Control device, ozone generation system, ozone storage device, ozone generation device, water treatment system, ozone injection control method, and recording medium

Abstract

The control device (2) of the present application is a control device that controls an ozone generating portion (3) that can store generated ozone and inject ozone into a water treatment process (6), generates ozone in the ozone generating portion (3) in at least a part of a time period in which the unit price of electric power is a first value, that is, a first time period, so that the amount of ozone generation per unit time becomes a first amount, causes the ozone generating portion (3) to inject ozone of a second amount that is smaller than the first amount per unit time into the water treatment process (6) and store ozone that is not injected into an injection target among the generated ozone in the first time period, and causes the ozone generating portion (3) to release the stored ozone and inject it into the water treatment process (6) in at least a part of a time period in which the unit price of electric power is a second value that is higher than the first value, that is, a second time period.

Description

Technical Field

[0001] This disclosure relates to control devices, ozone generation systems, ozone storage devices, ozone generating devices, water treatment systems, ozone injection control methods, and recording media. Background Technology

[0002] Ozone has been widely used for sterilization and cleaning in recent years. Typical ozone generators produce ozone when needed. Patent Document 1 discloses a technology that reduces operating costs by operating and storing ozone at night when electricity is cheap, and then using the stored ozone during the day.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 11-292512 Summary of the Invention

[0006] The technical problem that the invention aims to solve

[0007] According to the system that applies ozone, it is not limited to use only during the daytime or other periods when electricity costs are high. For example, in water treatment, ozone needs to be provided both day and night. Even in water treatment based on membrane separation activated sludge process, where ozone water is used to clean the separation membrane, the cleaning of the separation membrane is not limited to the daytime. However, in the technology described in Patent Document 1, ozone is only stored at night and only used during the day, and the ozone generator is stopped when ozone is used. Therefore, the application of the technology described in Patent Document 1 is limited to systems with a specific usage mode where ozone is only used during periods when electricity costs are high. That is, the technology described in Patent Document 1, for example, cannot be applied to usage modes where ozone is used regardless of day or night, and the cost reduction is insufficient.

[0008] This disclosure was made in view of the above circumstances, and its purpose is to provide a control device that can reduce operating costs.

[0009] Technical means for solving technical problems

[0010] To solve the aforementioned problems and achieve the objective, the control device disclosed herein is a control device that controls an ozone generator capable of storing and injecting ozone into an ozone injection target. During at least a portion of a time period when the electricity unit price is a first value, i.e., a first time period, the ozone generator produces ozone, such that the ozone production amount per unit time is a first quantity. During the first time period, the ozone generator injects a second quantity of ozone per unit time, which is smaller than the first quantity, into the injection target and stores the ozone produced that was not injected into the injection target. During a second time period when the electricity unit price is above the first value... At least a portion of the segment, namely the second time period, involves the ozone generator releasing stored ozone and injecting it into the injection target. Using a real value representing the amount of ozone injected into the injection target by the ozone generator, the injection amount at each moment within a certain period is predicted. Using the predicted results and the electricity unit price for each time period, the amount of ozone generated, the amount of ozone stored, and the amount of stored ozone released by the ozone generator at each moment are determined, so as to reduce the electricity cost required for ozone generation within a certain period compared to the case where no storage is performed, and the determined results are used to control the ozone generator.

[0011] Invention Effects

[0012] The control device disclosed herein can reduce operating costs. Attached Figure Description

[0013] Figure 1 This is a diagram showing a structural example of a water treatment system equipped with the ozone generation system according to Embodiment 1.

[0014] Figure 2 This is a diagram showing a structural example of the control unit in Embodiment 1.

[0015] Figure 3 This is a diagram illustrating an example of a computer system that implements the control device of Embodiment 1.

[0016] Figure 4 This is a flowchart illustrating an example of the processing steps in the control unit of Embodiment 1.

[0017] Figure 5 This is a diagram illustrating an example of the ozone supply involved in Embodiment 1.

[0018] Figure 6 This is a diagram illustrating an example of the cost reduction effect of implementation method 1.

[0019] Figure 7 This is a flowchart illustrating an example of the processing steps in the control unit involved in a variation of Embodiment 1.

[0020] Figure 8 This is a diagram illustrating an example of the ozone supply involved in a variation of Embodiment 1.

[0021] Figure 9 This is a diagram illustrating an example of the cost reduction effect in a variation of embodiment 1.

[0022] Figure 10 This is a diagram showing a structural example of a water treatment system equipped with the ozone generation system according to Embodiment 2.

[0023] Figure 11 This is a diagram showing a structural example of a water treatment system equipped with the ozone generation system according to Embodiment 3.

[0024] Figure 12 This is a diagram showing an example of the structure of the control unit in Embodiment 3.

[0025] Figure 13 This is a flowchart illustrating an example of the planning steps in the case of applying cost formulating in Implementation 3.

[0026] Figure 14 This is a diagram illustrating a structural example of the injection volume prediction unit in Implementation 3, where prediction is performed using machine learning.

[0027] Figure 15 This is a flowchart illustrating an example of the actions in the model generation unit of Embodiment 3.

[0028] Figure 16 This is a flowchart illustrating an example of the operation in the prediction unit of Embodiment 3.

[0029] Figure 17 This is a schematic diagram illustrating an example of a neural network.

[0030] Figure 18 This is a diagram illustrating a structural example of the ozone generation system according to Embodiment 4.

[0031] Figure 19 This is a diagram illustrating a structural example of the ozone generation system according to Embodiment 5. Detailed Implementation

[0032] Hereinafter, the control device, ozone generating system, ozone storage device, ozone generating device, water treatment system, ozone injection control method and computer program involved in the embodiments will be described in detail based on the accompanying drawings.

[0033] Implementation method 1.

[0034] Figure 1 This is a diagram illustrating a structural example of a water treatment system equipped with the ozone generation system according to Embodiment 1. (See diagram below.) Figure 1 As shown, the water treatment system of this embodiment includes an ozone generating system 1, a water treatment process 6 that uses ozone provided from the ozone generating system 1 to treat water, and a waste ozone treatment unit 7 that treats the waste ozone discharged from the water treatment process 6 to a concentration below an allowable value.

[0035] The water treatment system of this embodiment is basically in operation 24 hours a day, and the ozone generation system 1 provides a roughly constant amount of ozone to the water treatment process 6 regardless of day or night.

[0036] In processes requiring high reliability, continuity, and consistency, such as water treatment, the performance margin for reliable treatment is taken into account when determining the specifications of the ozone generation system 1. Therefore, the design value for ozone generation often has a margin relative to the actual amount of ozone injected, i.e., the amount of ozone used. For example, determining an appropriate injection rate after the water treatment system has been in operation sometimes results in a margin; additionally, a margin is sometimes included for redundancy. Furthermore, with the promotion of energy conservation in recent years, there are also cases where the ozone injection rate is minimized. These factors lead to a difference between the design value for ozone generation and the amount of ozone injected, i.e., surplus capacity.

[0037] On the other hand, ozone generators are typically designed to achieve maximum efficiency at their design values. Therefore, if less ozone is generated than the design value, power loss and reduced efficiency occur. For efficient operation, generating ozone at the design value would result in the waste of unused ozone.

[0038] In this embodiment, in a system that operates continuously for 24 hours, operating costs are reduced by effectively utilizing the aforementioned remaining capacity. Here, an example is described for a system that uses a constant amount of ozone continuously for 24 hours, but the method of using ozone to reduce operating costs by effectively utilizing the remaining capacity of this embodiment is not limited to this, and can be applied to any other method of use.

[0039] like Figure 1 As shown, the ozone generation system 1 includes a control device 2, an ozone generating unit 3, and an ozone injection unit 5. The ozone generating unit 3 generates and stores ozone, and injects at least one of the generated ozone and the stored ozone into the ozone injection unit 5 based on instructions from the control device 2. The control device 2 controls the amount of ozone generated, stored, and removed from the ozone generating unit 3. The ozone injection unit 5 injects ozone from the ozone generating unit 3 into the water treatment process 6 to maintain the ozone injection amount into the water treatment process 6 at a target value. The water treatment process 6 is one example of the target of ozone injection from the ozone generating unit 3, but the target is not limited to the water treatment process 6.

[0040] The ozone generating unit 3 includes a raw gas supply unit 31, an ozone generator 32, an ozone storage unit 33, and switching valves 34 and 35. The raw gas supply unit 31 supplies oxygen-containing gas, i.e., the raw gas, to the ozone generator 32. The ozone generator 32 uses the raw gas supplied from the raw gas supply unit 31 to generate ozone. The ozone storage unit 33 stores the ozone generated in the ozone generator 32. Furthermore, the ozone storage unit 33 extracts the stored ozone and supplies it to the ozone injection unit 5.

[0041] In the ozone generation system 1 of this embodiment, ozone generated in the ozone generator 32 is delivered via two paths: an ozone delivery path 36 connected to the ozone injection unit 5 via a switching valve 34, and an ozone delivery path 37 connected to the ozone injection unit 5 via a switching valve 35 and an ozone storage unit 33. The ozone is delivered through one of these two paths by opening and closing the switching valves 34 and 35. For example, if the switching valve 34 is closed and the switching valve 35 is open, the ozone generated in the ozone generator 32 is stored in the ozone storage unit 33 via the ozone delivery path 37. Furthermore, if the switching valve 35 is closed and the switching valve 34 is open, the ozone generated in the ozone generator 32 is supplied to the ozone injection unit 5 via the ozone delivery path 36. Furthermore, if both switching valves 34 and 35 are opened, the ozone generated in the ozone generator 32 is transported through both ozone transport paths 36 and 37, thereby providing ozone to the ozone injection unit 5 and storing it in the ozone storage unit 33. When using these two transport paths to transport ozone, the remaining portion of the ozone generated by the ozone generator 32 that is injected into the water treatment process 6 by the ozone injection unit 5 is transported through the ozone transport path 37 and stored in the ozone storage unit 33. The opening and closing of the switching valves 34 and 35 can be controlled directly by the control device 2, or by a control unit (not shown) within the ozone generator 3 based on instructions from the control device 2.

[0042] The ozone storage unit 33 can be constructed using any method, but it may include, for example, an adsorption cylinder filled with an adsorbent such as silica gel. Within the adsorption cylinder, by controlling temperature and pressure, ozone and oxygen are separated from a mixed gas containing both by utilizing the difference in their adsorption and desorption properties. The ozone storage unit 33 selectively adsorbs and stores ozone using an adsorbent maintained at a low temperature, and supplies the separated oxygen to the ozone generator 32 via the oxygen reuse path 38, thus reusing the separated oxygen as a feed gas. This significantly reduces the cost of the feed gas.

[0043] Ozone has a short lifespan, making it difficult to store. However, as described above, ozone can be stored for a long time by employing an ozone storage unit 33, which utilizes the adsorption-desorption phenomenon associated with pressure fluctuations of an adsorbent maintained at a low temperature. That is, the generated ozone can be temporarily stored using the ozone storage unit 33, and any amount of ozone can be extracted from the ozone storage unit 33 at any given time and supplied to the ozone injection unit 5 via the ozone delivery path 37.

[0044] The control device 2 includes a data input / output unit 21 and a control unit 22. The data input / output unit 21 receives input from the user and provides various information to the user. For example, the data input / output unit 21 displays the reduction in operating costs, the amount of ozone generated, and the operating status of the ozone generator 3. The control unit 22 uses the design value of the ozone generation amount in the ozone generator 3 and the required ozone injection amount to formulate a plan related to the generation, storage, and extraction of stored ozone to suppress operating costs, and controls the generation, storage, and extraction of ozone in the ozone generator 3 according to the formulated plan.

[0045] Figure 2 This is a diagram showing an example of the structure of the control unit 22 in this embodiment. Figure 2 As shown, the control unit 22 includes a planning unit 221, an electricity unit price storage unit 222, an injection quantity information storage unit 223, a planning storage unit 224, and an instruction unit 225.

[0046] The electricity unit price storage unit 222 stores the electricity unit price as the electricity price for different time periods. The injection quantity information storage unit 223 stores the target value of the ozone injection quantity injected into the water treatment process 6, and also stores the design value of the ozone injection quantity, i.e., the maximum amount of ozone produced by the ozone generator 32 of the ozone generator unit 3. The electricity unit price, the design value of the ozone injection quantity, and the target value of the ozone injection quantity for each time period can be input by the user via the data input / output unit 21, or received by the control device 2 from other devices not shown. Furthermore, these values ​​can also be changed via the data input / output unit 21.

[0047] The planning unit 221 uses the electricity unit price for each time period stored in the electricity unit price storage unit 222 and the design value and target value of ozone injection amount stored in the ozone injection amount information storage unit 223 to formulate a plan related to ozone generation, storage, and extraction of stored ozone, in order to suppress operating costs. Furthermore, the planning unit 221 generates information indicating the electricity reduction effect based on the formulated plan and outputs the generated information and the formulated plan to the data input / output unit 21. Hereinafter, the plan related to ozone generation, storage, and extraction of stored ozone will be referred to as a plan or ozone generation plan. The planning unit 221 stores the formulated plan in the plan storage unit 224. The instruction unit 225, based on the plan stored in the plan storage unit 24, instructs the ozone generation unit 3 on the amount of ozone generated, stored, and extracted from stored ozone in the ozone generation unit 3.

[0048] Here, the hardware structure of the control device 2 in this embodiment will be described. The control device 2 is implemented by a computer system. Figure 3 This is a diagram showing an example of a computer system that implements the control device 2 of this embodiment. Figure 3 The computer system shown includes a processor 101, a memory 102, a communication circuit 103, a display unit 104, and an input unit 105.

[0049] The processor 101, serving as a computing device, is, for example, a CPU (Central Processing Unit), GPU (Graphics Processing Unit), microprocessor, microcontroller, or DSP (Digital Signal Processor). The memory 102, serving as a storage unit, is, for example, a semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), or EEPROM (Electrically Erasable Programmable Read Only Memory), a hard disk, or a floppy disk. The communication circuit 103 is a transceiver capable of communication.

[0050] The display unit 104 is a monitor or display screen, and the input unit 105 is a button, switch, keyboard, mouse, or similar device. Alternatively, a touch panel integrating the display unit 104 and the input unit 105 can be used.

[0051] The control device 2 is implemented by executing a program that describes the processes performed by the control device 2. Specifically, the program is installed in the memory 102. When the program is executed, the program read from the memory 102 is stored in the main memory area of ​​the memory 102. In this state, the processor 101 executes the processes of the control device 2 as described in this embodiment according to the program stored in the memory 102. In addition, the program can be provided by a recording medium or by a transmission medium via a communication circuit 103.

[0052] Executed by processor 101 Figure 3 The program stored in the memory 102 shown can thus achieve Figure 1 The control unit 22 is shown. Furthermore, the control unit 22 is also implemented using the memory 102. Figure 1 The data input / output unit 21 shown consists of Figure 3 This is achieved through the display unit 104 and the input unit 105 shown.

[0053] Next, the operation of this embodiment will be explained. As described above, the designed ozone injection amount is more than the actual ozone injection amount injected into water treatment process 6. Therefore, if the designed ozone injection amount is set to X mg / L and the target ozone injection amount injected into water treatment process 6 is set to Y mg / L, then X is larger than Y. Furthermore, X and Y are real numbers. In this embodiment, the ozone injection amount is always set to a constant amount, but when the target ozone injection amount varies depending on the time period, the target amount for each time period is stored in the injection amount information storage unit 223.

[0054] In this embodiment, the difference between X and Y, i.e., the remaining capacity, is utilized to reduce operating costs. Figure 4 This is a flowchart illustrating an example of the processing steps in the control unit 22 of this embodiment. The control unit 22 determines whether the electricity unit price differs due to time periods (step S1). Specifically, the planning unit 221 reads the electricity unit price for each time period from the electricity unit price storage unit 222 and determines whether the read electricity unit price differs due to time periods.

[0055] When the electricity price varies depending on the time of day (step S1 is yes), the control unit 22 formulates an ozone generation plan to maximize ozone generation capacity during other time periods, thereby storing ozone for use during the time period with the highest electricity price (step S2). There is no particular restriction on the period for which the ozone generation plan is formulated, but one day is set as the target period. Furthermore, since electricity prices are often determined based on time periods within a day, the target period is set to one day here, but plans can also be formulated in units of one week, one year, etc.

[0056] In step S2, specifically, the planning unit 221 uses the electricity unit price read in step S1 to determine the time period with the highest electricity unit price. It then reads the target value of the injection volume for that time period from the injection volume information storage unit 223 and calculates the amount of ozone required for injection during the time period with the highest electricity unit price, as the storage requirement. Next, the planning unit 221 formulates a plan to generate ozone at the designed injection volume value X mg / L and store the calculated storage requirement during time periods other than the time period with the highest electricity unit price. For example, the planning unit 221 formulates a plan to generate ozone at the designed injection volume value X mg / L and store the calculated storage requirement during the time period with the lowest electricity unit price. In this case, if ozone injection is also required during a time period with a lower electricity unit price, the planning unit 221 formulates an ozone generation plan to generate the target value Y mg / L of ozone injection for that time period, and also generate ozone for storage. That is, surplus capacity is utilized to store ozone. If the amount of ozone that can be stored during periods of low electricity prices is less than the required storage amount, the planning unit 221 also formulates a plan to generate and store ozone at a designed injection rate of X mg / L during the second lowest electricity price period. By repeating this operation, the planning unit 221 can formulate an ozone generation plan that stores ozone used during periods of high electricity prices in other periods. Therefore, compared to generating a target ozone injection rate without storage, operating costs can be reduced.

[0057] After step S2, the control unit 22 stores the plan, namely the ozone generation plan (step S4), and the process ends. In step S4, specifically, the planning unit 221 stores the ozone generation plan in the plan storage unit 224.

[0058] If the electricity unit price does not vary according to the time period (step S1 is no), the control unit 22 determines the time period for generating ozone at maximum capacity, formulates an ozone generation plan based on the determined time period (step S3), and advances the process to step S4.

[0059] In step S3, the planning unit 221 determines the time period for generating ozone at maximum capacity, i.e., at the designed injection rate of X mg / L. Furthermore, if step S1 is not specified, the electricity price is constant and independent of the time period; therefore, the time period for generating ozone at the designed injection rate of X mg / L can be arbitrarily set. In addition, the planning unit 221 formulates a plan to ensure that the ozone stored by generating ozone at the designed injection rate of X mg / L is used in any time period outside of this specified time period. As described above, the ozone generator 32 is designed to be most efficient when generating ozone at maximum capacity. Therefore, even if the electricity price does not change according to the time period, by setting the time period for generating ozone at the designed injection rate of X mg / L, the efficiency is higher during that time period than during other time periods. Therefore, the electricity required to generate a constant amount of ozone can be reduced, thus reducing operating costs. For example, generally, if the efficiency for generating ozone at the designed injection rate of X mg / L is set to 90%, the efficiency for generating the actual required injection rate of ozone is often around 70% to 80%. Therefore, by generating ozone at a designed injection rate of X mg / L, power loss can be reduced, thus lowering operating costs.

[0060] Alternatively, if step S1 is not performed, step S3 is performed to consider efficiency. However, step S3 can be omitted, and an ozone generation plan can be developed to generate the required amount of ozone without storage.

[0061] The instruction unit 225 controls the ozone generator 3 according to the established plan. This allows for the utilization of surplus capacity to reduce operating costs. As an example, the following scenario illustrates the case where X = 2.5, Y = 0.5, meaning the design value for ozone injection is 2.5 mg / L, and after operation, ozone is injected into the water treatment process 6, which operates continuously for 24 hours, at a constant injection rate of the target value of 0.5 mg / L. Furthermore, the water treatment capacity of the water treatment process 6 is set at 150,000 tons / day. Electricity costs are divided into three time periods: peak hours (8 hours), normal hours (8 hours), and nighttime hours (8 hours). The electricity price is highest during peak hours, followed by normal hours, and lowest during nighttime hours.

[0062] In this scenario, during the nighttime period when electricity prices are lowest, ozone generator 32 is operated to produce the required ozone supply of 25 kg for 8 hours, and the remaining 25 kg is stored during the peak period when electricity prices are highest. The residual capacity of ozone generation system 1 is 2.0 mg / L (2.5 mg / L minus 0.5 mg / L). If operated at the designed ozone injection rate for 8 hours, it can store 100 kg of ozone, thus fully meeting the 25 kg required during the peak period. For example, during the nighttime period, ozone generator 32 can be operated for approximately 2 hours at the designed ozone injection rate of 2.5 mg / L. Alternatively, a longer-term plan can be developed to operate at the designed ozone injection rate of 2.5 mg / L for 8 hours, storing the required amount for 4 days of peak periods. The ozone separated during storage is then supplied to ozone generator 32 via ozone reuse path 38 for reuse.

[0063] During normal periods, ozone generator 32 is operated to produce the required ozone supply of 25 kg for that period. That is, ozone is produced at a target ozone injection rate of 0.5 mg / L.

[0064] Therefore, the control device 2 of this embodiment formulates a plan and issues instructions to the ozone generator 3 as described above, so that the ozone generator 3 generates ozone during at least a portion of the time period when the electricity unit price is the first value, i.e., the first time period, so that the ozone generation amount per unit time is the first amount. The time period when the electricity unit price is the first value is, for example, the nighttime period mentioned above. Then, during the first time period, the control device 2 causes the ozone generator 3 to inject a second amount of ozone, which is smaller than the first amount per unit time, into the injection target, and stores the ozone generated that was not injected into the injection target. Furthermore, during at least a portion of the time period when the electricity unit price is above the first value, i.e., the second time period, the control device 2 causes the ozone generator 3 to release the stored ozone and inject it into the injection target. The time period when the electricity unit price is the second value is, for example, the peak time period mentioned above. For example, the first amount is the amount corresponding to the capacity of X mg / L mentioned above, and the second amount is the amount corresponding to the capacity of Y mg / L mentioned above. That is, the first amount is, for example, the maximum amount that the ozone generator 3 can generate per unit time. In the example above, during the entire peak period, the ozone generator 3 releases the stored ozone and injects it into the target at a second amount per unit time. However, the stored and released ozone can also be used during certain periods, rather than the entire peak period. Furthermore, in the example above, ozone is generated at maximum capacity during nighttime hours, but this is not a limitation. If ozone is generated and stored at a capacity higher than Y mg / L, the remaining capacity can be utilized to reduce operating costs.

[0065] Furthermore, the program for controlling the control device 2 of this embodiment, for example, causes the computer system controlling the ozone generator 3 to perform the following steps: During at least a portion of a time period when the electricity unit price is a first value, i.e., a first time period, the ozone generator 3 generates ozone, such that the amount of ozone generated per unit time is a first amount. The ozone generator 3 can store the generated ozone and inject the ozone into the ozone injection target. Furthermore, the program causes the computer system to perform the following steps: During the first time period, the ozone generator 3 injects a second amount of ozone, less than the first amount, into the injection target per unit time, and stores ozone generated that was not injected into the injection target; and during at least a portion of a time period when the electricity unit price is a second value or higher, i.e., a second time period, the ozone generator 3 releases the stored ozone and injects it into the injection target.

[0066] Figure 5 This is a diagram illustrating an example of the ozone supply involved in this embodiment. Figure 5 As illustrated above, the electricity price varies across three time periods: peak, normal, and nighttime. This illustrates the ozone supply when ozone generation system 1 injects ozone into water treatment process 6 at a constant rate over 24 hours. Figure 5 As shown, during peak hours, the ozone generator 32, which is the main power source, does not operate but stops in advance. Then, the ozone storage unit 33 releases the ozone stored during the nighttime period and supplies the ozone to the ozone injection unit 5. Figure 5 The comparative example shown is one that produces ozone at a constant rate over 24 hours without storing ozone.

[0067] Figure 6 This diagram illustrates an example of the cost reduction effect of this embodiment. (and...) Figure 5 Similarly, in the comparative examples, Figure 6 The comparative example shown is one that produces ozone at a constant rate over 24 hours without storing it. Figure 6 As shown, in the comparative example, the ozone production is constant regardless of the time of day. Therefore, the operating cost varies depending on the electricity price, with the highest operating cost during peak hours. In contrast, in this embodiment, no ozone is produced during peak hours. Therefore, there are no operating costs for ozone production during peak hours, while ozone is produced during periods with lower electricity prices. As a result, as shown on the right, this embodiment reduces daily operating costs compared to the comparative example. Furthermore, in this embodiment 1, not only the difference in electricity prices but also the reuse of oxygen generated during storage contributes to reducing raw material costs.

[0068] In addition, the data input / output unit 21 displays... Figure 6The cost reduction effect shown can be displayed to the user, indicating the amount of cost reduction. Furthermore, the data input / output unit 21 can display the ozone generation rate in chronological order, or it can display the operating status of the ozone generator 32 in chronological order. The ozone generation rate and operating status can be planned values, or data acquired from the ozone generator 32 and displayed as actual values. Thus, the data input / output unit 21 can display, for example, at least one of the following: a screen showing the reduction in electricity costs compared to a situation without ozone storage; a screen showing the ozone generation rate and ozone storage rate for each time period; and the operating status of the ozone generator 32.

[0069] <Variation Example>

[0070] In the example above, ozone used during peak hours is stored during the nighttime period. However, during the nighttime period, not only ozone needed during peak hours can be stored, but also ozone needed during normal hours, thus limiting the operation of ozone generator 32 to the nighttime period.

[0071] Figure 7 This is a flowchart illustrating an example of the processing steps in the control unit 22 involved in a variation of this embodiment. Figure 7 The steps S1, S3, S4 shown are... Figure 4 The example shown is the same. If step S1 is yes, the control unit 22 selects the time period with the highest electricity unit price from the unselected time periods (step S5). In detail, the planning unit 221 uses the electricity unit price read in step S1 to select the time period with the highest electricity unit price from the unselected time periods.

[0072] Next, the control unit 22 determines whether there are additional ozone-generating periods within the time periods where the electricity unit price is lower than the selected time period (step S6). Specifically, the planning unit 221 uses the electricity unit price read in step S1 and the temporarily maintained plan to determine whether there are additional ozone-generating periods within the time periods where the electricity unit price is lower than the selected time period. The temporarily maintained plan is the plan formulated but not yet finalized in step S7 described later.

[0073] If there is no additional time period for ozone generation in the time period where the electricity unit price is lower than the electricity unit price of the selected time period (no in step S6), the control unit 22 advances the process to step S4.

[0074] If there is a time period in which the electricity unit price is lower than the electricity unit price of the selected time period, and there is a time period in which ozone can be generated additionally (step S6 is yes), the control unit 22 formulates a plan (step S7), which plans to generate ozone used in the selected time period in the time period with the lowest electricity unit price, excluding the time period that has already been planned to generate ozone at its maximum capacity.

[0075] In detail, in step S7, the planning unit 221, referring to the temporarily maintained plan, extracts time periods other than the time periods already planned for maximum ozone generation, and formulates a plan for generating ozone for use in the time period selected in step S5 within the extracted time periods. In the first step S7, there is no temporarily maintained plan, and the time period with the highest electricity unit price is selected in step S5; therefore, [the process is as follows]. Figure 4 The processing in step S2, for example, involves calculating the required storage amount during the period with the highest electricity unit price and formulating a plan to generate and store the required storage amount during the period with the lowest electricity unit price. The planning unit 221 temporarily holds the formulated plan. In the second step S7, the period for storing the required storage amount during the period with the highest electricity unit price has been determined, therefore, there is a period that has been determined to operate at maximum capacity to supply the required storage amount during the period with the highest electricity unit price. Therefore, the control unit 22 formulates a plan and holds the formulated plan, which generates ozone for use in the selected period during the period with the lowest electricity unit price, excluding the period that has been planned to generate ozone at maximum capacity. The same processing is performed in the third and subsequent steps S7.

[0076] After step S7, the planning unit 221 of the control unit 22 determines whether to end the planning process (step S8). If the planning process is ended (step S8 is yes), the process proceeds to step S4. In step S8, for example, the planning process is determined to end if a certain number of times has been performed in step S7. The number of times determined is, for example, the number obtained by subtracting 1 from the number of electricity price divisions. For example, if the electricity price for the three divisions of peak time, normal time, and nighttime time is determined, the number of times determined is 2.

[0077] If the planning process is not completed (step S8 is not specified), the control unit 22 repeats the process from step S5. By performing this process, plans can be made not only for the time period with the highest electricity unit price, but also for other time periods, which utilize ozone stored during the time period with the lower electricity unit price.

[0078] For example, the designed ozone injection rate is 2.5 mg / L. After operation, ozone is injected into the water treatment process 6, which operates 24 hours a day, at a constant injection rate of 0.5 mg / L (the target ozone injection rate). The treatment capacity of the water treatment process 6 is set at 150,000 tons / day. In this example, the required storage amount for peak periods can be stored during the nighttime period. Furthermore, the required storage amount for normal periods is also 25 kg, which can also be stored during the nighttime period. Therefore, in this case, the ozone generation system 1 injects ozone into the water treatment process 6 during the nighttime period at the target ozone injection rate of 0.5 mg / L, and generates ozone at the designed ozone injection rate of 2.5 mg / L to store 50 kg of ozone. Then, the ozone generation system 1 releases the stored ozone during peak and normal periods and injects it into the water treatment process 6.

[0079] Therefore, the control device 2 can, during at least a portion of a time period in which the electricity price is higher than the first value and lower than the second value (i.e., a third time period), cause the ozone generator 3 to release the stored ozone and inject it into the target. The time period in which the electricity price is the third value is, for example, the aforementioned normal time period.

[0080] Figure 8 This is a diagram illustrating an example of the ozone supply involved in a variation of this embodiment. Figure 8 The illustrated variation shows an example of ozone that can be stored during nighttime hours for use during peak and normal periods. In this case, ozone generation is not required during peak and normal periods.

[0081] Figure 9 This is a diagram illustrating an example of the cost reduction effect in a variation of this embodiment. Figure 9 In, such as Figure 8 As shown, the usage cost of a variation is illustrated in the case where ozone can be stored during both peak and normal periods at night. A comparative example is an example where ozone is generated at a constant amount over 24 hours without storage. Therefore, in the variation, compared to... Figure 6 Compared to the example shown, this can further reduce application costs.

[0082] As described above, in this embodiment, surplus capacity is utilized during periods of lowest electricity prices to store ozone for use at least during periods of highest electricity prices. Therefore, in a system with 24-hour ozone injection, operating costs can be reduced compared to a system without storage. Furthermore, not limited to 24-hour ozone injection systems, even when ozone is used only during the day or when ozone usage varies across time periods, operating costs can similarly be reduced by utilizing surplus capacity to store ozone during periods of lowest electricity prices.

[0083] Implementation method 2.

[0084] Figure 10 This is a diagram illustrating a structural example of a water treatment system equipped with the ozone generation system according to Embodiment 2. (See diagram for details.) Figure 10 As shown, the water treatment system of this embodiment is the same as the water treatment system of Embodiment 1, except that it includes an ozone generating system 1a instead of the ozone generating system 1 of Embodiment 1. Structural elements having the same functions as in Embodiment 1 are labeled with the same reference numerals as in Embodiment 1, and repeated descriptions are omitted. Hereinafter, the differences from Embodiment 1 will be the main focus of the description.

[0085] The ozone generating system 1a of this embodiment is the same as the ozone generating system 1 of Embodiment 1, except that it includes an ozone generating unit 3a instead of the ozone generating unit 3 of Embodiment 1. The ozone generating unit 3a of this embodiment is the same as that of Embodiment 1, except that it includes ozone generators 32-1, 32-2 and a standby generator 39 instead of the ozone generator 32 of Embodiment 1. Ozone generators 32-1, 32-2 and the standby generator 39 are the same as the ozone generator 32 of Embodiment 1. The three ozone generators 32-1, 32-2 and the standby generator 39 are incorporated into the ozone generating system 1a, wherein ozone generators 32-1 and 32-2 are always operating, and the standby generator 39 is used as a backup.

[0086] Therefore, in the ozone generation system 1a equipped with a backup generator 39, in this embodiment, the backup generator 39 is also operated during periods of lower electricity prices to reduce operating costs. That is, in this embodiment, the total design value of the ozone injection amount of the three ozone generators 32-1, 32-2 and the backup generator 39 is used as the design value of the ozone injection amount in Embodiment 1, and ozone is stored during periods of lower electricity prices, similar to Embodiment 1.

[0087] For example, similar to the example described in Implementation 1, the electricity unit price is determined in three divisions: peak time period, normal time period, and nighttime time period, and the ozone generation system 1a injects ozone into the water treatment process 6 with a target value of Y mg / L, which is a constant amount for 24 hours.

[0088] In this embodiment, the control unit 22 uses the total design value of the ozone injection amount of the three ozone generators 32-1, 32-2, and the standby generator 39 as the design value X mg / L of the ozone injection amount in Embodiment 1, and formulates an ozone generation plan in the same way as in Embodiment 1. Therefore, ozone that can be stored during peak hours can be used during the nighttime period when electricity prices are lower, and the stored ozone can be used during peak hours. Alternatively, similar to a variation of Embodiment 1, ozone that can be stored during both peak and normal hours can be used during the nighttime period when electricity prices are lower, and the stored ozone can be used during both peak and normal hours.

[0089] Therefore, in this embodiment, the backup generator 39 is used to store ozone even during periods of low electricity price, thereby reducing operating costs and making effective use of the backup generator 39.

[0090] Implementation method 3.

[0091] Figure 11 This is a diagram showing a structural example of a water treatment system equipped with the ozone generation system according to Embodiment 3. Figure 11 The water treatment system shown is a system that uses membrane separation activated sludge process to purify the water being treated. For example... Figure 11 As shown, the water treatment system of this embodiment includes: a membrane bioreactor (MBR) system 9, which includes membrane bioreactor (MBR) devices 91-1 and 91-2; and an ozone generation system 1b, which provides ozone water for cleaning the membrane units 92-1 and 92-2 of the MBR devices 91-1 and 91-2, respectively.

[0092] In MBR system 9, the treated water is biologically decomposed by activated sludge in a treatment tank (not shown), and then filtered from the primary side to the secondary side in membrane units 92-1 and 92-2, which have filter membranes, and discharged through piping (not shown).

[0093] On the surface and inside of the filtration membranes in membrane units 92-1 and 92-2, fouling substances including sludge, suspended solids, microorganisms, and microbial metabolites adhere or adhere. This causes an increase in the membrane permeation pressure differential (the difference between the secondary side pressure and atmospheric pressure during membrane filtration), resulting in a gradual deterioration of filtration performance, such as a decrease in the filtration flux per unit time and per unit membrane filtration area. Therefore, to maintain the filtration performance of the separation membranes, membrane unit cleaning is necessary to remove fouling substances from both the inside and surface of the separation membranes. In this embodiment, ozone water generated by the ozone generation system 1b is used as the cleaning solution for membrane cleaning.

[0094] like Figure 11As shown, the ozone generating system 1b is identical to the ozone generating system 1 of Embodiment 1, except that it includes a control device 2a, an ozone water manufacturing unit 8 (instead of the control device 2), and an ozone injection unit 5. Structural elements having the same functions as in Embodiment 1 are labeled with the same reference numerals as in Embodiment 1, and repeated descriptions are omitted. Hereinafter, the description will focus on the differences from Embodiment 1.

[0095] In this embodiment, similar to the ozone injection unit 5 in Embodiment 1, the ozone water production unit 8 is supplied with either ozone generated in the ozone generator 32 or ozone released from the ozone storage unit 33. The ozone water production unit 8 uses the supplied ozone to generate ozone water and injects the generated ozone water into the injection units of membrane units 92-1 and 92-2. Furthermore, Figure 11 In this system, the ozone water generation unit 8, which serves as the injection unit, is located outside the MBR system 9. However, the ozone water generation unit 8 can also be located near the membrane units 92-1 and 92-2, respectively. Membrane unit cleaning is performed appropriately based on the historical changes in the membrane performance of membrane units 92-1 and 92-2. Although the timing of membrane unit cleaning is not shown in the figure, an instruction is sent from the MBR system 9 to the control device 2a.

[0096] In this embodiment, the design value for the ozone injection rate is also set as a target value that needs to be reduced from the design value after the water treatment system is put into operation. In this embodiment, the design value for the ozone injection rate is set to X mg / L, and the target value for the ozone injection rate is set to Y mg / L. During membrane unit cleaning in MBR units 91-1 and 91-2, the cleaning timing and frequency vary depending on the state of the inflow water. Therefore, compared to consuming electricity by generating ozone for each cleaning cycle, generating and storing ozone at the design value of X mg / L during periods of lower electricity price, and releasing it when cleaning is required, is more energy-efficient and reduces operating costs. The cleaning timing in MBR units 91-1 and 91-2 can be simultaneous or different in each unit. Furthermore, the cleaning frequency can be various, such as once per day, six times per day, or once per week.

[0097] like Figure 11 As shown, the control device 2a includes the same data input / output unit 21 and control unit 22a as in Embodiment 1.

[0098] For example, similar to the example described in Embodiment 1, if three electricity unit prices are set for peak hours, normal hours, and nighttime hours, the control unit 22a formulates a plan to generate ozone at a designed ozone injection rate during the nighttime hours of a certain day and pre-store it in the ozone storage unit 33 until the maximum amount that can be stored is reached, and controls the ozone generating unit 3 based on the plan. Alternatively, the control unit 22a can predict the number of cleaning cycles within a certain period and use the predicted number of cleaning cycles to determine the amount of ozone stored.

[0099] Figure 12 This is a diagram showing an example of the structure of the control unit 22a in this embodiment. Figure 12 As shown, the control unit 22a adds an injection volume performance storage unit 226 and an injection volume prediction unit 227 to the control unit 22 of Embodiment 1, and includes a planning unit 221a to replace the planning unit 221 of Embodiment 1. The injection volume performance storage unit 226 acquires and stores performance values ​​of the ozone injection volume injected into membrane units 92-1 and 92-2. The performance values ​​of the ozone injection volume injected into membrane units 92-1 and 92-2 can be received from the ozone water production unit 8 or the MBR system 9 by the data input / output unit 21 and stored in the injection volume performance storage unit 226. For example, the user can input an approximate performance value of the cleaning frequency, such as how many times a month, via the data input / output unit 21.

[0100] The injection volume prediction unit 227 uses the performance values ​​stored in the injection volume performance storage unit 226 to predict the amount of ozone injection required for membrane unit cleaning within a certain period, and outputs the prediction result to the planning unit 221a. For example, assuming the amount of ozone injection used in one cleaning, the injection volume prediction unit 227 predicts the number of membrane unit cleanings within a certain period based on the performance values ​​stored in the injection volume performance storage unit 226, and multiplies the predicted number of membrane unit cleanings by the amount of ozone injection used in one cleaning to predict the ozone injection volume within a certain period. For example, the past performance values ​​can be divided into periods, the number of membrane unit cleanings within each period can be calculated separately, and the average of the calculated number of times can be set as the predicted value of the number of membrane unit cleanings.

[0101] The planning unit 221a uses the prediction results received from the injection volume prediction unit 227 to formulate a plan to store the ozone injection amount required for membrane unit cleaning for a certain period during periods of low electricity prices. In this case, the injection volume prediction unit 227 can plan to generate and store more ozone than predicted. Even if there is excess stored ozone in actual operation, it can be used for cleaning in the next specified period. Furthermore, ozone can be generated for cleaning when the actual number of cleaning cycles exceeds the prediction. In this case, operating costs can be reduced compared to not storing ozone.

[0102] For example, if the electricity unit price is set for three periods: peak time, normal time, and nighttime time, and the period is one week, and the number of cleanings is predicted to be three times during the week, the planning department 221a formulates a plan to generate and store ozone that meets the minimum number of cleanings during the nighttime period at the beginning of the week.

[0103] Furthermore, the examples described above assume that the required ozone injection volume for a given period can be met during the period with the lowest electricity price. However, depending on the length of the given period and the amount of ozone used, it is possible that the required ozone injection volume cannot be met during the period with the lowest electricity price. Additionally, the possibility of future adjustments to electricity price tiers or changes in electricity prices should also be considered.

[0104] Therefore, the planning department 221a can formulate the operating cost as an evaluation function, determine the constraints, and solve the optimization problem under the constraints to minimize the operating cost, thereby determining the plan for a certain period.

[0105] Figure 13 This is a flowchart illustrating an example of the planning steps when using cost formulating in this embodiment. Steps S1, S3, and S4 are the same as in Embodiment 1. Figure 4 The example shown is the same.

[0106] If step S1 is true, the injection volume prediction unit 227 predicts the amount of ozone used within a certain period, i.e., the amount of ozone injected (step S11). The prediction result is the predicted value of the injection volume for each time period within the certain period. At this time, there is no particular limitation on the time scale of each time period; it can be a 30-minute unit, an hourly unit, or a unit other than these. Next, the planning unit 221a uses the prediction result of the injection volume prediction unit 227, i.e., the predicted value of the usage, to set the ozone generation amount for each time period within the certain period (step S12). In addition, in step S12, not only the ozone generation amount is set, but also the amount of ozone used and the amount stored in the generated ozone are set. The initial values ​​of these set amounts are set to arbitrary values ​​within the range of satisfying the limiting conditions. The limiting conditions are, for example, the conditions shown in the following equations (1) to (6). Other limiting conditions may also be determined.

[0107] y (t) =A (t) +B (t) · · · (1)

[0108] The sum of S(t) from time 0 to t - the sum of B(t) from time 0 to time t-1 ≥ B(t) ···(2)

[0109] The sum of S(t) from time 0 to time t - the sum of B(t) from time 0 to time t ≦ the upper limit of ozone storage...(3)

[0110] G(t)≦X max ···(4)

[0111] S(t)≦X max ···(5)

[0112] G (t) =S (t) +A (t) · · · (6)

[0113] Additionally, time t is set to an integer representing the time when the start time of a certain period is set to 0, y(t) is set to the predicted amount of ozone used at time t, G(t) is set to the ozone generation at time t, that is, the amount of ozone produced by ozone generator 32 at time t, and X... max Let A(t) be the maximum ozone generation per unit time (equivalent to the design value). Furthermore, let A(t) be the amount used in G(t) at time t, i.e., the injection amount at time t; let S(t) be the amount stored in G(t) at time t; and let B(t) be the amount of ozone released from the stored ozone at time t.

[0114] In the above formula, the upper limit of ozone storage and X max The value y(t) is predetermined and input as the prediction result. Therefore, the planning unit 221a appropriately sets the above G(t), A(t), B(t), and S(t) within the range that satisfies the above constraints.

[0115] Next, the planning department 221a calculates the operating cost over a certain period (step S13). For example, the planning department 221a calculates the electricity consumption, θ, in the operating cost using the following formula (7). Here, the electricity consumption is considered as the operating cost, but the operating cost can also include the cost of the raw material gas. In addition, C(t) is the electricity unit price at time t, P(t) is the electricity required to generate a unit amount of ozone, and η(t) is the efficiency expressed as a percentage. P(t) is predetermined. In addition, η(t) is the design value and is the maximum as described above. If ozone generation is performed at a value smaller than the design value, it will decrease. Therefore, the planning department 221a determines η(t) in advance as a function of G(t), or maintains the correspondence between η(t) and G(t) in a table, and uses G(t) to calculate η(t).

[0116] θ=Σ{C(t)·G(t)·P(t)·100 / η(t)}···(7)

[0117] Next, the planning unit 221a determines whether to end the search (step S14). If the conditions for ending the search are met, the planning unit 221a determines that step S14 is correct. The conditions for ending the search can be determined based on the search algorithm for the optimization problem, such as whether a certain number of searches have been performed.

[0118] If the search is not terminated (step S14 is not specified), the set ozone generation amount is changed (step S15), and the planning unit 221a repeats the process from step S13. In step S15, G(t), A(t), B(t), and S(t) are changed within the range that satisfies the above-mentioned constraints. The method for changing these values ​​is determined according to the search algorithm for the optimization problem.

[0119] If the search ends (step S14 is yes), the planning unit 221a formulates a plan based on the setting value that minimizes the operating cost (step S16) and advances the process to step S4. Specifically, the planning unit 221a maintains the setting values ​​corresponding to the operating cost calculated in step S13, namely G(t), A(t), B(t), and S(t), and in step S16, formulates a plan based on the setting value that minimizes the operating cost among them.

[0120] By employing the above methods, an ozone generation plan can be developed to minimize operating costs over a given period. Furthermore, Figure 13 The treatment shown is not limited to membrane unit cleaning and can be applied to any system that uses ozone. Figure 13 The processing shown can also be applied, for example, to the system described in Embodiment 1 that always provides a constant amount. In this case, the predicted value of the injection amount over a certain period can be set as a constant value, independent of time t.

[0121] Furthermore, the injection volume prediction unit 227 can acquire data representing the status of membrane units 92-1 and 92-2, and use this data to predict the amount of ozone used within a certain period. For example, the control unit 22a can acquire data from the MBR system 9 obtained by measuring the difference between the secondary side pressure and atmospheric pressure of membrane units 92-1 and 92-2, and the filtration water volume (flux) per unit time and per unit membrane filtration area of ​​membrane units 92-1 and 92-2, and use the acquired data to predict the timing of membrane unit cleaning or the number of membrane unit cleanings within a certain period through machine learning.

[0122] Figure 14 This is a diagram illustrating a structural example of the injection volume prediction unit 227 in this embodiment when prediction is performed using machine learning. Figure 14 In the example shown, the injection volume prediction unit 227 includes a model generation unit 231, a learned model storage unit 232, and a prediction unit 233.

[0123] Figure 15 This is a flowchart illustrating an example of the operations in the model generation unit 231 of this embodiment. Additionally, Figure 15 The example described uses a machine learning algorithm with a teacher, but there are no restrictions on the machine learning algorithm used; reinforcement learning, etc., can be used. The model generation unit 231 acquires teacher data containing measurement data and correct data (step S31). Specifically, the model generation unit 231 acquires, for example, measurement data representing the states of membrane units 92-1 and 92-2 and corresponding correct data from the MBR system 9 via the data input / output unit 21. For example, the model generation unit 231 acquires measurement data during the processing period as time series data and acquires the time when membrane unit cleaning is performed at a certain period after that period as correct data. Multiple sets of this measurement data and corresponding correct data are acquired.

[0124] Next, the model generation unit 231 generates a learning completion model (step S32). In detail, the model generation unit 231 uses the acquired multiple sets of data as teacher data and utilizes teacher-aided machine learning to generate a learning completion model.

[0125] Next, the model generation unit 231 stores the learned model (step S33) and ends the process. Specifically, in step S33, the model generation unit 231 stores the learned model in the learned model storage unit 232. Furthermore, the learned model can be generated for each membrane unit 92-1 and 92-2, or a common learned model can be used in membrane units 92-1 and 92-2.

[0126] Figure 16 This is a flowchart illustrating an example of the operation in the prediction unit 233 of this embodiment. For example... Figure 16 As shown, the prediction unit 233 acquires measurement data (step S41). Specifically, when predicting the number of membrane unit cleanings to be performed within a certain period after this period, the prediction unit 233 acquires, for example, measurement data representing the state of membrane units 92-1 and 92-2 from the MBR system 9 via the data input / output unit 21. This measurement data is time-series data for a period of the same length as the processing period used in model generation.

[0127] Next, the prediction unit 233 inputs the measurement data into the learning completion model to predict the cleaning timing within a certain period (step S42), and then ends the process. In detail, the prediction unit 233 sets the output of the learning completion model obtained by inputting the measurement data from the learning completion model storage unit 232 into the learning completion model as the predicted value of the cleaning timing within a certain period.

[0128] As for the aforementioned machine learning algorithms with instructors, for example, neural networks (including deep learning) can be used, but are not limited to these; decision trees, multivariate regression, random forests, etc., are also possible, and any algorithm can be used. A neural network consists of an input layer composed of multiple neurons, an intermediate layer (hidden layer) composed of multiple neurons, and an output layer composed of multiple neurons. The intermediate layer has one or more layers.

[0129] Figure 17 This is a schematic diagram illustrating an example of a neural network. For example, if it is... Figure 17 In a three-layer neural network as shown, when multiple inputs are fed into the input layer (X1-X3), each value is multiplied by weight W1 (w11-w16) and fed into the intermediate layer (Y1-Y2). The result is then multiplied by weight W2 (w21-w26) and output from the output layer (Z1-Z3). The output varies depending on the values ​​of weights W1 and W2.

[0130] In this embodiment, the relationship between the feature quantity and the correct data is learned by adjusting the weights W1 and W2, so that the output from the output layer when the feature quantity of the teacher data, i.e. the measurement data, is input into the input layer is close to the correct data.

[0131] Furthermore, while the injection volume prediction unit 227 generates a learned completion model in the above example, it is not limited to this; the learned completion model can be performed by a learning device not shown. Additionally, the above example uses measurement data from membrane units 92-1 and 92-2, examples of ozone injection targets, but the feature quantities input to the learned completion model are not limited to measurement data; state data representing the state of the injection target can be used. Therefore, the injection volume prediction unit 227 can use the learned completion model, which predicts the injection volume at each moment of injection into the injection target within a certain period based on the state data representing the state of the injection target, and the acquired state data to predict the injection volume at each moment of injection into the injection target within a certain period.

[0132] Furthermore, in the above example, efficiency was considered when calculating the electricity usage cost as an operating cost. However, a plan could also be developed to calculate the electricity usage cost without considering efficiency and to minimize the electricity usage cost. In addition, in the above example, a plan was developed to minimize the electricity usage cost, but it is sufficient to reduce operating costs compared to the case of not storing ozone. Therefore, the search and plan could be completed if the operating cost is reduced compared to the case of not storing ozone. That is, the control unit 22a can predict the injection amount at each moment of injection into the injection target within a certain period, and use the predicted results and the electricity unit price for each time period to determine the ozone generation amount, ozone storage amount, and ozone release amount in the ozone generator 3 at each moment, so as to reduce the electricity usage cost required for ozone generation within a certain period compared to the case of not storing ozone, and use the determined results to control the ozone generator 3.

[0133] As described above, in this embodiment, ozone is stored during periods of low electricity prices and the stored ozone is used to clean membrane units 92-1 and 92-2 in the MBR system 9. This reduces operating costs compared to not storing ozone. Furthermore, by predicting ozone usage and calculating operating costs, operating costs can be minimized by determining the amount of ozone produced, regardless of the method of use.

[0134] Implementation method 4.

[0135] Figure 18 This diagram illustrates a structural example of the ozone generation system according to Embodiment 4. The ozone generation system of this embodiment can be applied to a water treatment system in the same way as Embodiment 1. Furthermore, the ozone injection unit 5 shown in the diagram injects ozone into the water treatment process 6 in the same manner as in Embodiment 1. In this embodiment, an additional function is added to a water treatment system already equipped with an ozone generator 32, thereby realizing an ozone generation system 1 identical to that of Embodiment 1. Structural elements having the same functions as in Embodiment 1 are labeled with the same reference numerals as in Embodiment 1, and repeated descriptions are omitted. Hereinafter, the differences from Embodiment 1 will be the main focus of the description.

[0136] For example, suppose an ozone generator is already installed using air as raw material, and ozone is injected from this ozone generator into the same water treatment process 6 as in Embodiment 1. In such a water treatment system, the existing ozone generator is directly used as the ozone generator 32 of Embodiment 1, and the ozone storage device 200 (shown by the dashed line) is added. Thus, the same ozone generation system 1 as in Embodiment 1 can be realized. In addition, the control device 2 can be newly installed, or it can be set as the control device 2 by changing the existing control device. The ozone storage device 200 is obtained by removing the ozone generator 32 and the switching valve 34 from the control device 2 and ozone generation unit 3 described in Embodiment 1. In addition, regarding the switching valve 34, it is assumed that some valves also exist in the existing system, so an example of using this valve is shown, but the switching valve 34 can also be included in the ozone storage device 200.

[0137] Furthermore, even existing ozone generators designed for use as dry air devices can be converted into ozone generators 32 that use oxygen as a raw material, with only minor adjustments to the power supply. While using oxygen as the raw material increases the cost compared to using air, as described in Embodiment 1, the ozone storage unit 33 allows for oxygen reuse, thus minimizing the cost increase associated with changing the type of raw material. Moreover, by changing the raw material to oxygen, ozone generation efficiency is significantly improved compared to using dry air, and a high concentration of ozone can be obtained.

[0138] In addition, when injecting ozone water into the MBR system 9 described in Embodiment 3, an ozone generation system can also be realized by adding an ozone storage device 200 to the existing system.

[0139] As described above, by adding to existing ozone generation systems that use air as raw material... Figure 18 The ozone storage device 200 shown can be modified to easily achieve a more efficient and lower-cost ozone generation system 1.

[0140] Implementation method 5.

[0141] Figure 19 This diagram illustrates a structural example of the ozone generating system according to Embodiment 5. The ozone generating system 1c of this embodiment can be applied to a water treatment system in the same way as Embodiment 1. Furthermore, although the diagram is omitted, the ozone injection unit 5 of the ozone generating system 1c injects ozone into the water treatment process 6 in the same manner as in Embodiment 1. Structural elements having the same functions as in Embodiment 1 are labeled with the same reference numerals as in Embodiment 1, and repeated descriptions are omitted. Hereinafter, the differences from Embodiment 1 will be the main focus of the description.

[0142] Figure 19In the ozone generation system 1c shown, the ozone generating unit 3b, which serves as an ozone generator, also functions as a control device 2. Embodiment 1 Figure 1 The diagram is omitted, but the ozone generator 3 is generally equipped with a control unit that controls each part. Figure 19 In the example shown, a control unit 22b is provided that has the functions of both the control unit and the control unit 22 of Embodiment 1. The control unit 22b performs the same operations as the control unit 22 of Embodiment 1, and controls the ozone generator 32, switching valves 34, 35, etc., within the ozone generator 3b. Regarding the data input / output unit 21, if it is already installed within the ozone generator 3b, the existing data input / output unit 21 within the ozone generator 3b can be reused, or a new one can be installed. Furthermore, if an existing ozone storage unit is used in an existing water treatment system, it can be added from... Figure 19 The ozone generating device after removing the ozone storage unit 33 from the ozone generating unit 3b shown is used to realize the ozone generating system 1c.

[0143] Therefore, the control unit 22b within the ozone generator, i.e., the ozone generator 3b, can perform the same operation as in Embodiment 1. Furthermore, when applied to the MBR system 9 described in Embodiment 3, the control unit 22b within the ozone generator 3b can similarly perform the same operation as in Embodiment 3.

[0144] The structure shown in the above embodiments is an example that can be combined with other known technologies. The embodiments can be combined with each other, and parts of the structure can be omitted or modified without departing from the spirit of the work.

[0145] Label Explanation

[0146] 1, 1a, 1b, 1c Ozone Generation Systems

[0147] 2.2a Control device

[0148] 3, 3a, 3b Ozone Generating Unit

[0149] 5. Ozone Injection Section

[0150] 6. Water Treatment Process

[0151] 7. Waste Ozone Treatment Department

[0152] 8. Ozone Water Manufacturing Department

[0153] 9 MBR systems

[0154] 21 Data Input / Output Section

[0155] 22, 22a, 22b Control Department

[0156] 31 Raw Material Gas Supply Department

[0157] 32, 32-1, 32-2 Ozone Generator

[0158] 33 Ozone Storage Department

[0159] 34, 35 Switching valves

[0160] 36, 37 Ozone transport pathways

[0161] 38 Oxygen Reuse Pathways

[0162] 39. Backup generator

[0163] 91-1 and 91-2 MBR units

[0164] 92-1 and 92-2 membrane units

[0165] 200 Ozone Storage Device

[0166] Planning Department 221, 221a

[0167] 222 Electricity Unit Price Storage Department

[0168] 223 Injection Volume Information Storage Unit

[0169] 224 Planned Storage Department

[0170] 225 Instruction Section

[0171] 226 Injection Volume Actual Performance Storage Department

[0172] 227 Injection Volume Prediction Department

[0173] 231 Model Generation Department

[0174] 232 Learning completes the model storage department

[0175] 233 Forecasting Department.

Claims

1. A control device for controlling an ozone generator capable of storing generated ozone and injecting ozone into an ozone injection target, characterized in that, During at least a portion of a time period when the electricity unit price is a first value, i.e., a first time period, the ozone generator produces ozone such that the ozone production amount per unit time is a first amount. During the first time period, the ozone generator injects a second amount of ozone per unit time, which is smaller than the first amount, into the injection target and stores the ozone produced that was not injected into the injection target. During at least a portion of a time period when the electricity unit price is a second value greater than the first value, i.e., a second time period, the ozone generator releases the stored ozone and injects it into the injection target. Using a real value representing the amount of ozone injected into the target by the ozone generator, the injection amount at each moment within a certain period is predicted. Using the predicted results and the electricity unit price for each time period, the amount of ozone generated, the amount of ozone stored, and the amount of ozone released by the ozone generator at each moment are determined, so as to reduce the electricity cost required for ozone generation within the certain period compared with the case of no storage. The determined results are used to control the ozone generator.

2. The control device as described in claim 1, characterized in that, As a constant independent of time period, the ozone generator injects the second amount of ozone into the injection target every unit of time.

3. The control device as described in claim 2, characterized in that, During all time periods when the electricity unit price is the second value, the ozone generator injects the stored and released ozone into the injection target at the second amount per unit time.

4. The control device as described in claim 3, characterized in that, During at least a portion of a third time period, in which the electricity price is higher than the first value and lower than the second value, the ozone generator releases the stored ozone and injects it into the injection target.

5. The control device as described in any one of claims 1 to 4, characterized in that, The efficiency, which depends on the amount of ozone produced per unit time, is used to determine the amount of ozone produced, stored, and released from the ozone generator at each moment, so as to reduce the electricity cost required for ozone production over the given period compared to the case where ozone is not stored. The first quantity is the maximum amount that the ozone generating unit can produce per unit time, and the efficiency is maximized when the amount of ozone produced per unit time is the first quantity.

6. The control device as described in any one of claims 1 to 4, characterized in that, The amount of ozone produced, stored, and released in the ozone generator at each moment is determined to minimize the electricity cost required for ozone production during the specified period.

7. The control device as described in any one of claims 1 to 4, characterized in that, It is equipped with a data input / output unit that displays at least one of the following: a screen showing the reduction in electricity usage costs compared to the case where ozone is not stored; a screen showing the amount of ozone stored for each time period; and the operating status of the ozone generator.

8. The control device as described in any one of claims 1 to 4, characterized in that, Obtain state data representing the state of the injection object, and use the learned model for predicting the injection amount at each moment of the injection into the injection object within a certain period based on the state data and the obtained state data to predict the injection amount at each moment of the injection into the injection object within the certain period.

9. An ozone generation system, characterized in that, include: An ozone generator that produces ozone; An ozone storage unit that stores the ozone generated by the ozone generator; An injection unit injects ozone into an ozone injection target, which is at least one of ozone generated by the ozone generator and ozone released from the ozone storage unit. as well as A control device uses a real-world value representing the amount of ozone injected by the ozone generator into the target to predict the injection amount at various times within a certain period. Using the predicted results and the electricity price per unit time for each period, the control device determines the amount of ozone produced, stored, and released from the ozone generator at each time point. This reduces the electricity cost required for ozone production within the specified period compared to a scenario without storage. The control device uses the determined results to control the ozone generator, the ozone storage unit, and the injection unit. Based on the instruction of the control device, the ozone generator produces ozone during at least a portion of a time period in which the electricity unit price is a first value, i.e., a first time period, such that the amount of ozone produced per unit time is a first amount. Based on the instruction of the control device, the injection unit injects a second amount of ozone, less than the first amount, into the injection target per unit time during the first time period. Based on the instructions of the control device, the ozone storage unit stores ozone generated by the ozone generator that was not injected into the target during the first time period, and releases the stored ozone during at least a portion of a second time period in which the electricity price is above the first value, i.e., the second time period. The injection unit injects ozone released from the ozone storage unit into the injection target during the second time period.

10. An ozone storage device for storing ozone produced by an ozone generator, characterized in that it comprises: An ozone storage unit that stores the ozone generated by the ozone generator; as well as A control device that controls the ozone generator, the ozone storage device, and the injection unit that injects ozone into the target of ozone injection. The control device causes the ozone generator to produce ozone during at least a portion of a time period when the electricity unit price is a first value, i.e., a first time period, such that the ozone production per unit time is a first amount. During the first time period, the ozone generator injects a second amount of ozone per unit time, which is smaller than the first amount, into the injection target, and the ozone storage unit stores ozone generated that was not injected into the injection target. During at least a portion of a time period when the electricity unit price is a second value above the first value, i.e., a second time period, the ozone storage unit releases the stored ozone, and the injection unit injects the ozone released from the ozone storage unit into the injection target. The control device uses a real value representing the amount of ozone injected into the target by the ozone generator to predict the injection amount at each moment within a certain period. Using the predicted results and the electricity unit price for each time period, it determines the amount of ozone generated, stored, and released from the ozone generator at each moment, so as to reduce the electricity cost required for ozone generation within the certain period compared to the case where no storage is performed. The determined results are used to control the ozone generator, the ozone storage unit, and the injection unit.

11. An ozone generating apparatus for generating ozone and providing the generated ozone to at least one of an ozone storage unit for storing ozone and an injection unit for injecting ozone into an ozone recipient, the ozone generating apparatus being characterized by comprising: An ozone generator that produces ozone and can supply the produced ozone to at least one of the ozone storage unit and the injection unit; as well as A control device that controls the ozone generator, the ozone storage unit, and the injection unit. The control device causes the ozone generator to produce ozone during at least a portion of a time period when the electricity unit price is a first value, i.e., a first time period, such that the ozone production per unit time is a first amount. During the first time period, the ozone generator injects a second amount of ozone per unit time, which is smaller than the first amount, into the injection target, and the ozone storage unit stores ozone generated that was not injected into the injection target. During at least a portion of a time period when the electricity unit price is a second value above the first value, i.e., a second time period, the ozone storage unit releases the stored ozone, and the injection unit injects the ozone released from the ozone storage unit into the injection target. The control device uses a real value representing the amount of ozone injected into the target by the ozone generator to predict the injection amount at each moment within a certain period. Using the predicted results and the electricity unit price for each time period, it determines the amount of ozone generated, stored, and released from the ozone generator at each moment, so as to reduce the electricity cost required for ozone generation within the certain period compared to the case where no storage is performed. The determined results are used to control the ozone generator, the ozone storage unit, and the injection unit.

12. A water treatment system, characterized in that, include: A water treatment device, which includes a membrane unit, uses membrane separation of activated sludge to purify the water to be treated. as well as An ozone generation system that injects ozone water used for cleaning the membrane unit into the membrane unit. The ozone generation system includes: An ozone generator that produces ozone; An ozone storage unit that stores the ozone generated by the ozone generator; An ozone water production unit, for the purpose of ozone injection, uses at least one of ozone generated by the ozone generator and ozone released from the ozone storage unit to generate ozone water, and injects the generated ozone water into the membrane unit; and The control unit predicts the injection amount into the membrane unit at various times within a certain period. Using the predicted results and the electricity price per unit time for each period, it determines the ozone generation, ozone storage, and ozone release at each time point. This reduces the electricity cost required for ozone generation within the specified period compared to a scenario without ozone storage. The control unit uses the determined results to control the ozone generator and the ozone storage unit. The control unit causes the ozone generator to produce ozone during at least a portion of a time period when the electricity unit price is a first value, i.e., a first time period, such that the ozone production per unit time is a first amount. During the first time period, the ozone generator injects a second amount of ozone per unit time, which is smaller than the first amount, into the injection target and stores the ozone produced that was not injected into the injection target. During at least a portion of a time period when the electricity unit price is a second value above the first value, i.e., a second time period, the ozone generator releases the stored ozone and injects it into the injection target. The control unit uses a real value representing the amount of ozone injected into the target by the ozone generator to predict the injection amount at each moment within a certain period. Using the predicted results and the electricity unit price for each time period, it determines the amount of ozone generated, the amount of ozone stored, and the amount of ozone released from the ozone generator at each moment, so as to reduce the electricity cost required for ozone generation within the certain period compared to the case where no storage is performed. The control unit uses the determined results to control the ozone generator and the ozone storage unit.

13. An ozone injection control method, which is an ozone injection control method for injecting ozone into an ozone generation system into which ozone is injected, characterized in that, Ozone is generated in at least a portion of the time period during which the electricity price is at the first value, i.e., the first time period, such that the amount of ozone generated per unit time is the first amount. During the first time period, a second amount of ozone, less than the first amount, is injected into the target per unit time. The ozone generated during the first time period was not injected into the target ozone. The stored ozone will be released during at least a portion of a second time period during which the electricity price is above the first value, i.e., during the second time period. During the second time period, the released ozone is injected into the injection target. Using actual values ​​representing the amount of ozone injected into the target, the injection amount at each moment within a certain period is predicted. Using the predicted results and the electricity price per unit time for each time period, the amount of ozone produced, the amount of ozone stored, and the amount of ozone released at each moment are determined, so that the electricity cost required for ozone production within the certain period is reduced compared to the case where no storage is carried out.

14. A computer-readable recording medium storing a computer program, characterized in that, When executed by the processor of a computer system that controls the ozone generator that stores and injects ozone into the ozone injection target, the program performs the following steps: The step of generating ozone in the ozone generator during at least a portion of the time period in which the electricity unit price is the first value, i.e., the first time period, so that the amount of ozone generated per unit time is the first amount. The step of having the ozone generator inject a second amount of ozone, which is smaller than the first amount per unit time, into the injection target during the first time period, and storing the ozone generated that was not injected into the injection target; The step of releasing the stored ozone from the ozone generator and injecting it into the injection target during at least a portion of a time period during which the electricity unit price is above the first value (i.e., the second time period); as well as Using a real value representing the amount of ozone injected into the object, the injection amount at each moment within a certain period is predicted. Using the predicted results and the electricity price per unit time for each time period, the amount of ozone produced, the amount of ozone stored, and the amount of ozone released at each moment are determined, so as to reduce the electricity cost required for ozone production within the certain period compared to the case where no storage is carried out.

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