in from the previous sludge dewatering facility 110. The water to be treated contains organic substances (organic pollutants) and the like. The primary sedimentation tank 121 precipitates the impurities in the influent water received as described above, thereby separating the influent water into the water to be treated and the impurities. The impurities are the impurities such as suspended substances that could not be completely removed in the previous sludge dewatering facility 110. The impurities removed by the primary sedimentation tank 121 are discharged from the wastewater treatment facility 120 and disposed of by an external facility or the like. On the other hand, the water to be treated from which the impurities have been removed is sent from the primary sedimentation tank 121 to the subsequent reaction tank 122 by a conveying device (not shown) such as a pipe.

[0027] The reaction tank 122 functions as a reaction tank for biologically treating the water to be treated sent from the primary sedimentation tank 121 by microorganisms. As shown in FIG. 1 for example, the reaction tank 122 includes an anaerobic tank 123 where anaerobic biological treatment is performed, an anoxic tank 124 where biological treatment (denitrification treatment etc.) is performed in an anoxic state, and an aerobic tank 125 where aerobic biological treatment is performed.

[0028] The anaerobic tank 123, the anoxic tank 124, and the aerobic tank 125 each contain a microbial group such as activated sludge and biologically treat the water to be treated. In the present embodiment, the anaerobic tank 123, the anoxic tank 124, and the aerobic tank 125 are arranged in the order of the anaerobic tank 123, the anoxic tank 124, and the aerobic tank 125 in the flow direction of the water to be treated, as shown in FIG. 1 for example. That is, the anaerobic tank 123, the anoxic tank 124, and the aerobic tank 125 are arranged such that biological treatment in an anaerobic state and aerobic biological treatment are sequentially performed after anaerobic biological treatment is performed on the water to be treated.

[0029] Specifically, the anaerobic tank 123 receives the water to be treated that has flowed in from the primary sedimentation tank 121 via pipes or the like. In the anaerobic tank 123, anaerobic microorganisms among the microbial population contained in the activated sludge perform anaerobic biological treatment on the water to be treated. Examples of such anaerobic biological treatment include a phosphorus release treatment in which organic matter in the water to be treated is taken up by phosphate-removing bacteria and phosphate is released from the phosphate-removing bacteria as a process (first stage) of phosphate removal treatment.

[0030] The anoxic tank 124 receives the water to be treated (the water to be treated on which anaerobic biological treatment has been performed) that has flowed in from the anaerobic tank 123 via pipes or the like. Further, the anoxic tank 124 receives the nitrification mixture that has been circulated (returned) from the aerobic tank 125 via pipes by the action of a pump or the like. The nitrification mixture is a liquid containing nitrate in an ionic state, which is generated by oxidizing (nitrifying) ammonia through aerobic biological treatment in the aerobic tank 125. That is, the water to be treated in the anoxic tank 124 contains nitrate ions due to the nitrification of ammonia. In the anoxic tank 124, microorganisms (denitrifying bacteria) that prefer an anoxic state among the microbial population contained in the activated sludge perform biological treatment on the water to be treated in an anoxic state. Examples of such biological treatment in an anoxic state include a treatment in which nitrate ions in the water to be treated are decomposed by denitrifying bacteria into water and nitrogen gas. The nitrogen gas decomposed from the water to be treated as described above is released from the anoxic tank 124 to the outside (the atmosphere).

[0031] The aerobic tank 125 is equipped with an oxygen dissolution device (not shown) such as a blower for aeration. The aerobic tank 125 receives the water to be treated (the water to be treated in which anaerobic biological treatment and biological treatment in an anoxic state have been sequentially performed) flowing in from the anoxic tank 124 via a pipe or the like, and aerates the received water to be treated. In the aerobic tank 125, aerobic microorganisms among the microbial groups contained in the activated sludge perform aerobic biological treatment on the water to be treated. Examples of the aerobic biological treatment include a treatment of decomposing organic substances in the water to be treated into water and carbon dioxide gas using oxygen (dissolved oxygen) dissolved in the liquid in the aerobic tank 125, a treatment of nitrifying ammonia (ammonia nitrogen) in the water to be treated into nitric acid (nitrate nitrogen) by the action of nitrifying bacteria (nitrification reaction), and a treatment of taking in and removing phosphoric acid released in the anaerobic tank 123 described above by phosphate-removing bacteria, etc.

[0032] The reaction tank 122 obtains treated water obtained by purifying the water to be treated by subjecting the water to be treated to biological treatment as described above. The obtained treated water is sent from the reaction tank 122 (the aerobic tank 125 in this embodiment) to the subsequent final sedimentation tank 126 by a conveying device (not shown) such as a pipe.

[0033] Note that the anaerobic tank 123 may be composed of a single anaerobic tank, or may be composed of a plurality of anaerobic tanks communicating with each other via a pipe or the like. Further, these plurality of anaerobic tanks may be connected in series or in parallel via a pipe or the like. Similarly, the anoxic tank 124 may be composed of a single anoxic tank, or may be composed of a plurality of anoxic tanks communicating with each other via a pipe or the like. Further, these plurality of anoxic tanks may be connected in series or in parallel via a pipe or the like. The aerobic tank 125 may be composed of a single aerobic tank, or may be composed of a plurality of aerobic tanks communicating with each other via a pipe or the like. Further, these plurality of aerobic tanks may be connected in series or in parallel via a pipe or the like.

[0034] The final sedimentation tank 126 is arranged on the outflow end side of the treated water in the wastewater treatment facility 120 as shown in FIG. 1, for example, and receives the treated water biologically treated (purified) by the reaction tank 122. Also, a part of the activated sludge flows into the final sedimentation tank 126 together with the treated water from the reaction tank 122 (aeration tank 125 in this embodiment). The final sedimentation tank 126 sediments the activated sludge in the received treated water as described above, thereby separating the treated water from the activated sludge. The treated water thus obtained is sent from the final sedimentation tank 126 to a subsequent disinfection device (not shown) through pipes or the like. The sent treated water is disinfected by the disinfection facility and then discharged outside the wastewater treatment facility 120.

[0035] Also, as shown in FIG. 1, a part of the activated sludge sedimented in the final sedimentation tank 126 is returned as return sludge from the final sedimentation tank 126 to the reaction tank 122 by a conveying device (not shown) such as a pipe. At this time, the return sludge merges with the water to be treated from the primary sedimentation tank 121 and is sequentially returned to each of the anaerobic tank 123, anoxic tank 124, and aeration tank 125 together with the water to be treated. Thereby, the concentration of the activated sludge in the reaction tank 122 (particularly in the aeration tank 125) can be maintained constant. Also, the remainder of the sedimented activated sludge is discharged outside the wastewater treatment facility 120 as excess sludge from the final sedimentation tank 126 by a conveying device such as a pipe as shown in FIG. 1.

[0036] (Operation condition derivation device) Next, the operation condition derivation device 1 according to the embodiment of the present invention will be described. The operation condition derivation device 1 is a device that derives the optimal operation conditions of the above-described wastewater treatment system 100, and as shown in FIG. 1, includes a data collection unit 10, an arithmetic processing unit 20, a process control unit 30, an input unit 40, a condition setting unit 50, a visualization unit 60, and an operation control unit 70.

[0037] The data collection unit 10 collects process data that can be actually measured (observed) during the operation of the wastewater treatment system 100. Examples of the above process data include the operating conditions of the wastewater treatment system 100 and observed values.

[0038] Examples of the operating conditions of the wastewater treatment system 100 include the operating conditions of each of the sludge dewatering facility 110 and the wastewater treatment facility 120. Examples of the operating conditions of the sludge dewatering facility 110 include the flow rate of the influent sludge to the solid-liquid separator 111. Examples of the operating conditions of the wastewater treatment facility 120 include the flow rate of the influent water to the primary sedimentation tank 121 (the inflow rate of the water to be treated), the aeration volume of the aerobic tank 125, the return volume of the returned sludge from the final sedimentation tank 126 to the reaction tank 122, the return volume of the nitrification mixture from the aerobic tank 125 to the anoxic tank 124, etc.

[0039] The observed value of the wastewater treatment system 100 is a value (actual measured value) observed from the wastewater treatment system 100 operating according to the above operating conditions. In the present embodiment, the observed value of the wastewater treatment system 100 includes the observed value of the sludge dewatering facility 110 and the observed value of the wastewater treatment facility 120. Examples of the observed value of the sludge dewatering facility 110 include the properties of the influent sludge, the discharge amount of the dewatered sludge removed from the influent sludge, the flow rate and water quality of the wastewater (water to be treated) from which the dewatered sludge has been removed, etc. Examples of the observed value of the wastewater treatment facility 120 include the water quality of the influent water to the primary sedimentation tank 121 (i.e., the water quality of the water to be treated). Examples of the water quality of the water to be treated (hereinafter sometimes referred to as the water quality to be treated) include the concentrations of phosphoric acid phosphorus (PO4-P), ammonia nitrogen (NH4-N), and nitrate nitrogen (NO3-N) contained in the water to be treated, the chemical oxygen demand (COD) and the biochemical oxygen demand (BOD) of the water to be treated, etc. Examples of the COD of the water to be treated include the chemical oxygen demand by potassium dichromate (COD cr) and the like. Further, as the observed values of the wastewater treatment facility 120, for example, the concentrations of activated sludge suspended solids (MLSS), PO4-P, NH4-N, and NO3-N contained in the liquid in the aerobic tank 125, the concentrations of MLSS, PO4-P, NH4-N, and NO3-N contained in the liquid in the anaerobic tank 123, the water quality of the treated water (hereinafter sometimes referred to as the treated water quality), the total amount of total nitrogen (T-N) contained in the returned sludge, and the concentration of MLSS are mentioned. As the treated water quality, for example, the COD (COD cr etc.) and BOD of the treated water, the concentrations of PO4-P, NH4-N, and NO3-N contained in the treated water, the T-N in the treated water, and the concentration of suspended solids (SS) floating in the treated water are mentioned.

[0040] For example, in the wastewater treatment system 100, a plurality of measuring devices (not shown) for measuring various process data along the time series are provided. The data collection unit 10 is composed of a memory or the like, and collects the process data actually measured during the operation of the wastewater treatment system 100 from each of the sludge dewatering facility 110 and the wastewater treatment facility 120 each time the measurement is performed. For example, when the process data of the wastewater treatment system 100 is measured discretely at predetermined time intervals, the data collection unit 10 sequentially collects the process data such as a plurality of observed values that are discrete in time along the time series. Further, when the process data of the wastewater treatment system 100 is measured continuously along the time series, the data collection unit 10 sequentially collects a plurality of process data that are continuous in time along the time series. In the present embodiment, "continuous in time" means continuous every predetermined unit time (for example, 1 hour). That is, the unit time is shorter than the measurement time interval when the process data is measured discretely along the time series, and the time interval between the observed values that are continuous in time is shorter than the time interval between the observed values that are discrete in time. The data collection unit 10 sequentially accumulates the collected process data in association with the timing (year, month, day, date and time, etc.) when the process data was measured.

[0041] The arithmetic processing unit 20 executes various arithmetic processes related to deriving the optimal operating conditions of the wastewater treatment system 100. For example, as shown in FIG. 1, the arithmetic processing unit 20 includes a model construction unit 21, a sludge dewatering facility model 22, a wastewater treatment facility model 25, a model calculation unit 28, and an operating condition search unit 29.

[0042] The model construction unit 21 constructs a mathematical model used to derive the optimal operating conditions of the wastewater treatment system 100. For example, the model construction unit 21 adjusts the parameters of each of the initial models of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 based on the initial models of the sludge dewatering facility 110 and the wastewater treatment facility 120 and the process data collected by the data collection unit 10, so as to reduce (make close to zero) the error between the observed values of the operating states of the sludge dewatering facility 110 and the wastewater treatment facility 120 and the predicted values derived from the respective initial models, and constructs the sludge dewatering facility model 22 and the wastewater treatment facility model 25.

[0043] Specifically, in the present embodiment, the arithmetic processing unit 20 is preset with an initial model of the sludge dewatering facility model 22 that simulates the operation of the sludge dewatering facility 110 and an initial model of the wastewater treatment facility model 25 that simulates the operation of the wastewater treatment facility 120 corresponding to the wastewater treatment system 100 shown in FIG. 1. The initial model of the sludge dewatering facility model 22 is a mathematical model with the predicted value of the operating state of the sludge dewatering facility 110 as the target variable and the operating conditions of the sludge dewatering facility 110 as the explanatory variables. The initial model of the wastewater treatment facility model 25 is a mathematical model with the predicted value of the operating state of the wastewater treatment facility 120 as the target variable and the operating conditions of the wastewater treatment facility 120 as the explanatory variables. The relational expressions and coefficients between the target variables and the explanatory variables representing these initial models are initially set based on, for example, the past process data (past performance data) of the wastewater treatment system 100 collected (accumulated) by the data collection unit 10.

[0044] The model construction unit 21 derives a predicted value of the operating state of the sludge dewatering facility 110 based on the operating conditions of the sludge dewatering facility 110 among the process data collected by the data collection unit 10 and the initial model of the sludge dewatering facility model 22. The model construction unit 21 adjusts the parameters of the initial model of the sludge dewatering facility model 22 so as to reduce the error between the derived predicted value and the observed value of the sludge dewatering facility 110 among the process data collected by the data collection unit 10. Thereby, the model construction unit 21 constructs the sludge dewatering facility model 22 suitable for the current operation of the sludge dewatering facility 110 from the initial model. Specifically, as shown in FIG. 1, the model construction unit 21 constructs, as the sludge dewatering facility model 22, a sludge dewatering water quality model 23 that calculates the water quality to be treated from the operating conditions of the sludge dewatering facility 110 and the properties of the influent sludge, and a sludge dewatering power model 24 that calculates the power consumption during the operation of the sludge dewatering facility 110 from the operating conditions of the sludge dewatering facility 110.

[0045] Further, the model construction unit 21 derives a predicted value of the operating state of the wastewater treatment facility 120 based on the operating conditions of the wastewater treatment facility 120 among the process data collected by the data collection unit 10 and the initial model of the wastewater treatment facility model 25. The model construction unit 21 adjusts the parameters of the initial model of the wastewater treatment facility model 25 so as to reduce the error between the derived predicted value and the observed value of the wastewater treatment facility 120 among the process data collected by the data collection unit 10. Thereby, the model construction unit 21 constructs the wastewater treatment facility model 25 suitable for the current operation of the wastewater treatment facility 120 from the initial model. Specifically, as shown in FIG. 1, the model construction unit 21 constructs, as the wastewater treatment facility model 25, a wastewater treatment water quality model 26 that calculates the treated water quality from the operating conditions of the wastewater treatment facility 120 and the water quality to be treated, and a wastewater treatment power model 27 that calculates the power consumption during the operation of the wastewater treatment facility 120 from the operating conditions of the wastewater treatment facility 120.

[0046] The sludge dewatering equipment model 22 is an example of a related equipment model that simulates the operation of related equipment for water treatment other than biological treatment in relation to the wastewater treatment equipment 120, and simulates the operation of the sludge dewatering equipment 110 described above. The related equipment model in the present invention includes at least a power model that calculates the power consumption during the operation of the related equipment from the operating conditions of the related equipment as the operating state of the related equipment. For example, as shown in FIG. 1, the sludge dewatering equipment model 22 includes a sludge dewatering water quality model 23 and a sludge dewatering power model 24.

[0047] The sludge dewatering water quality model 23 is a water quality model represented by a relational expression with the water quality to be treated from the sludge dewatering equipment 110 as the target variable and the operating conditions of the sludge dewatering equipment 110 and the properties of the influent sludge as the explanatory variables. The sludge dewatering water quality model 23 calculates a predicted value of the water quality to be treated in response to the input of each value of the operating conditions of the sludge dewatering equipment 110 and the properties of the influent sludge. This water quality to be treated is the water quality of the drainage extracted from the influent sludge having such properties by the sludge dewatering equipment 110 operating according to the operating conditions, that is, the water quality of the influent water flowing from the sludge dewatering equipment 110 to the wastewater treatment equipment 120.

[0048] The sludge dewatering power model 24 is a power model represented by a relational expression with the power consumption during the operation of the sludge dewatering equipment 110 as the target variable and the operating conditions of the sludge dewatering equipment 110 as the explanatory variables. The sludge dewatering power model 24 calculates a predicted value of the power consumption in response to the input of the operating conditions of the sludge dewatering equipment 110. This power consumption is the power consumption required for the sludge dewatering equipment 110 when the sludge dewatering equipment 110 operates according to the operating conditions.

[0049] The wastewater treatment equipment model 25 is an example of a mathematical model that simulates the operation of the wastewater treatment equipment 120. For example, as shown in FIG. 1, the wastewater treatment equipment model 25 includes a wastewater treatment water quality model 26 and a wastewater treatment power model 27.

[0050] The wastewater treatment water quality model 26 is a water quality model that takes the treated water quality from biological treatment etc. of the wastewater treatment facility 120 as the target variable and the operating conditions of the wastewater treatment facility 120 and the water quality of the water to be treated as the explanatory variables, and is represented by the relational expression between these target variables and explanatory variables. Specifically, the wastewater treatment water quality model 26 represents the biological treatment process of the water to be treated by the wastewater treatment facility 120 with a plurality of mathematical formulas. Such a wastewater treatment water quality model 26 includes models constructed based on physicochemical insights such as the activated sludge model proposed by the IWA, and simulates the biological treatment process of the water to be treated carried out in the wastewater treatment facility 120.

[0051] For example, the wastewater treatment water quality model 26 includes a model formula regarding the flow rate or contained components of the water to be treated flowing (supplied) from the primary sedimentation tank 121 into the reaction tank 122, a model formula regarding the internal state of the anaerobic tank 123 (behavior of biological reactions by anaerobic microorganisms etc.), a model formula regarding the internal state of the anoxic tank 124 (behavior of biological reactions by denitrifying bacteria etc.), a model formula regarding the internal state of the aerobic tank 125 (behavior of biological reactions by aerobic microorganisms etc.), and a model formula regarding the substances flowing out from the reaction tank 122 or the final sedimentation tank 126 (treated water, returned sludge, etc.). Such a wastewater treatment water quality model 26 calculates a predicted value of the same item as the observed value of the wastewater treatment facility 120 operating according to the operating conditions, for example, a predicted value of the treated water quality, in response to the input of the operating conditions of the wastewater treatment facility 120 and the water quality of the influent water. In the present embodiment, the water quality of the influent water input into the wastewater treatment water quality model 26 is the predicted value of the water quality of the water to be treated calculated by the sludge dewatering water quality model 23 described above. The predicted value of the treated water quality by the wastewater treatment water quality model 26 is the predicted value of the water quality of the treated water obtained by purifying the influent water (water to be treated) of the above water quality by the wastewater treatment facility 120 operating according to the operating conditions.

[0052] The drainage treatment power model 27 is a power model represented by a relational expression with the power consumption of the drainage treatment facility 120 during operation as the target variable and the operating conditions of the drainage treatment facility 120 as the explanatory variables. The drainage treatment power model 27 calculates a predicted value of the power consumption in response to the input of the operating conditions of the drainage treatment facility 120. This power consumption is the power consumption required by the drainage treatment facility 120 when the drainage treatment facility 120 operates according to the operating conditions.

[0053] From the perspective of easily performing parameter adjustment of each of the above-described water quality models and power models, each of the sludge dewatering water quality model 23 and the sludge dewatering power model 24 is preferably a state space model composed of a state variable representing the internal state of the sludge dewatering facility 110 and an observation variable observable during the operation of the sludge dewatering facility 110. Similarly, each of the drainage treatment water quality model 26 and the drainage treatment power model 27 is preferably a state space model composed of a state variable representing the internal state of the drainage treatment facility 120 and an observation variable observable during the operation of the drainage treatment facility 120.

[0054] The model calculation unit 28 calculates a predicted value of the operating state of the drainage treatment system 100 by model calculation processing using a drainage treatment facility model 25 that simulates the operation of the drainage treatment facility 120 in the drainage treatment system 100 and a related facility model that simulates the operation of related facilities related to the drainage treatment facility 120. That is, the model calculation unit 28 calculates a predicted value of the operating state of the related facility based on the related facility model and at least the operating conditions of the related facility. In addition, the model calculation unit 28 calculates a predicted value of the operating state of the drainage treatment facility 120 including a predicted value of the water quality of the treated water based on the drainage treatment facility model 25, the operating conditions of the drainage treatment facility 120, and the water quality of the water to be treated (the water quality of the influent water shown in FIG. 1).

[0055] In the present embodiment, as the above-described related equipment model, for example, as shown in FIG. 1, a sludge dewatering water quality model 23 and a sludge dewatering power model 24 are used. Specifically, the model calculation unit 28 calculates a predicted value of the operating state of the sludge dewatering facility 110 based on the sludge dewatering water quality model 23, the operating conditions of the sludge dewatering facility 110, and the properties of the influent sludge. Examples of the predicted value of the operating state of the sludge dewatering facility 110 calculated by the model calculation unit 28 include predicted values of the same items as those of the observed values of the sludge dewatering facility 110 collected by the data collection unit 10 described above, excluding the power consumption amount, such as the predicted value of the water quality to be treated. Further, the model calculation unit 28 calculates the power consumption amount during the operation of the sludge dewatering facility 110 as a predicted value of the operating state of the sludge dewatering facility 110 based on the sludge dewatering power model 24 and the operating conditions of the sludge dewatering facility 110. In this model calculation process, the operating conditions of the sludge dewatering facility 110 input to the sludge dewatering power model 24 are the same as the operating conditions of the sludge dewatering facility 110 input to the above-described sludge dewatering water quality model 23. The power consumption amount calculated from the sludge dewatering power model 24 by the model calculation unit 28 is a predicted value of the power consumption amount that the sludge dewatering facility 110 consumes when the sludge dewatering facility 110 operates according to the input operating conditions.

[0056] Further, as the above-described wastewater treatment facility model 25, for example, as shown in FIG. 1, the model calculation unit 28 uses a wastewater treatment water quality model 26 and a wastewater treatment power model 27. Specifically, the model calculation unit 28 calculates a predicted value of the operating state of the wastewater treatment facility 120 based on the wastewater treatment water quality model 26, the operating conditions of the wastewater treatment facility 120, and the water quality of the treatment target. Examples of the predicted value of the operating state of the wastewater treatment facility 120 calculated by the model calculation unit 28 include predicted values of the same items as those of the observed values of the wastewater treatment facility 120 collected by the above-described data collection unit 10, excluding the power consumption amount, such as the predicted value of the treated water quality. In this model calculation process, the water quality of the treatment target input to the wastewater treatment water quality model 26 is, for example, the predicted value of the water quality of the treatment target output from the above-described sludge dewatering water quality model 23. Further, the model calculation unit 28 calculates the power consumption amount during the operation of the wastewater treatment facility 120 as a predicted value of the operating state of the wastewater treatment facility 120 based on the wastewater treatment power model 27 and the operating conditions of the wastewater treatment facility 120. The operating conditions of the wastewater treatment facility 120 input to the wastewater treatment power model 27 are the same as the operating conditions of the wastewater treatment facility 120 input to the above-described wastewater treatment water quality model 26. The power consumption amount calculated from the wastewater treatment power model 27 by the model calculation unit 28 is a predicted value of the power consumption amount that the wastewater treatment facility 120 consumes when the wastewater treatment facility 120 operates according to the input operating conditions.

[0057] The operation condition exploration unit 29 explores the optimal operation conditions of the wastewater treatment system 100 under the constraint conditions related to the operation of the wastewater treatment system 100. Specifically, the operation condition exploration unit 29 calculates the objective function value based on the predicted values of the operation states of the wastewater treatment system 100 calculated by the model calculation unit 28. In the present embodiment, the predicted values of the operation states of the wastewater treatment system 100 are the predicted values of the operation states of the sludge dewatering facility 110 and the wastewater treatment facility 120. The operation condition exploration unit 29 calculates, among the predicted values of the operation states of the sludge dewatering facility 110 and the wastewater treatment facility 120, for example, the power consumption during the operation of the sludge dewatering facility 110 output from the sludge dewatering power model 24 and the power consumption during the operation of the wastewater treatment facility 120 output from the wastewater treatment power model 27, and calculates the objective function value related to the power consumption during the operation of the entire wastewater treatment system 100.

[0058] In addition, the operation condition exploration unit 29 compares the predicted value of the treated water quality output from the treated water quality model 26 with the constraint conditions preset for the water quality of the treated water by the wastewater treatment facility 120 among the predicted values of the operation states of the sludge dewatering facility 110 and the wastewater treatment facility 120. The operation condition exploration unit 29 searches for the operation conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120 when the calculated objective function value is minimized within the range where the predicted value of the treated water quality satisfies the constraint conditions as the optimal operation conditions of the wastewater treatment system 100.

[0059] In this search process for the optimal operation conditions, the operation condition exploration unit 29 determines whether the predicted value of the treated water quality satisfies the constraint conditions through the above comparison process. When the predicted value of the treated water quality does not satisfy the constraint conditions, the operation condition exploration unit 29 changes at least one of the operation conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120 input to each of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 and the water quality of the water to be treated in a direction that improves the predicted value of the treated water quality to satisfy the constraint conditions. On the other hand, when the predicted value of the treated water quality satisfies the constraint conditions, the operation condition exploration unit 29 changes the at least one value in a direction that reduces the objective function value.

[0060] The above-described model calculation unit 28 repeatedly executes the above-described model calculation process using the operating conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120 including the values after the change by the operating condition search unit 29 and the water quality of the treatment target until the optimal operating conditions of the wastewater treatment system 100 are searched by the operating condition search unit 29. Thereby, the model calculation unit 28 repeatedly calculates the predicted value of the operating state of the sludge dewatering facility 110 (for example, the predicted values of the water quality of the treatment target and the power consumption) and the predicted value of the operating state of the wastewater treatment facility 120 (for example, the predicted values of the treated water quality and the power consumption) as the values used in the process of the above-described operating condition search unit 29.

[0061] The process control unit 30 controls each operation of the above-described data collection unit 10 and arithmetic processing unit 20. For example, each time the process data of the wastewater treatment system 100 is measured, the process control unit 30 controls the data collection unit 10 to sequentially collect and accumulate the measured process data along the time series. Further, the process control unit 30 controls the input / output of data and its timing between the above-described data collection unit 10 and the model construction unit 21, and controls the derivation timing of the predicted value and the adjustment timing of the parameters by the model construction unit 21.

[0062] The input unit 40 inputs data necessary for calculating the predicted value of the operating state of the wastewater treatment system 100 by the model calculation process. Specifically, the input unit 40 is composed of an input device or the like, and inputs data to the model calculation unit 28 in response to an input operation by an operator. The data input to the model calculation unit 28 by the input unit 40 is the initial value of the data input to each of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 from the model calculation unit 28.

[0063] For example, as the initial values of the data input into the sludge dewatering equipment model 22, there are the initial values of the operating conditions and operating states of the sludge dewatering equipment 110. As the initial values of the operating conditions of the sludge dewatering equipment 110, there are, for example, the initial values of the same items as the operating conditions of the sludge dewatering equipment 110 collected by the above-described data collection unit 10, such as the flow rate of the influent sludge. As the initial values of the operating states of the sludge dewatering equipment 110, there are, for example, the initial values of the same items as the observed values of the sludge dewatering equipment 110 collected by the above-described data collection unit 10, such as the properties of the influent sludge. Further, as the initial values of the data input into the wastewater treatment equipment model 25, there are, for example, the initial values of the operating conditions of the wastewater treatment equipment 120. As the initial values of the operating conditions of the wastewater treatment equipment 120, there are, for example, the initial values of the same items as the operating conditions of the wastewater treatment equipment 120 collected by the above-described data collection unit 10, such as the flow rate of the water to be treated.

[0064] The condition setting unit 50 sets constraint conditions and the like when the operation condition search unit 29 described above searches for the optimal operation conditions of the wastewater treatment system 100. Specifically, the condition setting unit 50 is composed of an input device or the like, and sets the above-mentioned constraint conditions according to the input operation of the operator. For example, the condition setting unit 50 receives the input of the treated water quality information that specifies the water quality of the treated water by the wastewater treatment facility 120, and variably sets the above-mentioned constraint conditions according to the received treated water quality information. Examples of the treated water quality information include items and numerical ranges of the treated water quality to be set as constraint conditions. Examples of the items of the treated water quality include the same items as the observed values of the treated water quality observable in the above-mentioned wastewater treatment facility 120. In addition, the condition setting unit 50 has a memory or the like in which a plurality of candidate items of the treated water quality to be set as constraint conditions are registered, and based on the treated water quality information received according to the input operation of the operator, selects the item of the treated water quality from among these plurality of candidate items, and may set the selected item of the treated water quality as the item of the constraint condition. The numerical range of the treated water quality as a constraint condition can be determined, for example, based on laws and regulations that define the treated water quality of wastewater treatment. The condition setting unit 50 sets a numerical range such as the upper limit value of the treated water quality according to the above-mentioned treated water quality information. The condition setting unit 50 transmits the constraint conditions set as described above to the operation condition search unit 29.

[0065] In addition, the condition setting unit 50 sets the item of the objective function value when the operation condition search unit 29 described above searches for the optimal operation conditions of the wastewater treatment system 100. For example, the condition setting unit 50 receives the input of the target information indicating the target to be minimized in the operation of the wastewater treatment system 100 according to the input operation of the operator, and variably sets the item of the objective function value based on the received target information. Examples of the target information (item of the objective function value) include the power consumption during the operation of the wastewater treatment system 100. For example, the power consumption during the operation of the wastewater treatment system 100 in the present embodiment is the total value of the power consumption during the operation of the sludge dewatering facility 110 and the power consumption during the operation of the wastewater treatment facility 120. The condition setting unit 50 transmits the item of the objective function value set in this way to the operation condition search unit 29 in association with the above-mentioned constraint conditions.

[0066] The visualization unit 60 visualizes the optimal operating conditions of the wastewater treatment system 100. Specifically, the visualization unit 60 is constituted by a display device, a printer, or the like, and displays or prints the optimal operating conditions of the wastewater treatment system 100 searched by the above-described operating condition search unit 29. Thereby, the visualization unit 60 visualizes the optimal operating conditions of the wastewater treatment system 100 so that an operator can visually recognize them. Note that the visualization unit 60 may be constituted by a combination of a display device and a printer, and may display and print the above optimal operating conditions.

[0067] The operation control unit 70 controls the operation of the wastewater treatment system 100 based on the optimal operating conditions of the wastewater treatment system 100 searched by the operation condition search unit 29. Specifically, the operation control unit 70 acquires the optimal operating conditions of the wastewater treatment system 100 searched by the operation condition search unit 29, and controls the operations of the wastewater treatment facility 120 and the related facilities (the sludge dewatering facility 110 in this embodiment) of the wastewater treatment system 100 based on the acquired optimal operating conditions.

[0068] (Operating Condition Derivation Method) Next, an operating condition derivation method for deriving the optimal operating conditions of the wastewater treatment system 100 according to the embodiment of the present invention will be described. FIG. 2 is a flowchart showing an example of the operating condition derivation method according to the embodiment of the present invention. In this operating condition derivation method, the above-described operating condition derivation device 1 (see FIG. 1) sequentially executes each processing procedure of steps S101 to S106 shown in FIG. 2, thereby deriving the optimal operating state of the wastewater treatment system 100.

[0069] Specifically, as shown in FIG. 2, the operation condition derivation device 1 first collects process data of the wastewater treatment system 100 that is the target of optimization of operation conditions (step S101). In the data collection process of step S101, the data collection unit 10 sequentially collects, from the wastewater treatment system 100 over time, as the process data, the operation conditions of the wastewater treatment system 100 and the observed values of the wastewater treatment system 100 operated according to the operation conditions. For example, in the present embodiment, the data collection unit 10 sequentially collects, over time, the operation conditions of each of the sludge dewatering facility 110 and the wastewater treatment facility 120 as the operation conditions of the wastewater treatment system 100. Further, the data collection unit 10 sequentially collects, over time, as the observed values of the wastewater treatment system 100, the observed values of the sludge dewatering facility 110 operated according to the operation conditions of the sludge dewatering facility 110 and the observed values of the wastewater treatment facility 120 operated according to the operation conditions of the wastewater treatment facility 120. The data collection unit 10 sequentially accumulates the collected process data in association with the measured timing.

[0070] After executing the data collection process of step S101 described above, the operation condition derivation device 1 constructs a mathematical model used for deriving the optimal operation conditions of the wastewater treatment system 100 (step S102). In the model construction process of step S102, the model construction unit 21 constructs, for example, a sludge dewatering facility model 22 and a wastewater treatment facility model 25 as the mathematical model.

[0071] Specifically, the model construction unit 21 acquires, from the process data collected in step S101, the operating conditions of the sludge dewatering facility 110 and the observed values of the sludge dewatering facility 110 operating according to the operating conditions, from the data collection unit 10 along the time series. The model construction unit 21 inputs the acquired operating conditions and the properties of the influent sludge in the sludge dewatering facility 110 among the acquired observed values into the initial model of the sludge dewatering water quality model 23 in the sludge dewatering facility model 22. Thereby, the model construction unit 21 derives a predicted value of the water quality to be treated as a predicted value of the operating state of the sludge dewatering facility 110 from the initial model. The model construction unit 21 selects the observed value of the water quality to be treated at the same time as the predicted value from among the observed values of the sludge dewatering facility 110 by the data collection unit 10, and adjusts the parameters (model coefficients) of the initial model so as to correct (reduce) the error between these predicted values and observed values. In this way, the model construction unit 21 constructs the sludge dewatering water quality model 23 suitable for the current operation of the sludge dewatering facility 110.

[0072] Also, the model construction unit 21 inputs the operating conditions of the sludge dewatering facility 110 acquired from the data collection unit 10 (the same as the operating conditions input into the initial model of the sludge dewatering water quality model 23) into the initial model of the sludge dewatering power model 24 in the sludge dewatering facility model 22. Thereby, the model construction unit 21 derives a predicted value of the power consumption of the sludge dewatering facility 110 when operating according to the input operating conditions as a predicted value of the operating state of the sludge dewatering facility 110 from the initial model. The model construction unit 21 selects the observed value of the power consumption of the sludge dewatering facility 110 at the same time as the predicted value from among the observed values of the sludge dewatering facility 110 by the data collection unit 10, and adjusts the parameters (model coefficients) of the initial model so as to correct (reduce) the error between these predicted values and observed values. In this way, the model construction unit 21 constructs the sludge dewatering power model 24 suitable for the current operation of the sludge dewatering facility 110.

[0073] Also, in the model construction process of step S102, the model construction unit 21 acquires, from the data collection unit 10 along the time series, among the process data collected in step S101, the operating conditions of the wastewater treatment facility 120 and the observed values of the wastewater treatment facility 120 operating according to the operating conditions. It is preferable that the operating conditions of the wastewater treatment facility 120 are those at the same time or in the vicinity of the same time as the operating conditions of the sludge dewatering facility 110 described above. Next, the model construction unit 21 inputs the operating conditions of the sludge dewatering facility 110 and the properties of the influent sludge into the sludge dewatering water quality model 23 constructed as described above, thereby deriving the predicted value of the water quality to be treated by the sludge dewatering facility 110 operating according to the operating conditions. The model construction unit 21 inputs the acquired operating conditions of the wastewater treatment facility 120 and the predicted value of the water quality to be treated derived above into the initial model of the wastewater treatment water quality model 26 among the wastewater treatment facility models 25. Thereby, the model construction unit 21 derives the predicted value of the treated water quality from the initial model as the predicted value of the operating state of the wastewater treatment facility 120. The model construction unit 21 selects the observed value of the treated water quality at the same time as the predicted value from among the observed values of the wastewater treatment facility 120 by the data collection unit 10, and adjusts the parameters (model coefficients) of the initial model so as to correct (reduce) the error between the predicted value and the observed value. In this way, the model construction unit 21 constructs the wastewater treatment water quality model 26 suitable for the current operation of the wastewater treatment facility 120.

[0074] Further, the model construction unit 21 inputs the operating conditions of the wastewater treatment facility 120 (the same as the operating conditions input to the initial model of the wastewater treatment water quality model 26) acquired from the data collection unit 10 into the initial model of the wastewater treatment power model 27 among the wastewater treatment facility models 25. Thereby, the model construction unit 21 derives, from the initial model, a predicted value of the power consumption of the wastewater treatment facility 120 when operating according to the input operating conditions, as a predicted value of the operating state of the wastewater treatment facility 120. The model construction unit 21 selects an observed value of the power consumption of the wastewater treatment facility 120 at the same time as the predicted value from among the observed values of the wastewater treatment facility 120 by the data collection unit 10, and adjusts the parameters (model coefficients) of the initial model so as to correct (reduce) the error between these predicted values and observed values. In this way, the model construction unit 21 constructs the wastewater treatment power model 27 suitable for the current operation of the wastewater treatment facility 120.

[0075] After executing the model construction process of step S102 described above, the operating condition derivation device 1 sets constraint conditions and the like when searching for the optimal operating conditions of the wastewater treatment system 100 (step S103). In the condition setting process of step S103, the condition setting unit 50 receives the input of the treated water quality information in response to the input operation of the operator, and variably sets the above constraint conditions based on the received treated water quality information.

[0076] For example, the condition setting unit 50 acquires information specifying the items and numerical ranges of the treated water quality by the wastewater treatment facility 120 as the above treated water quality information. The items of the treated water quality are the same as at least one item of the treated water quality from which predicted values are derived from the above-described wastewater treatment water quality model 26. Specifically, they are the concentrations of PO4-P, NH4-N, NO3-N, and SS in the treated water, and the COD, BOD, and T-N of the treated water, etc. The numerical range of the treated water quality is a numerical range such as the upper limit value set for each item of the treated water quality. The condition setting unit 50 sets, as the above constraint condition, the numerical range for each item of the treated water quality (for example, the upper limit value of the concentration or content of pollutants such as NH4-N contained in the treated water) to be satisfied when searching for the optimal operating conditions of the wastewater treatment system 100 based on the acquired treated water quality information.

[0077] Also, in the condition setting process of step S103, the condition setting unit 50 sets items of the objective function value when searching for the optimal operating conditions of the wastewater treatment system 100. Specifically, the condition setting unit 50 receives target information indicating a target to be minimized in the operation of the wastewater treatment system 100 in response to an input operation by an operator, and variably sets the items of the objective function value based on the received target information. For example, the condition setting unit 50 sets the power consumption amount during the operation of the wastewater treatment system 100 as an item of the objective function value. In the present embodiment, the power consumption amount during the operation of the wastewater treatment system 100 is the total value of the power consumption amount during the operation of the sludge dewatering facility 110 and the power consumption amount during the operation of the wastewater treatment facility 120. The condition setting unit 50 transmits the constraint conditions and the items of the objective function value set as described above to the operation condition search unit 29 in association with each other.

[0078] After executing the condition setting process of step S103 described above, the operation condition derivation device 1 derives the optimal operation conditions of the wastewater treatment system 100 (step S104). In the operation condition derivation process of step S104, the arithmetic processing unit 20 derives the optimal operation conditions of the wastewater treatment system 100 that can minimize the objective function value under the constraint conditions set by the condition setting process of step S103. The details of the operation condition derivation process of step S104 will be described later.

[0079] After executing the operation condition derivation process of step S104 described above, the operation condition derivation device 1 visualizes the optimal operation conditions of the wastewater treatment system 100 (step S105). In the visualization process of step S105, the visualization unit 60 acquires the optimal operation conditions of the wastewater treatment system 100 derived by the operation condition derivation process of step S104 from the arithmetic processing unit 20 (specifically, the operation condition search unit 29). The visualization unit 60 visualizes the acquired optimal operation conditions so that an operator can visually recognize them by display, printing, or a combination thereof. For example, the visualization unit 60 visualizes the optimal operation conditions of the sludge dewatering facility 110 and the optimal operation conditions of the wastewater treatment facility 120 as the optimal operation conditions of the wastewater treatment system 100. The operator can easily visually recognize the current optimal operation conditions of the wastewater treatment system 100 (in this embodiment, the current optimal operation conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120) based on the information visualized by the visualization unit 60.

[0080] After executing the visualization process of step S105 described above, the operation condition derivation device 1 controls the operation of the wastewater treatment system 100 (step S106) and ends this process. In the operation control process of step S106, the operation control unit 70 acquires the optimal operation conditions of the wastewater treatment system 100 derived by the arithmetic processing unit 20. In this embodiment, the operation control unit 70 acquires the optimal operation conditions visualized by the visualization process of step S105 from the visualization unit 60. Note that the operation control unit 70 may acquire the optimal operation conditions from the operation condition search unit 29 of the arithmetic processing unit 20. The operation control unit 70 controls the operation of the wastewater treatment system 100 based on the optimal operation conditions acquired as described above.

[0081] For example, the optimal operating conditions of the wastewater treatment system 100 include the optimal operating conditions of the sludge dewatering facility 110 and the optimal operating conditions of the wastewater treatment facility 120. In this case, the operation control unit 70 controls the operation of the sludge dewatering facility 110 based on the optimal operating conditions of the sludge dewatering facility 110, and controls the operation of the wastewater treatment facility 120 based on the optimal operating conditions of the wastewater treatment facility 120. Thereby, each of the sludge dewatering facility 110 and the wastewater treatment facility 120 can operate such that the objective function value (for example, the power consumption during operation of the entire wastewater treatment system 100) is minimized within the range where the treated water quality by the wastewater treatment facility 120 satisfies the constraint conditions by the condition setting process of step S103.

[0082] Thereafter, the operation condition derivation device 1 repeatedly executes each of the above-described processes of steps S101 to S106 as necessary. For example, the operation condition derivation device 1 repeats each of the above-described processes of steps S101 to S106 each time information for deriving the optimal operation conditions of the wastewater treatment system 100 is input from the input unit 40 to the arithmetic processing unit 20, or when at least one of the constraint conditions and the objective function value items is changed (newly set) by the condition setting unit 50.

[0083] (Operation Condition Derivation Process) Next, the operation condition derivation process of step S104 described above will be described in detail. FIG. 3 is a flowchart showing an example of the operation condition derivation process in the embodiment of the present invention. After executing the condition setting process (see FIG. 2) of step S103 as described above, the operation condition derivation device 1 executes the operation condition derivation process of step S104. In this operation condition derivation process, the operation condition derivation device 1 sequentially executes each of the process steps of steps S201 to S208 shown in FIG. 3.

[0084] Specifically, in the operation condition derivation process, as shown in FIG. 3, the operation condition derivation device 1 first sets initial values of data necessary for deriving the optimal operation conditions of the wastewater treatment system 100 (step S201). In the initial value setting process of step S201, the input unit 40 inputs the initial values of the model input data to the model calculation unit 28 according to the input operation of the operator. The model input data is data input to a mathematical model for calculating predicted values of the operation state of the wastewater treatment system 100.

[0085] In the present embodiment, as shown in FIG. 1 for example, the mathematical model is a sludge dewatering facility model 22 and a wastewater treatment facility model 25. The sludge dewatering facility model 22 has a sludge dewatering water quality model 23 and a sludge dewatering power model 24. The wastewater treatment facility model 25 has a wastewater treatment water quality model 26 and a wastewater treatment power model 27.

[0086] The input unit 40 inputs the initial values of the operation conditions and the operation state of the sludge dewatering facility 110 to the model calculation unit 28 as the initial values of the model input data of the sludge dewatering facility model 22. For example, the initial values of the operation conditions of the sludge dewatering facility 110 are the initial values of the same items as the operation conditions of the sludge dewatering facility 110 collected by the data collection unit 10 described above. The initial values of the operation state of the sludge dewatering facility 110 are the initial values of the same items as the observed values of the sludge dewatering facility 110 collected by the data collection unit 10 described above. In the present embodiment, the properties of the influent sludge are exemplified as the initial values of the operation state of the sludge dewatering facility 110. Further, the input unit 40 inputs the initial values of the operation conditions of the wastewater treatment facility 120 to the model calculation unit 28 as the initial values of the model input data of the wastewater treatment facility model 25. For example, the initial values of the operation conditions of the wastewater treatment facility 120 are the initial values of the same items as the operation conditions of the wastewater treatment facility 120 collected by the data collection unit 10 described above.

[0087] The model calculation unit 28 acquires the initial value of the model input data from the input unit 40, and sets the acquired initial value of the model input data as the initial value of the model input data to be used in the model calculation process described later. For example, the model calculation unit 28 sets each initial value of the operating conditions and the operating state (in this embodiment, the properties of the influent sludge) of the sludge dewatering facility 110 input from the input unit 40 as the initial value of the model input data of the sludge dewatering water quality model 23, and sets the initial value of the operating conditions of the sludge dewatering facility 110 as the initial value of the model input data of the sludge dewatering power model 24. In addition, the model calculation unit 28 sets the initial value of the operating conditions of the wastewater treatment facility 120 input from the input unit 40 as the initial value of the model input data of each of the wastewater treatment water quality model 26 and the wastewater treatment power model 27. In this embodiment, the initial value of the water quality to be treated derived from the sludge dewatering water quality model 23 is used as the initial value of the operating state of the wastewater treatment facility 120 input to the wastewater treatment water quality model 26 together with the initial value of the operating conditions of the wastewater treatment facility 120. The initial value of the water quality to be treated is derived from the sludge dewatering water quality model 23 by inputting the initial value of the model input data of the sludge dewatering water quality model 23 into the sludge dewatering water quality model 23.

[0088] Note that the initial value of the water quality to be treated may be input to the model calculation unit 28 by the input unit 40. In this case, the model calculation unit 28 may set the input initial value of the water quality to be treated as the initial value of the model input data of the wastewater treatment water quality model 26 together with the initial value of the operating conditions of the wastewater treatment facility 120.

[0089] After executing the initial value setting process of step S201 described above, the operation condition derivation device 1 calculates a predicted value of the operation state of the wastewater treatment system 100 using a mathematical model that simulates the operation of the wastewater treatment system 100 (step S202). In the model calculation process of step S202, the model calculation unit 28 calculates a predicted value of the operation state of the related equipment based on at least the operation condition of the related equipment and a related equipment model (in this embodiment, the sludge dewatering equipment model 22) that simulates the operation of the related equipment (the sludge dewatering equipment 110 in this embodiment). Further, the model calculation unit 28 calculates a predicted value of the operation state of the wastewater treatment equipment 120 including a predicted value of the quality of the treated water based on the wastewater treatment equipment model 25 that simulates the operation of the wastewater treatment equipment 120, the operation condition of the wastewater treatment equipment 120, and the quality of the water to be treated.

[0090] Specifically, the model calculation unit 28 inputs, into the sludge dewatering water quality model 23, the initial values of the operation condition of the sludge dewatering equipment 110 and the properties of the influent sludge among the initial values of the plurality of model input data set by the initial value setting process of step S201 described above. Thereby, the model calculation unit 28 calculates, from the sludge dewatering water quality model 23, a predicted value of the quality of the water to be treated as the initial value of the water to be treated. Further, the model calculation unit 28 inputs the initial value of the operation condition of the sludge dewatering equipment 110 that is the same as what is input to the sludge dewatering water quality model 23 into the sludge dewatering power model 24. Thereby, the model calculation unit 28 calculates, from the sludge dewatering power model 24, a predicted value of the power consumption of the sludge dewatering equipment 110 when operating according to the operation condition.

[0091] Next, the model calculation unit 28 inputs the operating conditions of the wastewater treatment facility 120 among the initial values of the plurality of model input data set by the above-described initial value setting process of step S201 and the initial value of the water quality to be treated calculated from the sludge dewatering water quality model 23 into the wastewater treatment water quality model 26. Thereby, the model calculation unit 28 calculates a predicted value of the treated water quality from the wastewater treatment water quality model 26. Further, the model calculation unit 28 inputs the initial value of the operating conditions of the wastewater treatment facility 120 that is the same as what was input into the wastewater treatment water quality model 26 into the wastewater treatment power model 27. Thereby, the model calculation unit 28 calculates a predicted value of the power consumption of the wastewater treatment facility 120 when operating according to the operating conditions from the wastewater treatment power model 27. The model calculation unit 28 transmits the predicted value of the power consumption of the sludge dewatering facility 110 calculated as described above and the predicted values of the treated water quality and power consumption of the wastewater treatment facility 120 to the operating condition search unit 29.

[0092] After executing the model calculation process of step S202 described above, the operating condition derivation device 1 calculates an objective function value related to the operation of the wastewater treatment system 100 (step S203). In the objective function value calculation process of step S203, the operating condition search unit 29 calculates the objective function value based on the predicted values of the operating states of the related facilities described above and the predicted value of the operating state of the wastewater treatment facility 120.

[0093] Specifically, the operating condition search unit 29 acquires each predicted value calculated by the model calculation process of step S202 from the model calculation unit 28. Next, the operating condition search unit 29 calculates the objective function value of the items set by the condition setting process of step S103 described above based on each acquired predicted value. For example, the item of the objective function value is the power consumption during the operation of the wastewater treatment system 100. In this case, the operating condition search unit 29 calculates the objective function value, which is the total value of these power consumptions, by adding up the predicted value of the power consumption of the sludge dewatering facility 110 and the predicted value of the power consumption of the wastewater treatment facility 120 calculated by the model calculation unit 28 described above.

[0094] After executing the objective function value calculation process in step S203 described above, the operation condition derivation device 1 determines whether the predicted water quality value of the treated water satisfies the preset constraint conditions regarding the water quality of the treated water by the wastewater treatment facility 120 (step S204).

[0095] In the determination process of step S204, the operation condition search unit 29 acquires the predicted value of the treated water quality calculated from the wastewater treatment water quality model 26 by the model calculation process in step S202 described above from the model calculation unit 28. Further, the above constraint conditions are represented by the numerical ranges for each item of the treated water quality set in the condition setting process in step S103 (see FIG. 2) described above. For example, as the above constraint conditions, an upper limit value of the concentration or content of pollutants such as NH4-N contained in the treated water is set. The operation condition search unit 29 has acquired such constraint conditions from the condition setting unit 50 in advance. The operation condition search unit 29 compares these predicted values of the treated water quality with the constraint conditions, and determines whether the predicted value of the treated water quality satisfies the constraint conditions. For example, when the predicted value of the treated water quality exceeds the upper limit value of the treated water quality as the constraint condition, the operation condition search unit 29 determines that the constraint conditions are not satisfied, and when the predicted value of the treated water quality is equal to or less than the upper limit value of the treated water quality as the constraint condition, the operation condition search unit 29 determines that the constraint conditions are satisfied.

[0096] When the predicted value of the treated water quality does not satisfy the constraint conditions (step S204, No), the operation condition derivation device 1 changes the model input data input to each of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 in a direction to be improved so that the predicted value of the treated water quality satisfies the constraint conditions (step S205). In the first input value change process of step S205, examples of the model input data include the operation conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120, and the water quality of the water to be treated. The operation condition search unit 29 changes at least one value among these model input data in a direction to be improved so that the predicted value of the treated water quality satisfies the constraint conditions.

[0097] For example, the operating condition search unit 29 acquires the model input data of each of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 from the model calculation unit 28. When each of the acquired plurality of model input data is the initial value set in the above-described step S201, the operating condition search unit 29 changes at least one of these initial values in a direction in which the predicted value of the treated water quality by the wastewater treatment water quality model 26 is improved so as to satisfy the constraint conditions. The operating condition search unit 29 transmits each of the plurality of model input data including the value changed in this way (hereinafter referred to as the updated value) to the model calculation unit 28 as the updated value of the model input data. Further, when each of the plurality of model input data acquired from the model calculation unit 28 is an updated value, the operating condition search unit 29 further changes at least one of these updated values in a direction in which the predicted value of the treated water quality by the wastewater treatment water quality model 26 is improved so as to satisfy the constraint conditions. The operating condition search unit 29 transmits each of the plurality of model input data changed in this way to the model calculation unit 28 as the updated value of the model input data.

[0098] After executing the first input value change process of step S205 described above, the operating condition derivation device 1 returns to step S202 and repeatedly executes the processing procedure after this step S202. At this time, in step S202 immediately after step S205, the model calculation unit 28 acquires the updated values of the plurality of model input data by this step S205 from the operating condition search unit 29. The model calculation unit 28 executes the above-described model calculation process using the updated values of the plurality of model input data acquired this time instead of the model input data before the change such as the above-described initial value.

[0099] On the other hand, when the predicted value of the treated water quality satisfies the constraint conditions (step S204, Yes), the operating condition derivation device 1 determines whether or not the above objective function value regarding the operation of the wastewater treatment system 100 is minimized (step S206). In the determination process of step S206, the operating condition search unit 29 determines whether or not the objective function value calculated by the objective function value calculation process of step S203 described above is minimized.

[0100] For example, the operating condition search unit 29 acquires a plurality of objective function values including the current objective function value and the past objective function values calculated in the previous step S203. When no minimum value exists among these plurality of objective function values, the operating condition search unit 29 determines that the objective function value has not been minimized. When a minimum value exists among these plurality of objective function values, the operating condition search unit 29 determines that the objective function value has been minimized. Note that when there is only one acquired objective function value, the operating condition search unit 29 may determine that the objective function value has not been minimized regardless of the value of the objective function value, or may determine that the objective function value has been minimized if the objective function value is smaller than a preset reference value.

[0101] When the objective function value has not been minimized (step S206, No), the operating condition derivation device 1 changes the model input data input to each of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 in a direction in which the objective function value decreases (step S207). In the second input value change process of step S207, as the model input data, similar to step S205 described above, the operating conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120 and the water quality of the water to be treated are included. The operating condition search unit 29 changes at least one value among these model input data in a direction in which the objective function value decreases. Note that the second input value change process is the same as the first input value change process described above, except that the model input data is changed in a direction in which the objective function value decreases. The operating condition search unit 29 transmits each of the changed plurality of model input data to the model calculation unit 28 as an updated value of the model input data.

[0102] After executing the second input value change process of step S207 described above, the operating condition derivation device 1 returns to step S202 and repeatedly executes the processing procedures after this step S202. At this time, in step S202 immediately after step S207, the model calculation unit 28 acquires updated values of a plurality of model input data from the operating condition search unit 29 by this step S207. The model calculation unit 28 executes the above-described model calculation process using the updated values of the plurality of model input data acquired this time instead of the model input data before the change such as the initial value described above.

[0103] On the other hand, when the objective function value is minimized (step S206, Yes), the operating condition derivation device 1 searches for the optimal operating conditions of the wastewater treatment system 100 according to this minimized objective function value (step S208). In the operating condition search process of step S208, the operating condition search unit 29 searches for the operating conditions of the wastewater treatment system 100 when the objective function value is minimized as the optimal operating conditions within the range where the above-described constraint conditions are satisfied by the predicted water quality value of the treated water.

[0104] For example, the operating condition search unit 29 acquires the respective operating conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120 corresponding to the minimized objective function value from the model calculation unit 28. As each of the operating conditions, when calculating the predicted values of the power consumption of the sludge dewatering facility 110 and the wastewater treatment facility 120 used for calculating the minimized objective function value, the operating conditions of the sludge dewatering facility 110 input to the sludge dewatering power model 24 and the operating conditions of the wastewater treatment facility 120 input to the wastewater treatment power model 27 are listed. The operating condition search unit 29 searches for the respective operating conditions of the sludge dewatering facility 110 and the wastewater treatment facility 120 as the optimal operating conditions of the wastewater treatment system 100 where the power consumption during operation is minimized.

[0105] In the operating condition derivation process of step S104 described above, the optimal operating conditions of the wastewater treatment system 100 are derived as described above. After executing the operating condition search process of step S208 described above, the operating condition derivation device 1 returns to step S104 shown in FIG. 2 and sequentially executes the processing procedures of steps S105 and S106.

[0106] (Operation condition derivation program) Next, an operation condition derivation program according to an embodiment of the present invention will be described. This operation condition derivation program is a program that causes a computer to execute the same processing procedure as the above-described operation condition derivation method (see steps S101 to S106 shown in FIG. 2 and steps S201 to S208 shown in FIG. 3). For example, the operation condition derivation device 1 shown in FIG. 1 is configured by a computer including a CPU, a memory, and the like. The operation condition derivation program is stored in the memory of the computer and executed by the CPU.

[0107] As described above, in the embodiment of the present invention, when deriving the optimal operation conditions of the wastewater treatment system 100, by model calculation processing using the sludge dewatering facility model 22 and the wastewater treatment facility model 25, the predicted values of the operating states of the sludge dewatering facility 110 and the wastewater treatment facility 120 in the wastewater treatment system 100 (including the predicted value of the quality of the treated water by the wastewater treatment facility 120) are calculated, and the objective function value is calculated based on these predicted values of the operating states. The operating conditions of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 when the objective function value is minimized within the range where the water quality prediction value of the treated water satisfies the preset constraint conditions for the treated water quality are searched for as the optimal operation conditions of the wastewater treatment system 100.

[0108] Therefore, not only the wastewater treatment facility 120 but also the overall operation of the wastewater treatment system 100 including related facilities (for example, the sludge dewatering facility 110) that perform water treatment other than biological treatment in relation to the wastewater treatment facility 120 is taken into account, and the optimal operation conditions of the wastewater treatment system 100 when the objective function value such as the power consumption required for the operation is minimized can be easily searched. Thereby, the optimal operation conditions of the wastewater treatment system 100 can be easily derived.

[0109] In addition, in the present embodiment, the operating conditions of the wastewater treatment system 100 and the observed values observed from the wastewater treatment system 100 operating according to the operating conditions are collected, and based on the respective initial models of the sludge dewatering facility model 22 and the wastewater treatment facility model 25 set in advance and the collected operating conditions, predicted values of the operating states of the sludge dewatering facility 110 and the wastewater treatment facility 120 are derived, and the parameters of the respective initial models are adjusted so as to reduce the error between the predicted values of the respective operating states derived and the collected observed values, thereby constructing the sludge dewatering facility model 22 and the wastewater treatment facility model 25.

[0110] Therefore, it is not necessary to adjust many parameters included in the sludge dewatering facility model 22 and the wastewater treatment facility model 25 through trial and error based on the treatment status such as the water quality and inflow rate of the water to be treated and empirical rules. By adjusting the parameters of the respective initial models, it is possible to easily construct the sludge dewatering facility model 22 and the wastewater treatment facility model 25 that can accurately predict the operating states of the sludge dewatering facility 110 and the wastewater treatment facility 120 with high precision. Furthermore, since the labor required for model construction can be significantly reduced, the time and labor required for model construction can be reduced.

[0111] In addition, in the present embodiment, an input of treatment water quality information for specifying the treated water quality is received, and the above-mentioned constraint conditions are variably set according to the received treatment water quality information. Therefore, the constraint conditions to be satisfied when deriving the optimal operating conditions of the wastewater treatment system 100 can be flexibly changed and set according to the actual operation of the wastewater treatment system 100 and the actual water quality of the treated water to be discharged.

[0112] In addition, in the present embodiment, based on the optimal operating conditions searched as described above, the operation of each facility in the wastewater treatment system 100 is controlled. Therefore, under the constraint conditions to be satisfied regarding the treated water quality, each facility in the wastewater treatment system 100 can be operated so that the objective function value such as the power consumption required for the operation of the entire wastewater treatment system 100 becomes minimum.

[0113] In the above-described embodiment, as related equipment that performs water treatment other than biological treatment in relation to the wastewater treatment facility 120, the sludge dewatering facility 110, which is the pre-stage facility of the wastewater treatment facility 120, is exemplified, and the optimal operating conditions of the wastewater treatment system 100 having these sludge dewatering facility 110 and wastewater treatment facility 120 are derived. However, the present invention is not limited thereto. For example, the related equipment in the wastewater treatment system 100 may be pre-stage equipment such as the sludge dewatering facility 110, or may be post-stage equipment (such as an advanced treatment facility) that removes contaminants remaining in the treated water discharged from the wastewater treatment facility 120 to further improve the water quality of the treated water, or may be both the pre-stage equipment and the post-stage equipment. That is, in the present invention, the wastewater treatment system 100 for which the optimal operating conditions are to be derived may include the pre-stage equipment and the wastewater treatment facility 120, or may include the wastewater treatment facility 120 and the post-stage equipment, or may include the pre-stage equipment, the wastewater treatment facility 120, and the post-stage equipment.

[0114] Further, in the above-described embodiment, as a mathematical model for simulating the operation of the wastewater treatment system 100, the sludge dewatering facility model 22 for simulating the operation of the sludge dewatering facility 110 and the wastewater treatment facility model 25 for simulating the operation of the wastewater treatment facility 120 are exemplified. However, the present invention is not limited thereto. In the present invention, the mathematical model may be any mathematical model that simulates the operation of each facility included in the wastewater treatment system 100. For example, it may be a plurality of mathematical models that simulate the operations of the pre-stage equipment and the wastewater treatment facility 120, or a plurality of mathematical models that simulate the operations of the wastewater treatment facility 120 and the post-stage equipment, or a plurality of mathematical models that simulate the operations of the pre-stage equipment, the wastewater treatment facility 120, and the post-stage equipment.

[0115] Also, in the above-described embodiment, the power consumption of the wastewater treatment system 100 is exemplified as the objective function value. However, the present invention is not limited thereto. In the present invention, the objective function value may be a value other than the power consumption, such as the emission amount of greenhouse gases (e.g., carbon dioxide) by the wastewater treatment system 100 or the running cost.

[0116] Also, in the above-described embodiment, the initial value of the model input data used in the model calculation process for deriving the predicted value of the operating state of the wastewater treatment system 100 was input (manually input) from the input unit 40 to the model calculation unit 28. However, the present invention is not limited to this. For example, the initial value of the model input data may be data (operating conditions, observed values, etc.) observed from the wastewater treatment system 100. In this case, it may be input from the data collection unit 10 to the model calculation unit 28.

[0117] In the above-described embodiment, the reaction tank 122 in which the anaerobic tank 123, the anoxic tank 124, and the aerobic tank 125 are connected in this order along the flow direction of the water to be treated was exemplified. However, the present invention is not limited to this. For example, the reaction tank 122 may be connected such that the anoxic tank 124, the aerobic tank 125, and the anaerobic tank 123 are arranged in this order along the flow direction of the water to be treated. Also, the tank included in the reaction tank 122 may be only the anaerobic tank 123, only the aerobic tank 125, or only the anoxic tank 124 and the aerobic tank 125.

[0118] Also, the present invention is not limited by the above-described embodiment, and those configured by appropriately combining the above-described components are also included in the present invention. In addition, all other embodiments, examples, operation techniques, etc. made by those skilled in the art based on the above-described embodiment are included in the scope of the present invention.

Explanation of Reference Numerals

[0119] 1 Operating Condition Derivation Device 10 Data Collection Unit 20 Arithmetic Processing Unit 21 Model Construction Unit 22 Sludge Dewatering Facility Model 23 Sludge Dewatering Water Quality Model 24 Sludge Dewatering Power Model 25 Wastewater Treatment Facility Model 26 Wastewater Treatment Water Quality Model 27 Wastewater Treatment Power Model 28 Model Calculation Unit 29 Operating Condition Search Unit 30 Processing Control Unit 40 Input Unit 50 Condition Setting Unit 60 Visualization Unit 70 Operation Control Unit 100 Wastewater Treatment System 110 Sludge Dewatering Equipment 111 Solid-Liquid Separator 120 Wastewater Treatment Equipment 121 Primary Sedimentation Tank 122 Reaction Tank 123 Anaerobic Tank 124 Anoxic Tank 125 Aerobic Tank 126 Final Sedimentation Tank

Claims

1. An operating condition derivation device for deriving the optimal operating conditions of a wastewater treatment system comprising a wastewater treatment facility that treats wastewater to be treated into treated water purified by biological treatment, and an associated facility that performs water treatment other than the biological treatment in relation to the wastewater treatment facility, wherein: Based on an associated facility model that simulates the operation of the associated facility and at least the operating conditions of the associated facility, a predicted value of the operating state of the associated facility is calculated, and based on a wastewater treatment facility model that simulates the operation of the wastewater treatment facility, the operating conditions of the wastewater treatment facility, and the water quality of the wastewater to be treated, a predicted value of the operating state of the wastewater treatment facility including a predicted value of the water quality of the treated water is calculated by a model calculation unit; Based on the predicted value of the operating state of the associated facility and the predicted value of the operating state of the wastewater treatment facility, an objective function value is calculated, and the operating conditions of each of the associated facility and the wastewater treatment facility when the objective function value is minimized within a range where the predicted value of the water quality of the treated water satisfies a preset constraint condition for the water quality of the treated water are searched for as the optimal operating conditions of the wastewater treatment system by an operating condition search unit; An operating condition derivation device characterized by comprising:

2. A data collection unit that collects the operating conditions of the wastewater treatment system and observed values observed from the wastewater treatment system operating according to the operating conditions; Based on each initial model of the preset associated facility model and the wastewater treatment facility model and the operating conditions of the wastewater treatment system by the data collection unit, predicted values of the operating states of each of the associated facility and the wastewater treatment facility are derived, and the parameters of each initial model are adjusted so as to reduce the error between the derived predicted values of the operating states and the observed values by the data collection unit, and the associated facility model and the wastewater treatment facility model are constructed by a model construction unit; The operating condition derivation device according to claim 1, characterized by comprising:

3. The operating condition derivation device according to claim 1 or 2, further comprising a condition setting unit that receives an input of treated water quality information for specifying the water quality of the treated water and variably sets the constraint condition according to the received treated water quality information.

4. The operating condition derivation device according to claim 1 or 2, further comprising an operating control unit that controls the operation of each of the associated facility and the wastewater treatment facility based on the optimal operating conditions searched for by the operating condition search unit.

5. The operation condition exploration unit determines whether the predicted value of the treated water quality satisfies the constraint conditions. If the constraint conditions are not satisfied, at least one value among the operation conditions of the related equipment and the wastewater treatment equipment and the water quality of the wastewater to be treated is changed in a direction such that the predicted value of the treated water quality satisfies the constraint conditions. If the constraint conditions are satisfied, the at least one value is changed in a direction such that the objective function value becomes smaller. Until the optimal operation conditions are explored, the model calculation unit repeatedly calculates the predicted value of the operation state of the related equipment and the predicted value of the operation state of the wastewater treatment equipment using the operation conditions of the related equipment and the wastewater treatment equipment including the changed values by the operation condition exploration unit and the water quality of the wastewater to be treated. The operation condition derivation device according to claim 1 or 2, characterized in that.

6. The related equipment model includes at least a power model that calculates the power consumption during the operation of the related equipment from the operation conditions of the related equipment as the predicted value of the operation state of the related equipment. The wastewater treatment equipment model includes a water quality model that calculates the predicted value of the treated water quality from the operation conditions of the wastewater treatment equipment and the water quality of the wastewater to be treated, and a power model that calculates the power consumption during the operation of the wastewater treatment equipment from the operation conditions of the wastewater treatment equipment as the predicted value of the operation state of the wastewater treatment equipment. The operation condition derivation device according to claim 1 or 2, characterized in that.

7. In an operation condition derivation method for deriving the optimal operation conditions of a wastewater treatment system including a wastewater treatment equipment that purifies the wastewater to be treated into treated water by biological treatment and related equipment that performs water treatment other than the biological treatment in relation to the wastewater treatment equipment, A model calculation step of calculating a predicted value of the operation state of the related equipment based on a related equipment model that simulates the operation of the related equipment and at least the operation conditions of the related equipment, and calculating a predicted value of the operation state of the wastewater treatment equipment including the predicted value of the treated water quality based on a wastewater treatment equipment model that simulates the operation of the wastewater treatment equipment, the operation conditions of the wastewater treatment equipment, and the water quality of the wastewater to be treated; An objective function value calculation step of calculating an objective function value based on the predicted value of the operation state of the related equipment and the predicted value of the operation state of the wastewater treatment equipment; A determination step of determining whether the predicted value of the treated water quality satisfies the preset constraint conditions for the quality of the treated water. An operating condition search step of searching for each operating condition of the related equipment and the wastewater treatment equipment when the objective function value is minimized within a range where the water quality prediction value of the treated water satisfies the constraint conditions, as the optimal operating conditions of the wastewater treatment system, An operating condition derivation method characterized by including the above.

8. Causing a computer to execute the operating condition derivation method according to Claim 7, An operating condition derivation program characterized by the above.

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