JP6779185B2 - Water quality control equipment, water treatment systems, heat plants, power plants, and water quality control methods - Google Patents

Description

The present invention relates to a water quality control device, a water treatment system, a heat plant, a power plant, and a water quality control method.

Patent Document 1 discloses a technique of measuring the water quality parameters of cooling water and boiler water and displaying the water treatment status and countermeasures for the measured water quality parameters.

JP-A-2015-205237

By the way, in a thermal plant that is cooled by cooling water (for example, a gas turbine plant, a GTCC (Gas Turbine Combined Cycle) plant, a nuclear power plant, a geothermal plant, etc.), the temperature differs depending on where the cooling water flows, and scaling is performed according to the temperature. , Corrosion, fouling and other risks are different.

On the other hand, the locations where cooling water can be sampled differ depending on the design of the plant, and it cannot always be said that cooling water at high-risk locations can be obtained depending on the plant.

An object of the present invention is a water quality control device, a water treatment system, a thermal plant, a power generation plant, and a water treatment plant capable of appropriately treating the cooling water even when the cooling water sampling location and the high-risk location are different. The purpose is to provide a water quality control method.

According to the first aspect of the present invention, the water quality control device includes a measurement result acquisition unit that acquires a measurement value related to the water quality of cooling water at a specific location of the heat plant, a past operation history of the heat plant, and the heat. A load model that is learned based on the environmental data of the plant and outputs information related to the load of the thermal plant after a predetermined time by inputting the environmental data, and the heat by inputting the environmental data into the load model. The control parameters of the water temperature information acquisition unit that acquires the information related to the water temperature at the target location different from the specific location of the plant and the water treatment apparatus that processes the cooling water based on the information related to the water temperature and the measured value. It is provided with a parameter determination unit for determining.

According to the second aspect of the present invention, the water quality control device according to the first aspect specifies the target water quality for specifying the water quality of the cooling water at the target location based on the information related to the water temperature and the measured value. Further, the parameter determination unit may determine the control parameter based on the water quality of the target location.

According to the third aspect of the present invention, in the water quality control device according to the second aspect, the target water quality specifying unit is set after a predetermined time of the target location based on the information related to the water temperature and the measured value. It may specify the water quality of the cooling water.

According to the fourth aspect of the present invention, in the water quality control device according to the second or third aspect, the target water quality specifying unit is the past operation history of the thermal plant and the water quality of the cooling water at the target location. Further provided with a water quality model that outputs the water quality of the cooling water at the target location by inputting the water quality of the cooling water at the specific location and the information related to the water temperature at the target location, the target water quality is further provided. The specific unit may specify the water quality of the cooling water at the target location by inputting the water quality of the cooling water at the specific location and the water temperature of the target location into the water quality model.

According to the fifth aspect of the present invention, the water quality control device according to the second or third aspect changes the temperature of the cooling water sampled from the specific location based on the information related to the water temperature. The temperature device is further provided with a temperature control instruction unit that outputs a temperature control instruction for adjusting the temperature to the water temperature of the target location, and the measurement result acquisition unit relates to the water quality of the cooling water that has been temperature-controlled by the temperature control device. the acquired measured values, the target quality specifying unit, the measurement result acquisition unit is based on the measurement values obtained may be also of a that identifies the quality of the cooling water in the target site.

According to the sixth aspect of the present invention, in the water quality control device according to any one of the first to fifth aspects, the parameter determining unit has the water quality of the cooling water at the specific location and the water quality of the target location. The control parameters may be determined based on the quality of the cooling water.

According to a seventh aspect of the present invention, the water quality control device according to any one of the first to sixth aspects relates to the thermal plant based on the water quality of the cooling water at the target location at the specific location. The risk estimation unit for estimating the height of risk is further provided, and the parameter determination unit may determine the control parameter based on the height of risk estimated by the risk estimation unit.

According to the eighth aspect of the present invention, in the water quality control device according to any one of the first to seventh aspects, the control parameters are the power of the water supply pump of the heat plant and the opening of the blow valve of the heat plant. It may include at least one of the degree and the injection volume of the chemical injection pump of the thermal plant.

According to the ninth aspect of the present invention, the water treatment system includes a cooling tower for cooling the cooling water, a water treatment device for treating the cooling water, and water quality according to any one of the first to eighth aspects. It is equipped with a control device.

According to the tenth aspect of the present invention, the heat plant includes the water treatment system according to the ninth aspect and a load device for heating the water cooled by the cooling water.

According to the eleventh aspect of the present invention, the power plant includes the water treatment system according to the ninth aspect, the load device for heating the water cooled by the cooling water, and the generator operated by the load device. And.

According to the twelfth aspect of the present invention, the water quality control method obtains a measured value relating to the water quality of the cooling water at a specific location of the thermal plant, the past operation history of the thermal plant, and the environment of the thermal plant. By inputting the environmental data into a load model that is learned based on the data and outputs information related to the load of the thermal plant after a predetermined time by inputting the environmental data, a purpose different from the specific location of the thermal plant is achieved. It has a capable of obtaining information related to the water temperature of locations, on the basis of the information and the measured value of the water temperature, that you determine the control parameters of the water treatment apparatus for performing treatment of the cooling water.

According to at least one of the above aspects, the water quality control device can appropriately perform water treatment of the cooling water even when the sampling location of the cooling water and the location having a high risk are different.

It is a schematic diagram which shows the structure of the power plant which concerns on 1st Embodiment. It is a schematic block diagram which shows the software structure of the water quality control device which concerns on 1st Embodiment. It is a flowchart which shows the operation of the water quality control device which concerns on 1st Embodiment. It is the schematic which shows the structure of the power plant which concerns on 4th Embodiment. It is a schematic block diagram which shows the software structure of the water quality control device which concerns on 4th Embodiment. It is a flowchart which shows the operation of the water quality control device which concerns on 4th Embodiment. It is a schematic block diagram which shows the structure of the computer which concerns on at least one Embodiment.

<First Embodiment>
Hereinafter, embodiments will be described in detail with reference to the drawings.
FIG. 1 is a schematic view showing a configuration of a power plant according to the first embodiment.
The water treatment system 100 according to the first embodiment is provided in the power plant 10. The power plant 10 includes a boiler 11, a steam turbine 12, a generator 13, a condenser 14, a pure water device 15, and a cooling tower 16. The configuration of the power plant 10 according to the other embodiment is not limited to this. For example, the power generation plant 10 according to another embodiment may have a generator 13 provided in another heat plant such as a gas turbine plant, a GTCC plant, a nuclear power plant, or a geothermal plant. A thermal plant is a plant that produces energy. In another embodiment, the water treatment system 100 may be provided in a thermal plant not provided with a generator 13.

The boiler 11 evaporates water to generate steam. The steam turbine 12 is rotated by the steam generated by the boiler 11. The generator 13 converts the rotational energy of the steam turbine 12 into electric power. The condenser 14 exchanges heat between the steam discharged from the steam turbine 12 and the cooling water, and returns the steam to water. The pure water device 15 produces pure water. The cooling tower 16 cools the cooling water heat-exchanged by the condenser 14. The cooling tower 16 is provided with a fan (not shown) for cooling the cooling water. The cooling tower 16 is provided with a stored water quality sensor 161. The stored water quality sensor 161 detects the quality of the cooling water stored in the cooling tower 16. Examples of water quality detected by the sensor include electrical conductivity, pH value, salt concentration, metal concentration, COD (Chemical Oxygen Demand), BOD (Biochemical Oxygen Demand), silica concentration, SDI (Silt Density Index), and turbidity. , ATP (Adenosine triphosphate) amount, DO (Dissolved Oxygen), residual chlorine, chemical concentration of dispersant, TOC (Total Organic Carbon), hardness (Ca, Mg, Total) and combinations thereof. The temperature control water quality sensor 1101 outputs a stored water quality index value indicating the detected water quality to the water quality control device 112. The cooling tower 16 is an example of a specific location of a thermal plant.

The water treatment system 100 includes a condenser 14, a cooling tower 16, a steam circulation line 101, a first replenishment line 102, a first drainage line 103, a first chemical injection line 104, a cooling water circulation line 105, and a second replenishment line 106. It includes a second drainage line 107, a second chemical injection line 108, a wastewater treatment device 111, a water quality control device 112, an environment measurement device 113, and an operation monitoring device 114.

The steam circulation line 101 is a line for circulating water and steam to the steam turbine 12, the condenser 14, and the boiler 11. A first water supply pump 1011 is provided between the condenser 14 and the boiler 11 in the steam circulation line 101. The first water supply pump 1011 pumps water from the condenser 14 to the boiler 11.
The first replenishment line 102 is a line for supplying the pure water generated by the pure water device 15 to the steam circulation line 101. A second water supply pump 1021 is provided on the first supply line 102. The second water supply pump 1021 is used when the condenser 14 is filled with water. During operation, the water in the first replenishment line 102 is pumped from the pure water device 15 toward the condenser 14 by the depressurization of the condenser 14.

The first drainage line 103 is a line for discharging a part of the water circulating in the steam circulation line 101 from the boiler 11 to the wastewater treatment device 111.
The first drug injection line 104 is a line for supplying a pH adjuster, an oxygen scavenger, or other drug to the steam circulation line 101. The first drug injection line 104 includes a first drug injection tank 1041 for storing the drug and a first drug injection pump 1042 for supplying the drug from the first drug injection tank 1041 to the steam circulation line 101. The first chemical injection pump 1042 is an example of a water treatment device that treats cooling water.
The steam circulation line 101, the first supply line 102, the first drainage line 103, and the first chemical injection line 104 form a circulating water system.

The cooling water circulation line 105 is a line for circulating cooling water to the condenser 14 and the cooling tower 16. The cooling water circulation line 105 is provided with a third water supply pump 1051. The third water supply pump 1051 pumps cooling water from the cooling tower 16 toward the condenser 14.

The second supply line 106 is a line for supplying the raw water taken from the water source to the cooling water circulation line 105 as makeup water. The second supply line 106 is provided with a fourth water supply pump 1061. The fourth water supply pump 1061 pumps make-up water from the water source toward the cooling tower 16.
The second drainage line 107 is a line for discharging a part of the water circulating in the cooling water circulation line 105 to the wastewater treatment device 111. A blow valve 1071 is provided in the second drainage line 107. The blow valve 1071 limits the amount of wastewater blown from the cooling water circulation line 105 to the wastewater treatment device 111. The blow valve 1071 is an example of a water treatment device that treats cooling water.

The second chemical injection line 108 is a line for supplying the cooling water circulation line 105 with an anti-food ingredient, an anti-scale agent, a slime control agent, a pH adjuster, or other chemicals. The second chemical injection line 108 includes a second chemical injection tank 1081 for storing the chemicals and a second chemical injection pump 1082 for supplying the chemicals from the second chemical injection tank 1081 to the cooling water circulation line 105.
A circulating water system is composed of a cooling water circulation line 105, a second supply line 106, a second drainage line 107, and a second chemical injection line 108. The second chemical injection pump 1082 is an example of a water treatment device that treats cooling water.

The sampling line 109 is a line for sampling the cooling water from the condenser 14. One end of the sampling line 109 is connected to the condenser 14, and the other end is connected to the temperature control device 110.
The temperature control device 110 has an electric heater and a Peltier element, and controls the cooling water sampled by the sampling line 109 to a temperature specified by the water quality control device 112. The temperature control device 110 is provided with a temperature control water quality sensor 1101. The temperature control water quality sensor 1101 detects the water quality of the cooling water whose temperature is controlled by the temperature control device 110. Examples of water quality detected by the sensor include electrical conductivity, pH value, salinity, metal concentration, COD (Chemical Oxygen Demand), BOD (Biochemical Oxygen Demand), and silica concentration, and combinations thereof. The temperature-controlled water quality sensor 1101 outputs a temperature-controlled water quality index value indicating the detected water quality to the water quality control device 112.

The wastewater treatment device 111 injects an acid, an alkali, a coagulant, or other chemicals into the wastewater discharged from the first wastewater line 103 and the second wastewater line 107. The wastewater treatment device 111 discards the wastewater treated by the chemicals.
The water quality control device 112 includes a stored water quality index value detected by the stored water quality sensor 161, a temperature controlled water quality index value detected by the temperature controlled water quality sensor 1101, environmental data around the power plant 10 measured by the environmental measuring device 113, and operation monitoring. Based on the operation data of the power generation plant 10 measured by the device 114, the power of the fourth water supply pump 1061, the opening degree of the blow valve 1071, and the injection amount (stroke amount or stroke number of the plunger) of the second chemical injection pump 1082 are determined. decide. The power of the fourth water supply pump 1061, the opening degree of the blow valve 1071, and the injection amount of the second chemical injection pump 1082 are examples of control parameters of the water treatment device.

The environment measuring device 113 measures the environment around the power plant 10 and generates environmental data. Examples of environmental data include weather, temperature and humidity in the area surrounding the power plant 10, and the quality of make-up water (turbidity level, etc.). The environmental measuring device 113 may accept input of environmental data such as the status of agricultural work upstream of the river flowing near the power plant 10, the status of the nearby community, and information on holidays.
The operation monitoring device 114 measures the operation data of the power plant 10 and generates the operation data. Examples of the operation data include the output of the power plant 10, various (steam, water, cooling water, chemicals, etc.) flow rates, the temperature and pressure of the boiler 11, the cooling water temperature, the air volume of the cooling tower 16, and the like.

FIG. 2 is a schematic block diagram showing a software configuration of the water quality control device according to the first embodiment.
The water quality control device 112 according to the first embodiment controls the water quality of the cooling water so that corrosion of the water treatment system 100 does not occur.
The water quality control device 112 includes a water quality index value acquisition unit 1111, an environmental data acquisition unit 1112, an operation data acquisition unit 1113, a load learning unit 1114, a load model storage unit 1115, a load estimation unit 1116, a target temperature estimation unit 1117, and a temperature control instruction. A unit 1118, a risk estimation unit 1119, and a parameter determination unit 1120 are provided.

The water quality index value acquisition unit 1111 acquires the stored water quality index value from the stored water quality sensor 161 and acquires the temperature controlled water quality index value from the temperature controlled water quality sensor 1101. Here, the stored water quality index value is an example of a measured value relating to the water quality of the cooling water at a specific location. In addition, the temperature control water quality index value represents the water quality of the cooling water at the target location, and is also an example of the measured value relating to the water quality of the cooling water at the specific location. That is, the water quality index value acquisition unit 1111 according to the first embodiment is an example of the measurement result acquisition unit that acquires the measured value related to the water quality of the cooling water at the specific location, and specifies the water quality of the cooling water at the target location. It is also an example of the target water quality identification part.

The environmental data acquisition unit 1112 acquires environmental data from the environmental measuring device 113.
The operation data acquisition unit 1113 acquires operation data from the operation monitoring device 114.

The load learning unit 1114 generates teacher data from the time series of the environment data and the operation data acquired in the past, and trains the load model stored in the load model storage unit 1115 by the teacher data. That is, the learning of the load model by the load learning unit 1114 is supervised learning. For example, the load learning unit 1114 associates the environmental data and the operation data related to one time with the output of the generator 13 after a predetermined time from the one time to obtain the teacher data. The output after a predetermined time can be specified from the time series of the operation data acquired in the past.

The load model storage unit 1115 stores a model for estimating the load after a predetermined time by inputting the environmental data and the operation data at one time. Examples of load models include neural network models, deep learning models, hidden Markov models, decision tree models, fuzzy control models, and the like.

The load estimation unit 1116 predicts the output of the generator 13 after a predetermined time by inputting environmental data and operation data into the load model stored in the load model storage unit 1115. The amount of heat exchange in the condenser 14 has a positive correlation with the output of the generator 13. Therefore, the output of the generator 13 is an example of information relating to the water temperature of the target location of the thermal plant. That is, the load estimation unit 1116 is an example of the water temperature information acquisition unit.

The target temperature estimation unit 1117 is based on the output of the generator 13 included in the operation data and the output of the generator 13 after a predetermined time predicted by the load estimation unit 1116, and the cooling water in the condenser 14 after a predetermined time. Calculate the temperature of. The condenser 14 is an example of a target location of a thermal plant. For example, the target temperature estimation unit 1117 calculates the temperature of the cooling water in the condenser 14 at the current time by calculating the heat balance in the thermal plant based on the operation data, and further outputs the output of the generator 13 after a certain period of time. By calculating the heat balance based on the above, the temperature of the cooling water in the condenser 14 after the predetermined time after the predetermined time is calculated. In addition, the amount of heat processed by an air blower for oxidation, an air compressor for spraying, or the like can also be used for calculating the heat balance.

The temperature control instruction unit 1118 outputs a temperature control instruction for adjusting the sampled cooling water to a target temperature to the temperature control device 110.

The risk estimation unit 1119 estimates the high risk of corrosion based on the temperature-controlled water quality index value and the temperature-controlled water quality index value acquired by the water quality index value acquisition unit 1111. For example, the risk estimation unit 1119 evaluates the height of corrosion risk by various evaluation methods according to the performance of the chemical, such as an estimation method using the Langeria index and an estimation method using the Rizner stability index. be able to. Here, as an example, a method of evaluation using the Langeria index will be described. When the Langeria index is less than 0, the risk of corrosion is low, and when the Langeria index is 0 or more, the risk of corrosion occurs. As shown in the following formula (1), the Langeria index SI is represented by the difference between pHm, which is the measured pH of cooling water, and pHs, which is the saturated pH of calcium carbonate.
SI = pHm-pHs ... (1)
As an example, a method for evaluating the high risk of corrosion using the Rizner stability index will be described. When the Rizner stability index is 7 or less, the risk of corrosion is low, and when the water quality index value is greater than 7, the risk of corrosion occurs. As shown in the following formula (2), the Rizner stability index RI is expressed by the difference between the pHm which is the measured pH of the cooling water and the pH which is twice the saturated pH of calcium carbonate.
RI = 2pHs-pHm ... (2)

The parameter determination unit 1120 determines the power of the fourth water supply pump 1061, the opening degree of the blow valve 1071, and the injection amount of the anticorrosive agent of the second chemical injection pump 1082, based on the height of the corrosion risk estimated by the risk estimation unit 1119. (Plunger stroke amount or number of strokes) is determined.

The operation of the water quality control device 112 according to the first embodiment will be described.
By inputting environmental data and operation data to the load model before controlling the water quality of the cooling water by the water quality control device 112, the load model is learned so that the output value of the generator 13 after a certain period of time is output. Let me. First, the load learning unit 1114 acquires the time series of the past environmental data and the operation data in the power generation plant 10 from the environmental data acquisition unit 1112 and the operation data acquisition unit 1113, and merges them. As a result, for a plurality of times, time-series data in which the environmental data and the operation data at that time are associated with each other is generated. Next, the load learning unit 1114 further associates the generated time-series data with the value of the output of the generator 13 after a predetermined time at that time. The output of the generator 13 after a predetermined time can be specified from the time series of the operation data. The load learning unit 1114 trains the load model stored in the load model storage unit 1115 using the generated time series data as teacher data. As a result, the load model becomes a trained model.

FIG. 3 is a flowchart showing the operation of the water quality control device according to the first embodiment.
When the water quality control device 112 starts the water quality control of the cooling water, the environmental data acquisition unit 1112 acquires the environmental data from the environmental measurement device 113, and the operation data acquisition unit 1113 acquires the operation data from the operation monitoring device 114 (step). S1). The load estimation unit 1116 estimates the output of the generator 13 by inputting the environmental data and the operation data into the load model stored in the load model storage unit 1115 (step S2).

The target temperature estimation unit 1117 estimates the temperature of the cooling water in the condenser 14 after a predetermined time based on the output of the generator 13 estimated by the load estimation unit 1116 and the operation data (step S3). The temperature control instruction unit 1118 outputs a temperature control instruction to the temperature control device 110 to adjust the temperature of the cooling water sampled from the sampling line 109 to the water temperature estimated by the target temperature estimation unit 1117 (step S4). As a result, the temperature control device 110 adjusts the temperature of the cooling water sampled from the sampling line 109 to the water temperature estimated by the target temperature estimation unit 1117. That is, the temperature control device 110 adjusts the temperature of the cooling water sampled from the cooling tower 16 to the temperature of the cooling water in the condenser 14. The temperature at which the temperature control device 110 adjusts the temperature does not necessarily have to be a temperature that completely matches the instructed temperature, but the temperature of the temperature control device 110 does not become lower than the instructed temperature. Adjust the temperature to. This can reduce the possibility of overlooking the risk of corrosion.

Next, the water quality index value acquisition unit 1111 acquires the stored water quality index value from the stored water quality sensor 161 and acquires the temperature controlled water quality index value from the temperature controlled water quality sensor 1101 (step S5). In step 4, since the temperature control device 110 adjusts the temperature of the sampled cooling water to the temperature of the cooling water in the condenser 14, the temperature control water quality index value is the water quality of the cooling water in the condenser 14. It can be said that it represents.

The risk estimation unit 1119 estimates the current high risk of corrosion in the cooling tower 16 and the high risk of future corrosion in the condenser 14 from the stored water quality index value and the temperature control water quality index value (step S6). The high risk of corrosion can be expressed by the Langeria index or the Rizner stability index.

Next, the parameter determination unit 1120 determines whether or not the quality of the cooling water satisfies the drainage constraint of the thermal plant (step S7). The drainage constraint is a constraint specified by a local government or the like in which a thermal plant is installed, and is, for example, a constraint on the values of phosphorus, nitrogen, TDS (Total Dissolved Solid), and COD (Chemical Oxygen Demand). When the water quality satisfies the drainage constraint (step S7: YES), the parameter determination unit 1120 sets the high corrosion risk as the target value based on the current high corrosion risk in the cooling tower 16 estimated by the risk estimation unit 1119. The amount of chemical injection by the second chemical injection pump 1082 is calculated (step S8). For example, the parameter determination unit 1120 calculates the drug injection amount for setting the Langeria index to 0 (target value) when the Langeria index representing the current high risk of corrosion in the cooling tower 16 is 1. That is, as the target value, a threshold value at which the risk of corrosion is eliminated or a value obtained by multiplying the threshold value by the safety factor is set.

The parameter determination unit 1120 determines whether or not the future corrosion risk in the condenser 14 is higher than the current corrosion risk (step S9). When the future corrosion risk is higher than the current corrosion risk (step S9: YES), the parameter determination unit 1120 determines the size of the difference between the high future corrosion risk and the current high corrosion risk. The drug injection amount calculated in step S7 is increased, and this drug injection amount is determined to be the drug injection amount by the second drug injection pump 1082 (step S10). On the other hand, when the height of the future corrosion risk is less than or equal to the current height of the corrosion risk (step S9: NO), the parameter determination unit 1120 uses the chemical injection amount calculated in step S8 as the second chemical injection pump. Determine the dosage according to 1082.

On the other hand, when the water quality does not satisfy the drainage constraint (step S7: NO), the parameter determination unit 1120 has a high corrosion risk based on the current high corrosion risk in the cooling tower 16 estimated by the risk estimation unit 1119. The amount of cooling water blown to set the target value is calculated (step S11). The parameter determination unit 1120 determines whether or not the future corrosion risk in the condenser 14 is higher than the current corrosion risk (step S12). If the future corrosion risk is higher than the current corrosion risk (step S12: YES), the parameter determination unit 1120 calculates in step S11 according to the size of the difference between the future corrosion risk and the current corrosion risk. The blow amount is increased, the blow amount is determined to be the blow amount by the blow valve 1071, and the injection amount of the fourth water supply pump 1061 is determined based on the blow amount (step S13). On the other hand, when the height of the future corrosion risk is equal to or less than the current height of the corrosion risk (step S12: NO), the parameter determination unit 1120 uses the blow amount calculated in step S13 as the blow amount by the blow valve 1071. The injection amount of the fourth water supply pump 1061 is determined based on the blow amount.

The parameter determination unit 1120 sets the determined chemical injection amount by the second chemical injection pump 1082, the opening degree of the blow valve 1071 and the injection amount of the fourth water supply pump 1061, respectively, to the second chemical injection pump 1082, the blow valve 1071, and the fourth. Output to the water supply pump 1061 (step S14). As a result, the second chemical injection pump 1082, the blow valve 1071 and the fourth water supply pump 1061 operate according to the instructions of the water quality control device 112.

As described above, the water quality control device 112 according to the first embodiment is derived from the specific location based on the stored water quality sensor 161 provided at the specific location (cooling tower 16) of the thermal plant and the output of the generator 13. It is possible to identify the quality of the cooling water at the destination where the risk of corrosion is high. As a result, the water quality control device 112 determines the control parameters of the water treatment device based on the water quality of the target location, so that the cooling water can be appropriately cooled even when the sampling location of the cooling water and the location at high risk are different. Water treatment can be performed. In this embodiment, the output of the generator 13 is used as information relating to the water temperature of the target location, but the present invention is not limited to this. For example, the information relating to the water temperature of the target location according to the other embodiment may be the water temperature of the target location itself, or may be other information such as the rotation speed of the steam turbine 12 and the steam flow rate of the boiler 11. Good.

Further, the water quality control device 112 according to the first embodiment predicts the water quality of the cooling water after a predetermined time at the target location based on the information and the measured value related to the water temperature. As a result, the water quality control device 112 can reduce the delay in control with respect to changes in water quality as compared with feedback control. Since the risk of corrosion increases cumulatively due to the delay in following the water treatment to changes in water quality, the risk of corrosion may suddenly increase at some point when only feedback control is performed, and it may be necessary to inject chemicals in a hurry. There is. On the other hand, the water quality control device 112 can reduce the risk of corrosion by reducing the delay in following the water treatment with respect to the change in water quality. Therefore, according to the water quality control device 112 according to the present embodiment, the need to suddenly add the drug is reduced. In addition, in other embodiments, the present invention is not limited to this, and the water quality of the cooling water at the current time of the target location may be predicted. In this case as well, the water quality control device 112 can achieve the effect that the water treatment of the cooling water can be appropriately performed even when the sampling location of the cooling water and the location having a high risk are different.

Further, the water quality control device 112 according to the first embodiment is learned based on the past operation history of the power plant 10 and the environmental data, and by inputting the environmental data, the generator 13 after a predetermined time of the power plant 10 It has a load model that outputs the output value. As a result, the water quality control device 112 can accurately estimate the water temperature at the target location after a predetermined time based on the environmental data.

The water quality control device 112 according to the first embodiment predicts the load of the generator 13 and specifies the temperature of the cooling water in the condenser 14 based on this, but is not limited to this. For example, the water quality control device 112 according to another embodiment may directly estimate the temperature of the cooling water in the condenser 14, or may relate to the water temperature at the target location such as the rotation speed of the steam turbine 12. Information may be obtained.

<Second embodiment>
The water quality control device 112 according to the first embodiment controls the water quality of the cooling water so that corrosion of the water treatment system 100 does not occur. On the other hand, the water quality control device 112 according to the second embodiment controls the water quality of the cooling water so that the water treatment system 100 does not scale.
The configuration of the power plant 10 according to the second embodiment is the same as that of the first embodiment.

The risk estimation unit 1119 of the water quality control device 112 according to the second embodiment estimates the height of the scaling risk based on the temperature control water quality index value and the temperature control water quality index value acquired by the water quality index value acquisition unit 1111. .. For example, the risk estimation unit 1119 can calculate the height of the scaling risk as a Langeria index. When the Langeria index is less than 0, the scaling risk is low, and when the Langeria index is 0 or more, the scaling risk occurs.
Further, for example, the risk estimation unit 1119 can calculate the scaling risk as a Resner stability index. When the Rizner stability index is 6 or more, the scaling risk is low, and when the water quality index value is less than 6, there is a scaling risk.

The parameter determination unit 1120 determines the power of the fourth water supply pump 1061, the opening degree of the blow valve 1071, and the injection amount of the antiscaling agent of the second chemical injection pump 1082 based on the scaling risk estimated by the risk estimation unit 1119. To do.

As described above, the water quality control device 112 according to the second embodiment is derived from the specific location based on the stored water quality sensor 161 provided at the specific location (cooling tower 16) of the thermal plant and the output of the generator 13. It is possible to identify the quality of the cooling water at the destination where the scaling risk is high. As a result, the water quality control device 112 determines the control parameters of the water treatment device based on the water quality of the target location, so that the cooling water can be appropriately cooled even when the sampling location of the cooling water and the location at high risk are different. Water treatment can be performed.

In the first embodiment, the control parameters are calculated based on the height of the corrosion risk, in the second embodiment, the control parameters are calculated based on the height of the scaling risk, but in the other embodiments, both of them are calculated. The control parameters may be calculated in consideration of the above. In this case, the parameter determination unit 1120 opens the power of the fourth water supply pump 1061 and the blow valve 1071 so that the Rizner stability index is 6 or more and 7 or less (preferably 6.5 or more and 7 or less). The degree and the amount of anti-scaling agent injected into the second drug injection pump 1082 may be determined.

<Third embodiment>
The water quality control device 112 according to the first embodiment controls the water quality of the cooling water so that the water treatment system 100 does not corrode, and the water quality control device 112 according to the second embodiment is attached to the water treatment system 100. Control the quality of the cooling water so that scaling does not occur. On the other hand, the water quality control device 112 according to the third embodiment controls the water quality of the cooling water so that fouling does not occur in the water treatment system 100.
The configuration of the power plant 10 according to the third embodiment is the same as that of the first embodiment.

The risk estimation unit 1119 of the water quality control device 112 according to the third embodiment determines the fouling risk based on the temperature control water quality index value, the temperature control water quality index value, and the cooling water temperature acquired by the water quality index value acquisition unit 1111. Estimate the height. As an estimation method of fouling risk, an estimation method by measuring ATP, an estimation method based on the contents of N (nitrogen), P (phosphorus), and C (carbon), and an estimation method using the intensity of autofluorescence of an organism. And so on. The risk of fouling increases as the concentration of substances involved in the growth of an organism (eg, nitrogen, phosphorus, carbon) increases, and as the temperature of cooling water approaches the optimum temperature for that organism. Since the optimum temperature differs depending on the organism (some organisms have cold resistance and some have heat resistance), the risk estimation unit 1119 fouls based on, for example, the organism having the indicated temperature closest to the temperature of the cooling water. The high risk may be estimated. The fouling risk is caused by an increase in the concentration of substances involved in the growth of living organisms due to rapid pollution of water sources. In general, in the case of microorganisms that require nitrogen and phosphorus, the ratio of nitrogen, phosphorus and carbon is roughly determined, and the carbon value can be estimated from the nitrogen or phosphorus value.

The parameter determination unit 1120 determines the power of the fourth water supply pump 1061, the opening degree of the blow valve 1071, and the bioproliferation inhibitor of the second drug injection pump 1082, based on the high fouling risk estimated by the risk estimation unit 1119. Determine the amount of injection (antibiotics, anti-algae, etc.).

As described above, the water quality control device 112 according to the third embodiment is derived from the specific location based on the stored water quality sensor 161 provided at the specific location (cooling tower 16) of the thermal plant and the output of the generator 13. It is possible to identify the quality of the cooling water at the destination where the fouling risk is high. As a result, the water quality control device 112 determines the control parameters of the water treatment device based on the water quality of the target location, so that the cooling water can be appropriately cooled even when the sampling location of the cooling water and the location at high risk are different. Water treatment can be performed.

In other embodiments, the control parameters may be calculated in consideration of not only the fouling risk but also one or both of the corrosion risk and the scaling risk.

<Fourth Embodiment>
The power plant 10 according to the first to third embodiments reproduces the state of the cooling water in the condenser 14 by adjusting the temperature of the cooling water sampled from the cooling tower 16 by the temperature control device 110. On the other hand, the power plant 10 according to the fourth embodiment estimates the water quality of the cooling water in the condenser 14 based on the stored water quality index value, the environmental data, and the operation data.

FIG. 4 is a schematic view showing the configuration of the power plant according to the fourth embodiment.
As shown in FIG. 4, the power plant 10 according to the fourth embodiment does not have to include the sampling line 109, the temperature control device 110, and the temperature control water quality sensor 1101 in the configuration of the first embodiment. On the other hand, the water quality control device 112 according to the fourth embodiment estimates the water quality of the cooling water in the condenser 14 based on the stored water quality index value, the environmental data, and the operation data.

FIG. 5 is a schematic block diagram showing a software configuration of the water quality control device according to the fourth embodiment.
The water quality control device 112 according to the fourth embodiment includes a water quality index value acquisition unit 1111, an environmental data acquisition unit 1112, an operation data acquisition unit 1113, a water quality learning unit 1121, a water quality model storage unit 1122, a water quality estimation unit 1123, and a risk estimation. A unit 1119 and a parameter determination unit 1120 are provided.

The water quality index value acquisition unit 1111 acquires the stored water quality index value from the stored water quality sensor 161. Here, the stored water quality index value is an example of a measured value relating to the water quality of the cooling water at a specific location. That is, the water quality index value acquisition unit 1111 according to the fourth embodiment is an example of the measurement result acquisition unit that acquires the measurement value related to the water quality of the cooling water at a specific location.

The environmental data acquisition unit 1112 acquires environmental data from the environmental measuring device 113.
The operation data acquisition unit 1113 acquires operation data from the operation monitoring device 114. Since the temperature of the cooling water in the condenser 14 changes depending on the operation of the power plant 10, the temperature of the cooling water in the condenser 14 can be calculated by the heat balance calculation based on the operation data. That is, the operation data acquisition unit 1113 is an example of the water temperature information acquisition unit.

The water quality learning unit 1121 generates teacher data from the time series of environmental data and operation data acquired in the past and the time series of the water quality index value of the cooling water in the water return device 14, and the water quality model storage unit is based on the teacher data. Train the water quality model stored in 1122. That is, the learning of the water quality model by the water quality learning unit 1121 is supervised learning. The water quality learning unit 1121 can obtain the above teacher data in, for example, a field test.

The water quality model storage unit 1122 stores a model for estimating the water quality index value of the cooling water in the condenser 14 after a predetermined time by inputting the environmental data and the operation data at one time. Examples of water quality models include neural network models, deep learning models, hidden Markov models, decision tree models, fuzzy control models, and the like.

The water quality estimation unit 1123 predicts the water quality index value of the cooling water in the condenser 14 after a predetermined time by inputting the environmental data and the operation data into the water quality model stored in the water quality model storage unit 1122. That is, the water quality estimation unit 1123 is an example of the target water quality identification unit.

The risk estimation unit 1119 estimates the high degree of corrosion risk, scaling risk, or fouling risk based on the temperature control water quality index value and the temperature control water quality index value acquired by the water quality index value acquisition unit 1111.
The parameter determination unit 1120 determines the power of the fourth water supply pump 1061, the opening degree of the blow valve 1071, and the injection amount of the drug of the second drug injection pump 1082 based on the height of the risk estimated by the risk estimation unit 1119. To do.

The operation of the water quality control device 112 according to the first embodiment will be described.
Before performing the water quality control of the cooling water by the water quality control device 112, the teacher including the environmental data, the operation data, the water quality index value of the cooling water in the cooling tower 16, and the water quality index value of the cooling water in the condenser 14 in the load model. By inputting the data, the water quality model is trained so as to output the water quality index value of the cooling water in the condenser 14 after a certain period of time. First, the water quality learning unit 1121 acquires the time series of the past environmental data, the operation data, and the stored water quality index value in the power plant 10, and merges them. As a result, for a plurality of times, time-series data in which the environmental data, the operation data, and the stored water quality index value at that time are associated with each other is generated. Next, the water quality learning unit 1121 further associates the generated time-series data with the water quality index value of the cooling water in the condenser 14 after a predetermined time at that time. The water quality learning unit 1121 trains the water quality model stored in the water quality model storage unit 1122 using the generated time series data as teacher data. As a result, the water quality model becomes a trained model.

FIG. 6 is a flowchart showing the operation of the water quality control device according to the fourth embodiment.
When the water quality control device 112 starts the water quality control of the cooling water, the environmental data acquisition unit 1112 acquires the environmental data from the environmental measurement device 113, the operation data acquisition unit 1113 acquires the operation data from the operation monitoring device 114, and the water quality index. The value acquisition unit 1111 acquires the stored water quality index value from the stored water quality sensor 161 (step S101). The water quality estimation unit 1123 estimates the water quality index value of the cooling water in the condenser 14 by inputting the environmental data, the operation data, and the stored water quality index value into the water quality model stored in the water quality model storage unit 1122 (step S102). ). Hereinafter, the water quality index value estimated by the water quality estimation unit 1123 is referred to as a target water quality index value.

The risk estimation unit 1119 estimates the current high risk in the cooling tower 16 and the future high risk in the condenser 14 from the stored water quality index value and the target water quality index value (step S103).

Next, the parameter determination unit 1120 determines whether or not the quality of the cooling water satisfies the drainage constraint of the thermal plant (step S104). When the water quality satisfies the drainage constraint (step S104: YES), the parameter determination unit 1120 sets the high risk as the target value based on the current high risk in the cooling tower 16 estimated by the risk estimation unit 1119. The amount of drug injection by the second drug injection pump 1082 for this purpose is calculated (step S105).

The parameter determination unit 1120 determines whether the future risk in the condenser 14 is higher than the current risk (step S106). If the future risk is higher than the current risk (step S106: YES), the parameter determination unit 1120 calculates in step S105 according to the size of the difference between the high future risk and the high current risk. The amount of the medicine to be injected is increased, and this amount of medicine is determined to be the amount of medicine to be injected by the second medicine injection pump 1082 (step S107). On the other hand, when the height of the future risk is less than or equal to the current height of the risk (step S9: NO), the parameter determination unit 1120 uses the second drug injection pump 1082 to determine the drug injection amount calculated in step S105. Determine the dosage.

On the other hand, when the water quality does not satisfy the drainage constraint (step S104: NO), the parameter determination unit 1120 targets the high risk based on the current high risk in the cooling tower 16 estimated by the risk estimation unit 1119. The amount of cooling water blown to make the value is calculated (step S108). The parameter determination unit 1120 determines whether the future risk in the condenser 14 is higher than the current risk (step S109). If the future risk is higher than the current risk (step S109: YES), the parameter determination unit 1120 determines the blow amount calculated in step S108 according to the size of the difference between the future risk and the current risk. The blow amount is increased, the blow amount is determined to be the blow amount by the blow valve 1071, and the injection amount of the fourth water supply pump 1061 is determined based on the blow amount (step S110). On the other hand, when the height of the future risk is equal to or less than the height of the current risk (step S109: NO), the parameter determination unit 1120 determines the blow amount calculated in step S13 as the blow amount by the blow valve 1071. , The injection amount of the fourth water supply pump 1061 is determined based on the blow amount.

The parameter determination unit 1120 sets the determined chemical injection amount by the second chemical injection pump 1082, the opening degree of the blow valve 1071 and the injection amount of the fourth water supply pump 1061, respectively, to the second chemical injection pump 1082, the blow valve 1071, and the fourth. Output to the water supply pump 1061 (step S111). As a result, the second chemical injection pump 1082, the blow valve 1071 and the fourth water supply pump 1061 operate according to the instructions of the water quality control device 112.

As described above, the target water quality specifying unit according to the fourth embodiment is based on the water quality model learned based on the past operation history of the heat plant and the water quality of the cooling water at the target location, and the cooling water at the target location. Identify the water quality of. As a result, the target water quality specifying unit according to the fourth embodiment can specify the water quality of the cooling water at the target location without adjusting the temperature of the cooling water as in the first to third embodiments. As a result, the time required for temperature control can be reduced, so that the water quality control device 112 can improve the controllability of the control of the water treatment device to the change in water quality.

Although one embodiment has been described in detail with reference to the drawings, the specific configuration is not limited to the above, and various design changes and the like can be made.
For example, the water quality control device 112 according to the above-described embodiment evaluates a risk based on a water quality index value and generates a control parameter of the water treatment device based on the risk, but the present invention is not limited to this. For example, the water quality control device 112 according to another embodiment may directly determine the control parameter from the water quality index value, or learns to output the control parameter by inputting the environmental data, the operation data, and the stored water quality index value. The control parameters of the water treatment device may be generated based on the completed model. Further, the water quality control device 112 according to the other embodiment may calculate the risk height based on the trained model that outputs the risk height by inputting the environmental data, the operation data, and the stored water quality index value. Good.

In the above-described embodiment, the case where the specific location is the cooling tower 16 and the target location is the condenser 14 has been described, but the present invention is not limited to this. For example, the specific location may be the condenser 14, or any location of the cooling water circulation line 105 and the second drainage line 107. Further, the target location may be the cooling tower 16, or any location of the cooling water circulation line 105 and the second drainage line 107.

In the above-described embodiment, the water quality control device 112 specifies the water quality of the cooling water at the target location based on the measured value related to the water quality of the cooling water at the specific location of the power generation plant 10 and the information regarding the water temperature at the target location. After that, the control parameters (such as the amount of chemical injection) of the water treatment device are determined, but the present invention is not limited to this. For example, in another embodiment, the water quality control device 112 receives a combination of a measurement value related to the water quality of the cooling water at a specific location and information related to the water temperature at the target location as an input, and outputs a control parameter of the water treatment apparatus. Control parameters may be determined using the completed model. That is, in another embodiment, the relationship between the information such as the load of the power plant 10 and the information such as the amount of chemical injection may be directly learned from the model.

FIG. 7 is a schematic block diagram showing a configuration of a computer according to at least one embodiment.
The computer 90 includes a CPU 91, a main storage device 92, an auxiliary storage device 93, and an interface 94.
The water quality control device 112 described above is mounted on the computer 90. The operation of each processing unit described above is stored in the auxiliary storage device 93 in the form of a program. The CPU 91 reads a program from the auxiliary storage device 93, expands it to the main storage device 92, and executes the above processing according to the program.
Further, the computer 90 may be a quantum computer. Since the quantum computer can process machine learning at a higher speed, the learning time can be significantly shortened because the computer 90 is a quantum computer. When a quantum computer is used, it is desirable to adopt a quantum annealing type quantum computer suitable for machine learning as the computer 90.

Examples of the auxiliary storage device 93 include HDD (Hard Disk Drive), SSD (Solid State Drive), magnetic disk, magneto-optical disk, CD-ROM (Compact Disc Read Only Memory), and DVD-ROM (Digital Versatile Disc Read Only). Memory), semiconductor memory, and the like. The auxiliary storage device 93 may be internal media directly connected to the bus of computer 90, or external media connected to computer 90 via an interface 94 or a communication line. When this program is distributed to the computer 90 via a communication line, the distributed computer 90 may expand the program to the main storage device 92 and execute the above processing. In at least one embodiment, the auxiliary storage device 93 is a non-temporary tangible storage medium.

Further, the program may be for realizing a part of the above-mentioned functions. Further, the program may be a so-called difference file (difference program) that realizes the above-mentioned function in combination with another program already stored in the auxiliary storage device 93.

10 Power plant 11 Boiler 12 Steam turbine 13 Generator 14 Water condenser 15 Pure water device 16 Cooling tower 100 Water treatment system 101 Steam circulation line 102 1st replenishment line 103 1st drainage line 104 1st chemical injection line 105 Cooling water circulation line 106 2nd replenishment line 107 2nd drainage line 108 2nd chemical injection line 109 Sampling line 110 Temperature control device 1101 Temperature control water quality sensor 111 Wastewater treatment device 112 Water quality control device 113 Environmental measurement device 114 Operation monitoring device 161 Storage water quality sensor 1111 Water quality Index value acquisition unit 1112 Environmental data acquisition unit 1113 Operation data acquisition unit 1114 Load learning unit 1115 Load model storage unit 1116 Load estimation unit 1117 Target temperature estimation unit 1118 Temperature control instruction unit 1119 Risk estimation unit 1120 Parameter determination unit 1121 Water quality learning unit 1122 Water quality model storage unit 1123 Water quality estimation unit 90 Computer 91 CPU
92 Main storage 93 Auxiliary storage 94 Interface

Claims (12)

A measurement result acquisition unit that acquires measurement values related to the quality of cooling water at a specific location in a thermal plant,
A load model that is learned based on the past operation history of the thermal plant and the environmental data of the thermal plant, and outputs information related to the load of the thermal plant after a predetermined time by inputting the environmental data.
A water temperature information acquisition unit that acquires information related to the water temperature at a target location different from the specific location of the thermal plant by inputting the environmental data into the load model .
A water quality control device including a parameter determination unit that determines control parameters of the water treatment device that processes the cooling water based on the information related to the water temperature and the measured value. Further provided with a target water quality specifying unit for specifying the water quality of the cooling water at the target location based on the information related to the water temperature and the measured value.
The water quality control device according to claim 1, wherein the parameter determination unit determines the control parameters based on the water quality of the target location. The water quality control device according to claim 2, wherein the target water quality specifying unit specifies the water quality of the cooling water after a predetermined time of the target location based on the information related to the water temperature and the measured value. The target water quality identification unit is
It is learned based on the past operation history of the thermal plant and the water quality of the cooling water at the target location, and the target location is input by inputting the water quality of the cooling water at the specific location and the water temperature of the target location. Further equipped with a water quality model that outputs the water quality of the cooling water
The target water quality specifying unit specifies the water quality of the cooling water at the target location by inputting the water quality of the cooling water at the specific location and the water temperature of the target location into the water quality model. Or the water quality control device according to claim 3 . Based on the information related to the water temperature, the temperature control device that changes the temperature of the cooling water sampled from the specific location is further provided with a temperature control indicator that outputs a temperature control instruction for adjusting the temperature to the water temperature of the target location. Prepare,
The measurement result acquisition unit acquires the measurement value related to the water quality of the cooling water whose temperature has been adjusted by the temperature control device.
The water quality control device according to claim 2 or 3 , wherein the target water quality specifying unit specifies the water quality of the cooling water at the target location based on the measured value acquired by the measurement result acquisition unit. The parameter determination unit determines the control parameter based on the water quality of the cooling water at the specific location and the water quality of the cooling water at the target location, according to any one of claims 1 to 5. The water quality control device described. Further provided with a risk estimation unit for estimating the height of the risk related to the thermal plant based on the water quality of the cooling water at the target location at the specific location.
The water quality control device according to any one of claims 1 to 6 , wherein the parameter determination unit determines the control parameter based on the height of risk estimated by the risk estimation unit. Any of claims 1 to 7 , wherein the control parameter includes at least one of the power of the water supply pump of the thermal plant, the opening degree of the blow valve of the thermal plant, and the injection amount of the chemical injection pump of the thermal plant. The water quality control device according to item 1. A cooling tower that cools the cooling water,
A water treatment device that treats the cooling water and
A water treatment system including the water quality control device according to any one of claims 1 to 8 . The water treatment system according to claim 9 and
A thermal plant including a load device for heating the water cooled by the cooling water. The water treatment system according to claim 9 and
A load device that heats the water cooled by the cooling water, and
A power plant including a generator operated by the load device. Obtaining measured values related to the quality of cooling water at a specific location in a thermal plant,
The environmental data is applied to a load model that is learned based on the past operation history of the thermal plant and the environmental data of the thermal plant and outputs information related to the load of the thermal plant after a predetermined time by inputting the environmental data. By inputting, information on the water temperature of the target location different from the specific location of the thermal plant can be obtained.
A water quality control method comprising determining a control parameter of a water treatment apparatus that processes the cooling water based on the information relating to the water temperature and the measured value.

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