JP7704596B2 - Moisture content control device, incineration facility system, moisture content control method, and program - Google Patents

Description

The present invention relates to a moisture content control device, an incineration facility system, a moisture content control method, and a program.

Conventionally, known technologies for stabilizing the temperature inside an incinerator that incinerates dewatered sludge in sludge treatment facilities such as sewage sludge include a technology that stabilizes the temperature inside the incinerator by controlling the moisture content of the sludge dewatered in a sludge dewatering machine (hereinafter also referred to as "dewatered sludge"), and a technology that stabilizes the temperature inside the incinerator by performing multi-input, multi-output predictive control.

For example, the following Patent Document 1 discloses a technology that adjusts the moisture content of the sludge fed into an incinerator and stabilizes the temperature inside the incinerator by controlling a moisture content adjustment mechanism to adjust the mixing ratio of dewatered sludge and dried sludge based on the sludge combustion state, which is indicated by the concentration of nitrous oxide gas.

In addition, the following Patent Document 2 discloses a technology for stabilizing the temperature inside the furnace by creating a learning model that uses a neural network to learn a model for operational control of a treatment plant equipped with a multi-input, multi-output system from various process data generated by the operation of the treatment plant, and then using the learning model to perform predictive operational control after a specified time.

Patent No. 5780806 JP 2005-242524 A

The viscosity of sludge changes with changes in sludge temperature, and the viscosity also changes with changes in sludge properties due to changes in sludge temperature. This change in sludge viscosity caused by changes in sludge temperature also changes the relationship between the shaft torque of the sludge dehydrator and the moisture content of the dehydrated sludge. For example, if a heating dehydrator that improves dehydration efficiency by heating the sludge is used as the sludge dehydrator, the properties of the sludge change due to changes in the sludge temperature, making it difficult to stably measure the moisture content. As a result, it also becomes difficult to control the temperature inside the incinerator by controlling the moisture content, as in the technology of Patent Document 1 and Patent Document 2.

In view of the above problems, the object of the present invention is to provide a moisture content control device, an incineration equipment system, a moisture content control method, and a program that can stabilize the temperature inside an incinerator by controlling the moisture content of dewatered sludge even when the properties of the sludge change in the sludge dewatering machine.

In order to solve the above-mentioned problems, a moisture content control device according to one embodiment of the present invention includes a dehydration condition information acquisition unit that acquires dehydration condition information indicating the dehydration conditions in a sludge dehydrator that dehydrates sludge; an in-furnace temperature acquisition unit that acquires the in-furnace temperature of an incinerator that incinerates the dehydrated sludge dehydrated in the sludge dehydrator; a moisture content prediction unit that predicts the moisture content of the dehydrated sludge discharged from the sludge dehydrator according to the dehydration conditions indicated by the acquired dehydration condition information using a trained model that has been machine - learned to determine the relationship between the dehydration condition information and the moisture content of the dehydrated sludge; a moisture content optimization unit that outputs the moisture content at which the in-furnace temperature stabilizes by model predictive control using at least the acquired in-furnace temperature and the predicted moisture content as inputs; and a moisture content control unit that controls the operation of the sludge dehydrator so that the moisture content of the dehydrated sludge discharged from the sludge dehydrator becomes the moisture content output from the moisture content optimization unit .

The incineration equipment system according to one aspect of the present invention is equipped with a moisture content control device.

A moisture content control method according to one aspect of the present invention includes a dehydration condition information acquisition step in which a dehydration condition information acquisition unit acquires dehydration condition information indicating dehydration conditions in a sludge dehydrator that dehydrates sludge, an in-furnace temperature acquisition step in which an incinerator temperature acquisition unit acquires an in-furnace temperature of an incinerator that incinerates the dehydrated sludge dehydrated in the sludge dehydrator, and a moisture content prediction step in which a moisture content prediction unit predicts the moisture content of the dehydrated sludge according to the dehydration conditions indicated by the acquired dehydration condition information using a trained model that has been machine-learned to understand the relationship between the dehydration condition information and the moisture content of the dehydrated sludge. The method includes a moisture content prediction process for predicting the moisture content of the dewatered sludge discharged from the sludge dewaterer ; a moisture content optimization process in which a moisture content optimization unit outputs the moisture content at which the furnace temperature stabilizes by model predictive control using at least the acquired furnace temperature and the predicted moisture content as inputs ; and a moisture content control process in which a moisture content control unit controls the operation of the sludge dewaterer so that the moisture content of the dewatered sludge discharged from the sludge dewaterer becomes the moisture content output from the moisture content optimization unit .

A program according to one embodiment of the present invention causes a computer to function as: dehydration condition information acquisition means for acquiring dehydration condition information indicating the dehydration conditions in a sludge dehydrator that dehydrates sludge; furnace temperature acquisition means for acquiring the furnace temperature of an incinerator that incinerates the dehydrated sludge dewatered in the sludge dehydrator; moisture content prediction means for predicting the moisture content of the dehydrated sludge discharged from the sludge dehydrator in accordance with the dehydration conditions indicated by the acquired dehydration condition information using a trained model that has been machine-learned to determine the relationship between the dehydration condition information and the moisture content of the dehydrated sludge; moisture content optimization means for outputting the moisture content at which the furnace temperature is stabilized by model predictive control using at least the acquired furnace temperature and the predicted moisture content as inputs ; and moisture content control means for controlling the operation of the sludge dehydrator so that the moisture content of the dehydrated sludge discharged from the sludge dehydrator becomes the moisture content output from the moisture content optimization means.

According to the present invention, even if the properties of the sludge change in the sludge dewatering machine, the temperature inside the incinerator can be stabilized by controlling the moisture content of the dewatered sludge.

1 is a diagram showing an example of the configuration of an incineration facility system according to a first embodiment. FIG. 2 is a block diagram showing an example of a functional configuration of a control panel according to the first embodiment; FIG. FIG. 2 is a diagram illustrating an example of input/output in a control panel according to the first embodiment. 5 is a flowchart showing an example of an operation of the control panel according to the first embodiment. FIG. 11 is a block diagram showing an example of a functional configuration of a control panel according to a second embodiment. FIG. 11 is a diagram illustrating an example of input/output in a control panel according to the second embodiment. 10 is a flowchart showing an example of an operation of a control panel according to a second embodiment.

The following describes in detail an embodiment of the present invention with reference to the drawings.

<<1. First embodiment>>
The first embodiment will be described with reference to FIGS. 1 to 4. FIG.

<1-1. Configuration of incineration equipment system>
First, the configuration of the incineration facility system according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of the incineration facility system according to the first embodiment.
As shown in FIG. 1, the incineration equipment system 1 includes a concentrator 10, a heating dehydrator 20, a torque sensor 21, a thermometer 22, a dehydrated sludge hopper 23, a sludge flow meter 24, an incinerator 30, a high-pressure water flow meter 31, a fuel flow meter 32, a waste heat boiler 40, a heat utilization equipment 50, a dust collector 60, a turbocharger 61, an oxygen concentration meter 62, a white smoke prevention preheater 63, a fan 64, a hot water boiler 65, a smoke treatment tower 70, and a control panel 100.

The concentrator 10 adds a coagulant to sewage sludge, such as mixed raw sludge generated from a sewage treatment plant, and thickens the resulting coagulated sludge A that is mixed and coagulated in a coagulation tank (not shown) or the like. For example, the concentrator 10 has a thickening filter screen therein, and the coagulated sludge A supplied from the concentrator 10 is thickened by separating water from it using the thickening filter screen.
The thickened sludge B discharged from the concentrator 10 is supplied to the heating dehydrator 20. A flocculant such as an inorganic flocculant, such as polyferric sulfate (PFS), or a polymer flocculant may be added to the thickened sludge B supplied to the heating dehydrator 20. The thickened sludge B may be heated using hot water K supplied from a hot water boiler 65, which will be described later.

The heating and dehydrating machine 20 is an example of a sludge dehydrator that dehydrates the concentrated sludge B supplied from the concentrator 10. The heating and dehydrating machine 20 has the function of heating and dehydrating the concentrated sludge B. The heating and dehydrating machine 20 heats the concentrated sludge B, for example, using hot water K supplied from a hot water boiler 65 described below. The heating and dehydrating machine 20 may be any of a vertical screw press, a horizontal screw press, and a rotary press, as long as it is a sludge dehydrator capable of dehydrating the concentrated sludge B.

The torque sensor 21 measures the axial torque of the heating and dehydrating machine 20. For example, the torque sensor 21 is provided so as to be able to measure the torque of a rotary drive unit (not shown) of the heating and dehydrating machine 20. The torque sensor 21 measures the torque of the rotary drive unit as the axial torque of the heating and dehydrating machine 20, and outputs the measurement result to the control panel 100.

The thermometer 22 measures the temperature (sludge temperature) of the sludge dehydrated in the heating and dehydrating machine 20. For example, the thermometer 22 is provided so as to be able to measure the temperature of the dehydrated sludge C discharged into the discharge chamber in the heating and dehydrating machine 20 after dehydration. The thermometer 22 measures the sludge temperature of the dehydrated sludge C and outputs the measurement result to the control panel 100.

The dewatered sludge hopper 23 temporarily stores the dewatered sludge C discharged from the heating dehydrator 20. The dewatered sludge C stored in the dewatered sludge hopper 23 is supplied to the incinerator 30 by, for example, a dewatered sludge supply pump (not shown).
A weighing scale (not shown) is provided in the dewatered sludge hopper 23. The weighing scale provided in the dewatered sludge hopper 23 measures the weight of the dewatered sludge hopper 23 and outputs the measurement result to the control panel 100. For example, the weighing scale measures the weight of the dewatered sludge hopper 23 before the supply of the dewatered sludge C begins, and the weight of the dewatered sludge hopper 23 in a state in which the supply of the dewatered sludge C has been temporarily stopped after the supply of the dewatered sludge C has begun. The amount of dewatered sludge C supplied to the incinerator 30 can be calculated from the difference between these weights.

The sludge flow meter 24 measures the supply amount (sludge flow rate) of dewatered sludge C supplied from the dewatered sludge hopper 23 to the incinerator 30, and outputs the measurement result to the control panel 100.

The incinerator 30 incinerates the dehydrated sludge C supplied from the heating dehydrator 20. The incinerator 30 is, for example, a supercharged fluidized bed incinerator, and the dehydrated sludge C supplied to the incinerator 30 is combusted while being fluidized together with the fluidized medium by high-temperature, high-pressure combustion air D supplied from a supercharger 61, which will be described later, to generate high-temperature combustion exhaust gas G.

The high-pressure water flow meter 31 measures the supply amount (high-pressure water flow rate) of high-pressure water E supplied to the incinerator 30 and outputs the measurement result to the control panel 100.

The fuel flow meter 32 measures the amount of fuel F (fuel flow rate) supplied to the incinerator 30 and outputs the measurement result to the control panel 100. The fuel may be, for example, auxiliary fuel for the incinerator, such as heavy oil, kerosene, city gas, or digester gas.

The combustion exhaust gas G generated in the incinerator 30 is supplied to the waste heat boiler 40, where it is cooled by heat exchange with the heat medium H supplied from the heat utilization equipment 50, and is then supplied to the dust collector 60 where dust is collected. The exhaust gas G is then supplied to the turbocharger 61 described above, which pressurizes the combustion air D supplied to the incinerator 30. Examples of the heat utilization equipment 50 include a dryer and a generator.

The combustion exhaust gas G discharged from the turbocharger 61 is supplied to the white smoke prevention preheater 63, where it is cooled by preheating the white smoke prevention air I supplied to the white smoke prevention preheater 63 by the fan 64.

The oxygen concentration meter 62 measures the oxygen concentration in the combustion exhaust gas G supplied to the white smoke prevention preheater 63 and outputs the measurement result to the control panel 100.

The combustion exhaust gas G cooled in the white smoke prevention preheater 63 is supplied to a hot water boiler 65 where it is further cooled, and then supplied to a flue gas treatment tower 70 .
The flue gas treatment tower 70 removes predetermined substances such as dust and impurities from the combustion exhaust gas G supplied from the hot water boiler 65 by spraying water supplied from the outside, and exhausts the combustion exhaust gas G from a chimney. The flue gas treatment tower 70 also supplies hot water K, which is water supplied from the outside and heated by the heat of the combustion exhaust gas G, to the hot water boiler 65. The hot water boiler 65 supplies the hot water K supplied from the flue gas treatment tower 70 to the concentrator 10 and the heating dehydrator 20.

The control panel 100 controls each part of the incineration equipment system 1. The control panel 100 is configured with a computer, etc.

<1-2. Control panel functional configuration>
The configuration of the incineration facility system 1 according to the first embodiment has been described above. Next, the functional configuration of the control panel 100 according to the first embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the functional configuration of the control panel 100 according to the first embodiment.
As shown in FIG. 2, the control panel 100 includes a communication unit 110, a dehydration condition information acquisition unit 120, a disturbance information acquisition unit 121, an oven temperature acquisition unit 122, an income/expense information acquisition unit 123, a memory unit 130, a moisture content prediction unit 140, a moisture content optimization unit 150, and a moisture content control unit 160.

(1) Communication unit 110
The communication unit 110 has a function of transmitting and receiving various information. For example, the communication unit 110 communicates with each unit of the incineration facility system 1.

(2) Dehydration condition information acquisition unit 120
The dehydration condition information acquisition unit 120 has a function of acquiring dehydration condition information. The dehydration condition information is information that indicates the conditions for dehydration in the heating dehydrator 20.
The dehydration condition information is information indicating, for example, the shaft torque of a rotary drive unit that rotates when the heating dehydrator 20 dehydrates the sludge, the sludge temperature of the dehydrated sludge, the sludge properties of the sludge, etc. The dehydration condition information acquisition unit 120 acquires at least one of the shaft torque, the sludge temperature, and the sludge properties as the dehydration condition information.

The shaft torque acquired by the dehydration condition information acquisition unit 120 is, for example, the shaft torque output from the torque sensor 21 .
The sludge temperature acquired by the dehydration condition information acquisition unit 120 is, for example, the sludge temperature output from the thermometer 22 .
The sludge properties acquired by the dewatering condition information acquisition unit 120 are, for example, the mixing ratio of primary settling sludge, excess sludge, digested sludge, etc. (hereinafter also referred to as "sludge mixing ratio"). The sludge mixing ratio is calculated, for example, from the flow rates of primary settling sludge, excess sludge, digested sludge, mechanically thickened sludge, etc. supplied to a sludge mixing tank (not shown) or the like. The flow rates of primary settling sludge, excess sludge, digested sludge, etc. are, for example, flow rates output from flow meters provided in the respective supply pipes of the primary settling sludge, excess sludge, digested sludge, etc. supplied to the sludge mixing tank. The sludge adjusted to a predetermined mixing ratio in the sludge mixing tank or the like is supplied to a coagulation tank (not shown) where it is thickened and dewatered.

The dehydration condition information is not limited to this example, and the dehydration condition information acquisition unit 120 may acquire information other than the shaft torque, sludge temperature, and sludge properties as the dehydration condition information.

(3) Disturbance information acquisition unit 121
The disturbance information acquisition unit 121 has a function of acquiring disturbance information. The disturbance information is information indicating a disturbance that affects a change in the furnace temperature.
The disturbance information is, for example, sludge temperature, sludge flow rate, high-pressure water flow rate, fuel flow rate, oxygen concentration, sludge transport time, etc. The disturbance information acquisition unit 121 acquires at least one of the sludge temperature or the sludge transport time from among the sludge temperature, sludge flow rate, high-pressure water flow rate, fuel flow rate, oxygen concentration, and sludge transport time as the disturbance information.

The sludge temperature acquired by the disturbance information acquisition unit 121 is, for example, the sludge temperature output from the thermometer 22 .
The sludge flow rate acquired by the disturbance information acquisition unit 121 is, for example, the sludge flow rate output from the sludge flow meter 24 .
The high-pressure water flow rate acquired by the disturbance information acquisition unit 121 is, for example, the high-pressure water flow rate output from the high-pressure water flow meter 31.
The fuel flow rate acquired by the disturbance information acquisition unit 121 is, for example, the fuel flow rate output from the fuel flow meter 32 .
The oxygen concentration acquired by the disturbance information acquisition unit 121 is, for example, the oxygen concentration output from the oxygen concentration meter 62 .
The sludge transport time acquired by the disturbance information acquisition unit 121 is, for example, the transport time of the dehydrated sludge from the heating dehydrator 20 to the incinerator 30. The sludge transport time is the total time of the time calculated based on the transport distance from the heating dehydrator 20 to the incinerator 30 and the residence time of the dehydrated sludge in the dehydrated sludge hopper 23. The disturbance information acquisition unit 121 may acquire the sludge transport time calculated externally, or may acquire the sludge transport time by calculating it itself.

(4) Furnace temperature acquisition unit 122
The furnace temperature acquisition unit 122 has a function of acquiring the furnace temperature. The furnace temperature is the temperature inside the incinerator 30 that incinerates the dehydrated sludge dehydrated by the heating dehydrator 20, and is, for example, the temperature inside the fluidized bed of the fluidized medium (e.g., fluid sand, etc.) (sand layer temperature), the temperature of the freeboard section, etc. In the first embodiment, the furnace temperature acquired by the furnace temperature acquisition unit 122 includes a set value and a measured value.

The set value of the furnace temperature is, for example, the temperature inside the furnace set by a control device of the incinerator 30 or the like provided in the incinerator 30. The furnace temperature acquisition unit 122 acquires the set value of the furnace temperature from the control device or the like. For example, the furnace temperature acquisition unit 122 acquires the set value of the furnace temperature as the furnace temperature used by the moisture content optimization unit 150 when the moisture content optimization unit 150 described below optimizes the moisture content.

The measured value of the furnace temperature is, for example, the temperature inside the furnace measured by a sensor device or the like that is installed so as to be able to measure the temperature inside the furnace of the incinerator 30. The furnace temperature acquisition unit 122 acquires the measured value of the furnace temperature from the sensor device or the like. For example, the furnace temperature acquisition unit 122 acquires as the measured value the furnace temperature of the incinerator 30 that is measured after the heating and dehydrating machine 20 is controlled based on the moisture content optimized by the moisture content optimization unit 150 described below. The measured value of the furnace temperature is used to update (feedback control) the prediction model in the moisture content optimization unit 150.

(5) Income and expenditure information acquisition unit 123
The balance information acquisition unit 123 has a function of acquiring balance information. The balance information is information indicating the material balance and the heat balance in the dehydration of sludge by the heating dehydrator 20. Specifically, the balance information acquisition unit 123 acquires, as balance information, the amount of combustion exhaust gas, the amount of dry gas, the amount of moisture brought in by the combustion air, the amount of moisture generated during sludge combustion, and the amount of moisture generated during auxiliary fuel combustion.

(6) Storage unit 130
The storage unit 130 has a function of storing various information. The storage unit 130 is configured by a storage medium, for example, a hard disk drive (HDD), a network attached storage (NAS), a solid state drive (SSD), a flash memory, an electrically erasable programmable read only memory (EEPROM), a random access read/write memory (RAM), a read only memory (ROM), or any combination of these storage media.
The memory unit 130 stores, for example, a trained model used by the moisture content prediction unit 140 described below, a prediction model used by the moisture content optimization unit 150, and the like.

(7) Moisture content prediction unit 140
The moisture content prediction unit 140 has a function of predicting the moisture content of the dewatered sludge. For example, the moisture content prediction unit 140 predicts the moisture content of the dewatered sludge dewatered under the dewatering conditions based on the dewatering condition information acquired by the dewatering condition information acquisition unit 120.
In the first embodiment, the moisture content prediction unit 140 acquires the moisture content of the dewatered sludge using a model capable of outputting the moisture content of the dewatered sludge. For example, the moisture content prediction unit 140 predicts the moisture content of the dewatered sludge using a trained model. The trained model is a trained model that has been machine-learned to learn the relationship between the dewatering condition information and the moisture content of the dewatered sludge. In other words, when dewatering condition information is input as input data, the trained model is capable of outputting the moisture content of the dewatered sludge as output data.
Specifically, the moisture content prediction unit 140 inputs the dewatering condition information acquired by the dewatering condition information acquisition unit 120 as input data into the trained model, and predicts the moisture content output as the moisture content of the dewatered sludge.

Any machine learning method may be applied to the trained model used by the moisture content prediction unit 140. Examples of the any machine learning method include linear regression, support vector machine regression, Gaussian process regression, decision tree, and neural network.
In addition, the model capable of outputting the moisture content of the dewatered sludge is not limited to a machine-learned trained model. For example, the model capable of outputting the moisture content of the dewatered sludge may be a regression model, a regression formula, a classification model, or the like.
The moisture content prediction unit 140 may also predict the moisture content of the dewatered sludge based on the income and expenditure information acquired by the income and expenditure information acquisition unit 123. For example, the moisture content prediction based on the income and expenditure information is calculated by further subtracting the amount of moisture generated during sludge combustion from the value excluding the amount of dry gas in the combustion gas and exhaust gas. Specifically, the sludge moisture content is calculated using the following formula.
Sludge moisture content = (amount of combustion exhaust gas - amount of dry gas - amount of moisture brought in by combustion air - amount of moisture generated during sludge combustion - amount of moisture generated during auxiliary fuel combustion) / amount of input sludge

(8) Moisture content optimization section 150
The moisture content optimization unit 150 has a function of optimizing the moisture content predicted by the moisture content prediction unit 140. For example, the moisture content optimization unit 150 optimizes the moisture content (predicted value) predicted by the moisture content prediction unit 140 by model predictive control (MPC) based on at least the furnace temperature (set value) acquired by the furnace temperature acquisition unit 122. The moisture content optimization unit 150 performs model predictive control using an optimizer and a predictive model. The predictive model simulates a model of incineration of dewatered sludge in the incinerator 30. Specifically, in the model predictive control, the optimizer and the predictive model predict a future response so as to achieve the input furnace temperature (set value), and an optimal moisture content (set value) is output.

The moisture content optimization unit 150 may also use disturbance information acquired by the disturbance information acquisition unit 121 when optimizing the moisture content (predicted value). That is, the moisture content optimization unit 150 may optimize the moisture content (predicted value) by model predictive control based on at least the furnace temperature (set value) and the disturbance information. This allows the moisture content optimization unit 150 to predict future responses that take into account disturbances from the optimizer and the prediction model using model predictive control, thereby outputting a more optimal moisture content (set value). That is, by also using disturbance information, the moisture content optimization unit 150 can optimize the moisture content (predicted value) with higher accuracy than optimization using only the furnace temperature (set value).

In addition, the moisture content optimization unit 150 predicts the future including disturbances by using model predictive control, so that the temperature inside the furnace is stabilized, and it becomes possible to operate the incinerator 30 under conditions where the generation and emission of nitrous oxide, which is said to be one of the ozone-depleting gases that destroy the ozone layer, is low. It also becomes possible to stably maintain a state in which the sludge burns stably (self-combustion) without using auxiliary fuel.
In addition, even when it is necessary to maintain the furnace temperature by using auxiliary fuel to support combustion, stabilizing the furnace temperature makes it possible to reduce the amount of auxiliary fuel such as heavy oil used, thereby reducing costs and carbon dioxide emissions.

The moisture content optimization unit 150 updates (feedback control) the prediction model used in the model prediction control based on the results of control based on the output moisture content (set value). For example, the moisture content optimization unit 150 updates the prediction model based on the internal temperature (measured value) of the incinerator 30 measured after the heating and dehydrating machine 20 is controlled based on the moisture content (set value). This enables the moisture content optimization unit 150 to improve the accuracy of predictions made by the prediction model, and also improve the accuracy of optimization of the moisture content (predicted value).

(9) Moisture content control section 160
The moisture content control unit 160 has a function of controlling the moisture content of the dewatered sludge discharged from the heating and dehydrating machine 20. For example, the moisture content control unit 160 controls the operation of the heating and dehydrating machine 20 so that the moisture content becomes the moisture content (set value) output from the moisture content optimization unit 150. As an example, the moisture content control unit 160 controls the moisture content of the dewatered sludge by manipulating the amount of flocculant added to the concentrated sludge supplied to the heating and dehydrating machine 20.

<1-3. Input/output on the control panel>
The functional configuration of the control panel 100 according to the first embodiment has been described above. Next, input/output in the control panel 100 according to the first embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of input/output in the control panel 100 according to the first embodiment. Fig. 3 shows an example in which the shaft torque, sludge temperature, and sludge mixing ratio are obtained as dewatering condition information, and the furnace temperature (set value) and disturbance information are used to optimize the moisture content (predicted value).

3, first, the shaft torque, sludge temperature, and sludge mixing ratio acquired by the dewatering condition information acquisition unit 120, and the balance information acquired by the balance information acquisition unit 123 are input to the moisture content prediction unit 140 of the control panel 100. The shaft torque and the sludge temperature are measured by the heating dehydrator 20.
The moisture content prediction unit 140 outputs the moisture content (predicted value) of the dewatered sludge based on the input dewatering condition information. The moisture content (predicted value) output from the moisture content prediction unit 140 is input to the moisture content optimization unit 150.

In addition to the moisture content (predicted value), the moisture content optimization unit 150 also receives disturbance information acquired by the disturbance information acquisition unit 121 and the furnace temperature (set value) acquired by the furnace temperature acquisition unit 122.
The moisture content optimization unit 150 outputs the moisture content (set value) based on the input moisture content (predicted value), disturbance information, and furnace temperature (set value). The moisture content (set value) output from the moisture content optimization unit 150 is input to the moisture content control unit 160.

The moisture content control unit 160 outputs an operation amount for controlling the moisture content of the dewatered sludge in the heating and dehydrating machine 20 based on the input moisture content (set value). The operation amount output from the moisture content control unit 160 is input to the heating and dehydrating machine 20 or equipment related to the heating and dehydrating machine 20.

The heating and dehydrating machine 20 discharges dehydrated sludge that has been dehydrated based on the input operation amount. The dehydrated sludge discharged from the heating and dehydrating machine 20 is supplied to the incinerator 30.
The incinerator 30 incinerates the supplied dewatered sludge and outputs the incinerator temperature (measured value) measured during or after incineration. The incinerator temperature (measured value) output from the incinerator 30 is input to the moisture content optimization unit 150.
The moisture content optimization unit 150 updates the prediction model based on the input furnace temperature (measured value).

<1-4. Control panel operation>
The input and output in the control panel 100 according to the first embodiment have been described above. Next, the operation of the control panel 100 according to the first embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing an example of the operation of the control panel 100 according to the first embodiment. Fig. 4 shows an example in which the shaft torque, sludge temperature, and sludge mixing ratio are obtained as dewatering condition information, and the furnace temperature (set value) and disturbance information are used to optimize the moisture content (predicted value).

As shown in FIG. 4, first, the dehydration condition information acquisition unit 120 of the control panel 100 acquires the dehydration condition information (step S101). Specifically, the dehydration condition information acquisition unit 120 acquires the shaft torque output from the torque sensor 21, the sludge temperature output from the thermometer 22, the sludge flow rate output from the sludge flowmeter 24, and the balance information output from the balance information acquisition unit 123 as the dehydration condition information.

Next, the moisture content prediction unit 140 of the control panel 100 predicts the moisture content of the dewatered sludge (step S102). Specifically, the moisture content prediction unit 140 predicts the moisture content (predicted value) of the dewatered sludge based on the moisture content output from the trained model using the dewatering condition information acquired by the dewatering condition information acquisition unit 120 as input data.

Next, the disturbance information acquisition unit 121 of the control panel 100 acquires disturbance information (step S103). Specifically, the disturbance information acquisition unit 121 acquires, as disturbance information, the sludge temperature output from the thermometer 22, the sludge flow rate output from the sludge flowmeter 24, the high-pressure water flow rate output from the high-pressure water flowmeter 31, the fuel flow rate output from the fuel flowmeter 32, the oxygen concentration output from the oxygen concentration meter 62, the sludge transport time calculated by the disturbance information acquisition unit 121, and the like.

Next, the furnace temperature acquisition unit 122 of the control panel 100 acquires the furnace temperature (step S104). Specifically, the furnace temperature acquisition unit 122 acquires the furnace temperature (set value) output from the control device of the incinerator 30 provided in the incinerator 30.

Next, the moisture content optimization unit 150 optimizes the moisture content (predicted value) (step S105). Specifically, the moisture content optimization unit 150 optimizes the moisture content (predicted value) predicted by the moisture content prediction unit 140 using model predictive control based on the disturbance information acquired by the disturbance information acquisition unit 121 and the furnace temperature (set value) acquired by the furnace temperature acquisition unit 122, and outputs the moisture content (set value).

Next, the moisture content control unit 160 controls the moisture content (step S106). Specifically, the moisture content control unit 160 controls the dehydration of the sludge in the heating dehydrator 20 so that the dehydrated sludge has the moisture content (set value) optimized by the moisture content optimization unit 150, and then ends the process.

As described above, the control panel 100 (moisture content control device) according to the first embodiment includes a dehydration condition information acquisition unit 120, an oven temperature acquisition unit 122, a moisture content prediction unit 140, and a moisture content optimization unit 150.
The dehydration condition information acquisition unit 120 acquires dehydration condition information indicating the dehydration conditions in the heating dehydrator 20 that dehydrates the sludge. The furnace temperature acquisition unit 122 acquires the furnace temperature (set value) of the incinerator 30 that incinerates the dehydrated sludge dehydrated in the heating dehydrator 20. The moisture content prediction unit 140 predicts the moisture content (predicted value) of the dehydrated sludge using a trained model that has been machine-learned to learn the relationship between the dehydration condition information and the moisture content of the dehydrated sludge. The moisture content optimization unit 150 optimizes the predicted moisture content (predicted value) by model predictive control based on at least the acquired furnace temperature (set value).

With this configuration, when the dehydration conditions of the sludge in the heating dehydrator 20 (e.g., sludge temperature) change, the control panel 100 according to the first embodiment can predict the moisture content of the dehydrated sludge discharged according to the dehydration conditions, and optimize the moisture content according to the incineration conditions of the incinerator 30 (e.g., furnace temperature). In other words, even if it is difficult to stably measure the moisture content of the dehydrated sludge due to changes in the sludge temperature, the control panel 100 can stably control the furnace temperature of the incinerator by controlling the moisture content of the dehydrated sludge based on the predicted and optimized moisture content.

Therefore, the control panel 100 according to the first embodiment makes it possible to stabilize the temperature inside the incinerator by controlling the moisture content of the dewatered sludge even if the properties of the sludge change in the sludge dewatering machine.

<<2. Second embodiment>>
The first embodiment has been described above. Next, a second embodiment will be described with reference to Fig. 5 to Fig. 7. In the second embodiment, an example will be described in which a moisture content (calculated value) calculated based on balance information, which is information on material balance and heat balance, is also used to optimize the moisture content (predicted value).

<2-1. Configuration of incineration equipment system>
The configuration of the incineration facility system according to the second embodiment is similar to the configuration of the incineration facility system 1 according to the first embodiment, so duplicated explanations will be omitted.

<2-2. Functional configuration of the control panel>
The configuration of the incineration facility system according to the second embodiment has been described above. Next, the functional configuration of the control panel 100a according to the second embodiment will be described with reference to Fig. 5. Fig. 5 is a block diagram showing an example of the functional configuration of the control panel 100a according to the second embodiment.
As shown in FIG. 5, the control panel 100a includes a communication unit 110, a dehydration condition information acquisition unit 120, a disturbance information acquisition unit 121, an oven temperature acquisition unit 122, an income/expense information acquisition unit 123, a memory unit 130, a moisture content prediction unit 140, a moisture content calculation unit 141, a moisture content optimization unit 150a, and a moisture content control unit 160.

(1) Communication unit 110
The functions of the communication unit 110 according to the second embodiment are similar to those of the communication unit 110 according to the first embodiment, and therefore a duplicated description will be omitted.

(2) Dehydration condition information acquisition unit 120
The functions of the dehydration condition information acquisition unit 120 according to the second embodiment are similar to those of the dehydration condition information acquisition unit 120 according to the first embodiment, and therefore overlapping descriptions will be omitted.

(3) Disturbance information acquisition unit 121
The function of the disturbance information acquisition unit 121 according to the second embodiment is similar to the function of the disturbance information acquisition unit 121 according to the first embodiment, so a duplicated description will be omitted.

(4) Furnace temperature acquisition section 122
The function of the furnace temperature acquisition unit 122 according to the second embodiment is similar to the function of the furnace temperature acquisition unit 122 according to the first embodiment, so a duplicated description will be omitted.

(5) Income and expenditure information acquisition unit 123
The function of the income and expenditure information acquiring unit 123 according to the second embodiment is similar to the function of the income and expenditure information acquiring unit 123 according to the first embodiment, and therefore a duplicated description will be omitted.

(6) Storage unit 130
The functions of the storage unit 130 according to the second embodiment are similar to those of the storage unit 130 according to the first embodiment, and therefore a duplicated description will be omitted.

(7) Moisture content prediction unit 140
The function of the moisture content predicting unit 140 according to the second embodiment is similar to the function of the moisture content predicting unit 140 according to the first embodiment, so a duplicated description will be omitted.

(8) Moisture content calculation unit 141
The moisture content calculation unit 141 has a function of calculating the moisture content. For example, the moisture content calculation unit 141 calculates the moisture content of the dewatered sludge based on the income/expenditure information acquired by the income/expenditure information acquisition unit 123. For example, the moisture content calculation unit 141 calculates the sludge moisture content by further subtracting the amount of moisture generated during sludge combustion from a value obtained by subtracting the amount of dry gas in the combustion gas and exhaust gas. Specifically, the moisture content calculation unit 141 calculates the sludge moisture content from the following formula.
Sludge moisture content = (amount of combustion exhaust gas - amount of dry gas - amount of moisture brought in by combustion air - amount of moisture generated during sludge combustion - amount of moisture generated during auxiliary fuel combustion) / amount of input sludge

(9) Moisture Content Optimization Unit 150a
The function of the moisture content optimization unit 150a according to the second embodiment is similar to the function of the moisture content optimization unit 150 according to the first embodiment, so a duplicated description will be omitted.
The moisture content optimization unit 150a optimizes the moisture content (predicted value) using the moisture content (calculated value).

For example, the moisture content optimization unit 150a optimizes the moisture content (predicted value) predicted by the moisture content prediction unit 140 based on at least the furnace temperature (set value) acquired by the furnace temperature acquisition unit 122 and the moisture content (calculated value) calculated by the moisture content calculation unit 141 using model predictive control.
In addition, the moisture content optimization unit 150a may optimize the moisture content (predicted value) by model predictive control based on at least the furnace temperature (set value), disturbance information, and the moisture content (calculated value).
In this way, the moisture content optimization unit 150a predicts future responses using model predictive control, taking into account the moisture content (calculated value) obtained by the optimizer and the predictive model, and can output a more optimal moisture content (set value) compared to the first embodiment, in which the moisture content (calculated value) is not used.

(10) Moisture content control section 160
The function of the moisture content control unit 160 according to the second embodiment is similar to the function of the moisture content control unit 160 according to the first embodiment, so a duplicated description will be omitted.

<2-3. Input/output on the control panel>
The functional configuration of the control panel 100a according to the second embodiment has been described above. Next, inputs and outputs in the control panel 100a according to the second embodiment will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of inputs and outputs in the control panel 100a according to the second embodiment. Fig. 6 shows an example in which the shaft torque, sludge temperature, and sludge mixing ratio are obtained as dewatering condition information, and the furnace temperature (set value), disturbance information, and moisture content (calculated value) are used to optimize the moisture content (predicted value).

6, first, the shaft torque, sludge temperature, and sludge mixing ratio acquired by the dewatering condition information acquisition unit 120 are input as dewatering condition information to the moisture content prediction unit 140 of the control panel 100a. The shaft torque and the sludge temperature are values measured by the heating dewatering machine 20.
The moisture content prediction unit 140 outputs the moisture content (predicted value) of the dewatered sludge based on the input dewatering condition information. The moisture content (predicted value) output from the moisture content prediction unit 140 is input to the moisture content optimization unit 150a.

The moisture content calculation unit 141 receives the balance information acquired by the balance information acquisition unit 123 .
The moisture content calculation unit 141 outputs the moisture content (calculated value) of the dewatered sludge based on the input balance information. The moisture content (calculated value) output from the moisture content calculation unit 141 is input to the moisture content optimization unit 150a.

In addition to the moisture content (predicted value) and the moisture content (calculated value), the moisture content optimization unit 150a also receives disturbance information acquired by the disturbance information acquisition unit 121 and the furnace temperature (set value) acquired by the furnace temperature acquisition unit 122.
The moisture content optimization unit 150a outputs a moisture content (set value) based on the input moisture content (predicted value), moisture content (calculated value), disturbance information, and furnace temperature (set value). The moisture content (set value) output from the moisture content optimization unit 150a is input to the moisture content control unit 160.

The moisture content control unit 160 outputs an operation amount for controlling dehydration in the heating and dehydrating machine 20 based on the input moisture content (set value). The operation amount output from the moisture content control unit 160 is input to the heating and dehydrating machine 20 or a device related to the heating and dehydrating machine 20.

The heating and dehydrating machine 20 discharges dehydrated sludge that has been dehydrated based on the input operation amount. The dehydrated sludge discharged from the heating and dehydrating machine 20 is supplied to the incinerator 30.
The incinerator 30 incinerates the supplied dewatered sludge and outputs the incinerator temperature (measured value) measured after incineration. The incinerator temperature (measured value) output from the incinerator 30 is input to the moisture content optimization unit 150a.
The moisture content optimization unit 150a updates the prediction model based on the input furnace temperature (measured value).

<2-4. Operation of the control panel>
The inputs and outputs in the control panel 100a according to the second embodiment have been described above. Next, the operation of the control panel 100a according to the second embodiment will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of the operation of the control panel 100a according to the second embodiment. Fig. 7 shows an example in which the shaft torque, sludge temperature, and sludge mixing ratio are obtained as dewatering condition information, and the furnace temperature (set value), disturbance information, and moisture content (calculated value) are used to optimize the moisture content (predicted value).

The processing of steps S201 and S202 shown in FIG. 7 is similar to the processing of steps S101 and S102 described with reference to FIG. 4, so duplicated explanations will be omitted.

After processing in step S202, the income/expense information acquisition unit 123 of the control panel 100a acquires income/expense information (step S203).

Next, the moisture content calculation unit 141 calculates the moisture content of the dewatered sludge (step S204). Specifically, the moisture content calculation unit 141 calculates the moisture content (calculated value) based on the income/expense information acquired by the income/expense information acquisition unit 123.

The processing of steps S205 and S206 shown in FIG. 7 is similar to the processing of steps S103 and S104 described with reference to FIG. 4, so duplicated explanations will be omitted.

After the processing of step S206, the moisture content optimization unit 150a of the control panel 100a optimizes the moisture content (predicted value) (step S207). Specifically, the moisture content optimization unit 150a optimizes the moisture content (predicted value) predicted by the moisture content prediction unit 140 using model predictive control based on the disturbance information acquired by the disturbance information acquisition unit 121, the furnace temperature (set value) acquired by the furnace temperature acquisition unit 122, and the moisture content (calculated value) calculated by the moisture content calculation unit 141, and outputs the moisture content (set value).

The process of step S208 shown in FIG. 7 is similar to the process of step S106 described with reference to FIG. 4, so a duplicated description will be omitted.

As described above, the control panel 100a (moisture content control device) according to the second embodiment includes a dehydration condition information acquisition unit 120, an oven temperature acquisition unit 122, a moisture content prediction unit 140, and a moisture content optimization unit 150a.
The dehydration condition information acquisition unit 120 acquires dehydration condition information indicating the dehydration conditions in the heating dehydrator 20 that dehydrates the sludge. The furnace temperature acquisition unit 122 acquires the furnace temperature (set value) of the incinerator 30 that incinerates the dehydrated sludge dehydrated by the heating dehydrator 20. The moisture content prediction unit 140 predicts the moisture content (predicted value) of the dehydrated sludge using a trained model that has been machine-learned to learn the relationship between the dehydration condition information and the moisture content of the dehydrated sludge. The moisture content optimization unit 150a optimizes the predicted moisture content (predicted value) by model predictive control based on at least the acquired furnace temperature (set value).

With this configuration, the control panel 100a according to the first embodiment can predict the moisture content of the dewatered sludge discharged according to the dewatering conditions (e.g., sludge temperature) when the dewatering conditions of the sludge in the heating dehydrator 20 change, and can optimize the moisture content according to the incineration conditions of the incinerator 30 (e.g., the temperature inside the furnace). In other words, even if it is difficult to stably measure the moisture content of the dewatered sludge due to changes in the sludge temperature, the control panel 100a can stably control the temperature inside the incinerator by controlling the moisture content of the dewatered sludge based on the predicted and optimized moisture content.

Therefore, the control panel 100a according to the second embodiment makes it possible to stabilize the temperature inside the incinerator by controlling the moisture content of the dewatered sludge even if the properties of the sludge change in the sludge dewatering machine.

The control panel 100a according to the second embodiment further includes an income/expense information acquisition unit 123 that acquires income/expense information, and a moisture content calculation unit 141 that calculates the moisture content of the dewatered sludge based on the income/expense information. The moisture content optimization unit 150a also uses the moisture content (calculated value) calculated by the moisture content calculation unit 141 to optimize the moisture content (predicted value) predicted by the moisture content prediction unit 140 through model predictive control.
As a result, the moisture content optimization unit 150a can predict future responses using model predictive control, taking into account the moisture content (calculated value) using the optimizer and the predictive model, and can output a more optimal moisture content (set value) compared to the first embodiment, which does not use the moisture content (calculated value).

The above describes an embodiment of the present invention. Note that a part or all of the control panel 100 (moisture content control device) in the above embodiment may be realized by a computer. In that case, a program for realizing this function may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read into a computer system and executed to realize the function. Note that the term "computer system" here includes hardware such as an OS and peripheral devices. Furthermore, the term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs, and CD-ROMs, and storage devices such as hard disks built into a computer system. Furthermore, the term "computer-readable recording medium" may include a medium that dynamically holds a program for a short period of time, such as a communication line when a program is transmitted via a network such as the Internet or a communication line such as a telephone line, and a medium that holds a program for a certain period of time, such as a volatile memory inside a computer system that is a server or client in that case. Furthermore, the above program may be a program for realizing a part of the above-mentioned function, or may be a program that can realize the above-mentioned function in combination with a program already recorded in the computer system, or may be a program that is realized using a programmable logic device such as an FPGA (Field Programmable Gate Array).

The above describes in detail an embodiment of the present invention with reference to the drawings, but the specific configuration is not limited to the above, and various design changes can be made without departing from the spirit of the present invention.

1...Incineration equipment system, 10...Concentrator, 20...Heating dehydrator, 21...Torque sensor, 22...Thermo thermometer, 23...Dehydrated sludge hopper, 24...Sludge flow meter, 30...Incinerator, 31...High pressure water flow meter, 32...Fuel flow meter, 40...Waste heat boiler, 60...Dust collector, 61...Turbocharger, 62...Oxygen concentration meter, 63...White smoke prevention preheater, 64...Fan, 65...Hot water boiler, 70...Flue gas treatment tower, 100, 100a...Control panel, 110...Communication signal unit, 120...dehydration condition information acquisition unit, 121...disturbance information acquisition unit, 122...furnace temperature acquisition unit, 123...income and expenditure information acquisition unit, 130...storage unit, 140...moisture content prediction unit, 141...moisture content calculation unit, 150, 150a...moisture content optimization unit, 160...moisture content control unit, A...flocculated sludge, B...concentrated sludge, C...dehydrated sludge, D...combustion air, E...high-pressure water, F...fuel, G...combustion exhaust gas, H...heat medium, I...air for preventing white smoke, K...hot water

Claims (9)

a dehydration condition information acquisition unit that acquires dehydration condition information indicating dehydration conditions in a sludge dehydrator that dehydrates sludge;
an incinerator temperature acquisition unit for acquiring an incinerator temperature of an incinerator that incinerates the dehydrated sludge dewatered by the sludge dewaterer;
a moisture content prediction unit that predicts the moisture content of the dewatered sludge discharged from the sludge dewaterer according to the dewatering conditions indicated by the acquired dewatering condition information, using a trained model that has been machine-learned to understand the relationship between the dewatering condition information and the moisture content of the dewatered sludge;
a moisture content optimization unit that outputs a moisture content at which the furnace temperature is stabilized by a model predictive control using at least the acquired furnace temperature and the predicted moisture content as inputs ;
a moisture content control unit that controls an operation of the sludge dewatering machine so that the moisture content of the dewatered sludge discharged from the sludge dewatering machine becomes the moisture content output from the moisture content optimization unit;
A moisture content control device comprising: a disturbance information acquisition unit for acquiring disturbance information indicating a disturbance that affects a change in the furnace temperature;
Further equipped with
the moisture content optimization unit outputs a moisture content at which the furnace temperature is stabilized by a model predictive control using at least the acquired furnace temperature and disturbance information and the predicted moisture content as inputs .
The moisture content control device according to claim 1 . The disturbance information acquisition unit acquires, as the disturbance information, at least one of a sludge temperature of the dewatered sludge or a sludge transport time during which the dewatered sludge is transported from the sludge dewaterer to the incinerator.
The moisture content control device according to claim 2 . The dehydration condition information acquisition unit acquires, as the dehydration condition information, at least one of a shaft torque of a rotation drive unit that rotates when the sludge dehydrator dehydrates the sludge, a sludge temperature of the dehydrated sludge, or a sludge property of the sludge.
The moisture content control device according to any one of claims 1 to 3. a balance information acquiring unit that acquires balance information regarding material balance and heat balance during dehydration of the sludge by the sludge dehydrator;
a moisture content calculation unit that calculates the moisture content of the dewatered sludge based on the acquired balance information;
Further equipped with
The moisture content optimization unit outputs a moisture content at which the furnace temperature is stabilized by a model predictive control using at least the acquired furnace temperature, the calculated moisture content, and the predicted moisture content as inputs.
The moisture content control device according to any one of claims 1 to 4. The furnace temperature acquisition unit acquires a furnace temperature of the incinerator measured after the sludge dewatering machine is controlled based on the moisture content output from the moisture content optimization unit,
The moisture content optimization unit updates a prediction model used in the model predictive control based on the acquired furnace temperature.
The moisture content control device according to any one of claims 1 to 5. An incineration facility system equipped with a moisture content control device according to any one of claims 1 to 6. a dehydration condition information acquisition step in which a dehydration condition information acquisition unit acquires dehydration condition information indicating dehydration conditions in a sludge dehydrator that dehydrates sludge;
an incinerator temperature acquisition step in which an incinerator temperature acquisition unit acquires an incinerator temperature of an incinerator that incinerates the dewatered sludge dewatered by the sludge dewatering machine;
a moisture content prediction process in which a moisture content prediction unit predicts the moisture content of the dewatered sludge discharged from the sludge dewaterer according to the dewatering conditions indicated by the acquired dewatering condition information, using a trained model that has been machine-learned to understand the relationship between the dewatering condition information and the moisture content of the dewatered sludge;
a moisture content optimization step in which a moisture content optimization unit outputs a moisture content at which the furnace temperature is stabilized by a model predictive control using at least the acquired furnace temperature and the predicted moisture content as inputs ;
a moisture content control step of controlling the operation of the sludge dewatering machine by a moisture content control unit so that the moisture content of the dewatered sludge discharged from the sludge dewatering machine becomes the moisture content output from the moisture content optimization unit;
A moisture content control method comprising: Computer,
a dehydration condition information acquiring means for acquiring dehydration condition information indicating dehydration conditions in a sludge dehydrator that dehydrates sludge;
an incinerator temperature acquisition means for acquiring an incinerator temperature of an incinerator for incinerating the dewatered sludge dewatered by the sludge dewatering machine;
a moisture content prediction means for predicting the moisture content of the dewatered sludge discharged from the sludge dewaterer according to the dewatering conditions indicated by the acquired dewatering condition information, using a trained model that has been machine-learned to understand the relationship between the dewatering condition information and the moisture content of the dewatered sludge;
a moisture content optimizing means for outputting a moisture content at which the furnace temperature is stabilized by a model predictive control using at least the acquired furnace temperature and the predicted moisture content as inputs ;
a moisture content control means for controlling the operation of the sludge dewatering machine so that the moisture content of the dewatered sludge discharged from the sludge dewatering machine becomes the moisture content output from the moisture content optimization means;
A program to function as a

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