Wet cooling unit cooling tower characteristic real-time monitoring method and system

Abstract

The invention relates to a wet cooling unit cooling tower characteristic real-time monitoring method and system, and the method comprises the steps: measuring the surrounding meteorological data and circulating water flow of a target cooling tower, collecting the real-time operation data of a power plant, and obtaining the design parameters of the cooling tower; iteratively calculating the atmospheric wet bulb temperature based on the measured meteorological data; and iteratively calculating characteristic parameters of the cooling tower based on the wind speed in the tower, including the characteristic coefficient of the cooling tower, the cooling amplitude of the cooling tower and the efficiency of the cooling tower, and monitoring the characteristics of the cooling tower of the wet cooling unit in real time. Compared with the prior art, the method has the advantages of high adaptability, high cooling tower performance calculation precision and the like. By collecting and analyzing operation data related to the performance of the cooling tower in real time and conducting iterative calculation on the wind speed in the cooling tower, real-time monitoring of performance parameters of the cooling tower is achieved, the problems affecting the performance of a unit can be found and solved in time, stable operation and efficient output of the unit are ensured, and the energy consumption level and the operation and maintenance cost of the unit can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of wet cooling unit cooling tower performance evaluation, and in particular to a real-time monitoring method and system for real-time evaluation of wet cooling unit cooling tower characteristics. Background Art

[0002] The performance of the cooling tower of the wet cooling unit has a profound impact on the economy of the power plant. Specifically, the loss of cold source constitutes the main part of the energy loss of the power plant. If the cooling tower performs poorly or operates unstably, it will cause the temperature of the circulating cooling water to rise, which will in turn cause the condenser vacuum to drop, reduce the working efficiency of the steam turbine unit, and ultimately increase the coal consumption for power generation, reduce the output of the equipment, and seriously affect the thermal efficiency of the power plant. Given that the efficiency of boilers and steam turbines in power plants has generally reached more than 90%, the space for energy-saving optimization is relatively limited, and the energy-saving potential of cooling towers has not yet been fully tapped. Studies have shown that for power plants equipped with steam turbine generator sets, the reduction in cooling water temperature is positively correlated with the improvement in thermal efficiency, especially in high-pressure units. For every 1°C reduction in cooling water temperature, the unit performance can be improved by about 0.35%.

[0003] However, for a long time, due to various reasons, power plants have not fully understood the energy-saving potential of cooling towers. Some power plants have even neglected the maintenance and monitoring of cooling towers, resulting in reduced cooling efficiency. The cooling performance of cooling towers is affected by many factors, including design parameters (such as filler layout, water distribution system configuration) and environmental factors (especially ambient crosswind). Ambient crosswinds can disrupt the flow field distribution in the tower, weaken the air flow performance, and thus reduce the cooling capacity of the cooling tower.

[0004] Chinese patent CN118310784A discloses a "cooling tower cooling efficiency evaluation method and system". The system iteratively calculates the wet bulb temperature based on the data from the cooling tower meteorological station. The method for calculating the approximation of the actual measurement of the cooling tower is clearly described, but the calculation of the ideal outlet temperature t2d is not described in detail. Therefore, there is a lack of methods for accurately calculating the cooling tower characteristics in real time; at the same time, as a system, how to pre-process the collected data and the consideration of the cooling tower design parameters are not perfect.

[0005] Chinese patent CN112698583A discloses "a wet cooling unit cold end performance monitoring and intelligent diagnosis system". This method mainly obtains environmental meteorological parameters and unit operation data under different working conditions from the database on a regular basis, and uses big data analysis and mining technology to calculate the cooling tower thermal change factor and resistance change factor according to the formula, so as to evaluate the changes in the cooling tower thermal performance and resistance performance. This method is more inclined to evaluate the changes in the cooling tower packing dirt or performance changes over a period of time, and lacks in the real-time dynamic evaluation of the cooling tower.

[0006] Chinese patent CN115481541A discloses "an accurate evaluation method for the comprehensive performance of a cooling tower". The main disadvantage of this method is that a large number of fitting formulas are used in the calculation methods such as the comprehensive performance analysis model based on water loss, the comprehensive performance analysis model based on air flow, and the comprehensive performance analysis model based on the air-water ratio λ. Such formulas need to be fitted according to different unit types, unit and cooling tower operating parameters, and do not have wide applicability; at the same time, the fitting formula will become inapplicable after a period of time due to changes in the accuracy of the operating data or the performance of the cooling tower, and at this time, the real-time performance of the cooling tower cannot be evaluated. Summary of the invention

[0007] The object of the present invention is to overcome the defects of the above-mentioned prior art and provide a cooling tower real-time performance monitoring method and system taking into account the environmental side wind conditions.

[0008] The purpose of the present invention can be achieved by the following technical solutions:

[0009] As a first aspect of the present invention, a method for real-time monitoring of cooling tower characteristics of a wet cooling unit is provided, the steps comprising:

[0010] Measure the meteorological data and circulating water flow around the target cooling tower, collect real-time operation data of the power plant, and obtain the design parameters of the cooling tower;

[0011] Iteratively calculate the atmospheric wet-bulb temperature based on the measured meteorological data;

[0012] The characteristic parameters of the cooling tower are calculated iteratively based on the wind speed in the tower, including the characteristic coefficient of the cooling tower, the cooling amplitude of the cooling tower and the efficiency of the cooling tower, and the cooling tower characteristics of the wet cooling unit are monitored in real time.

[0013] As a preferred technical solution, the method sets up multiple meteorological stations around the target cooling tower, and the measured meteorological data includes the atmospheric dry-bulb temperature T around the cooling tower. air , atmospheric humidity and atmospheric pressure P air .

[0014] As a preferred technical solution, the specific steps of iteratively calculating the atmospheric wet-bulb temperature are as follows:

[0015] According to the atmospheric dry bulb temperature T air Calculate the saturated vapor pressure P at atmospheric dry-bulb temperature wat ;

[0016] Assume that the initial value of the atmospheric wet-bulb temperature T_Wet_bulb0 is equal to the atmospheric dry-bulb temperature T air ;

[0017] The saturated vapor pressure P at the atmospheric wet-bulb temperature is calculated based on the initial value of the atmospheric wet-bulb temperature T_Wet_bulb0 water1 ;

[0018] According to the atmospheric dry bulb temperature T air , saturated vapor pressure P at atmospheric wet bulb temperature water1 , saturated vapor pressure P at atmospheric dry-bulb temperature water2 , atmospheric humidity Humidity, atmospheric pressure P air Calculate the atmospheric wet bulb temperature T_Wet_bulb;

[0019] Compare the deviation between the calculated atmospheric wet-bulb temperature T_Wet_bulb and the initial atmospheric wet-bulb temperature T_Wet_bulb0. If it is less than or equal to the set threshold, the iteration ends. Otherwise, the wet-bulb temperature is decreased by the set step size each time until the accuracy requirement is met and the iteration ends.

[0020] As a preferred technical solution, the specific steps of iteratively calculating the characteristic parameters of the cooling tower are as follows:

[0021] Set the initial value V0 of the wind speed in the tower, the initial value A_act of the characteristic parameter of the first cooling tower, and the outflow water temperature tmp_Twout and the inflow water temperature tmp_Twin;

[0022] Calculate the steam-water ratio tmp_Lamda in the tower at the initial value of wind speed;

[0023] The cooling tower characteristic number Ω is calculated according to the steam-water ratio tmp_Lamda in the tower, the first cooling tower characteristic parameter A_act and the second cooling tower characteristic parameter m;

[0024] Calculate the cooling number N related to meteorological conditions, and determine whether the cooling number N related to meteorological conditions and the cooling tower characteristic number Ω are equal; if they are not equal, change the tower water temperature tmp_Twout until N and Ω are equal;

[0025] Calculate the total resistance DeltaP of the cooling tower and the total extraction force H of the cooling tower to determine whether they are equal. If they are not equal, change the wind speed V0 in the tower and re-iterate the calculation until the error between the total resistance DeltaP of the cooling tower and the total extraction force H of the cooling tower is within a certain range.

[0026] Calculate the cooling tower cooling amplitude and efficiency, and calculate the initial value of the tower water temperature tmp_Twin at the same time, and determine whether the error between the tower water temperature tmp_Twin and the measured tower water temperature Twin is within the allowable range. If the error is not within the allowable range, change the wind speed V0 in the tower and re-iterate the calculation;

[0027] After the iteration is completed, the cooling tower characteristic coefficient, cooling tower cooling amplitude and cooling tower efficiency are output.

[0028] As a preferred technical solution, the cooling tower characteristic number Ω is calculated as follows:

[0029] Ω=A_act×tmp_Lamda m

[0030] Wherein: tmp_Lamda is the steam-water ratio in the tower; A_act is the characteristic parameter of the first cooling tower; m is the characteristic parameter of the second cooling tower.

[0031] As a preferred technical solution, the meteorological conditions related cooling number N is calculated as follows:

[0032]

[0033] In the formula: DeltT is the actual inlet and outlet water temperature rise; h2aa is the saturated air specific enthalpy with a temperature equivalent to the outlet water temperature tmp_Twout; h1 is the inlet wet air specific enthalpy; hmaa is the saturated air specific enthalpy with a temperature equivalent to the average water temperature tmp_Tm; hm is the mean specific enthalpy of the air in the tower, that is, the average value of the inlet wet air specific enthalpy h1 and the outlet wet air specific enthalpy h2; h1aa is the saturated air specific enthalpy with a temperature equivalent to the inlet water temperature tmp_Twin; h2 is the outlet wet air specific enthalpy.

[0034] As a preferred technical solution, the total resistance DeltaP of the cooling tower is calculated as follows:

[0035] DeltaP=0.5×Resist1×(Den_airin+Den_airout) / 2×V0 2

[0036] Among them, Resist1 is the total resistance coefficient calculated according to the wind speed V0 in the tower, and the calculation formula is as follows:

[0037] Resist1=Coff_Res_a+Coff_Res_b+Coff_Res_e-0.0253×V0 4 -0.2118×V0 3 +5.0962×V0 2 +14.37×V0

[0038] Among them, Coff_Res_a is the resistance coefficient from the air inlet to the tower throat, which is related to the ratio of the cooling tower inlet area to the tower area above the air inlet, as well as the resistance coefficients of the filler, water eliminator, and water distribution system during water sprinkling; Coff_Res_b is the resistance coefficient of the sprinkling rain area, which is related to the water sprinkling density, the effective height of the ventilation tower, and the inner radius of the tower above the air inlet; Coff_Res_e is the tower outlet resistance coefficient, which is related to the tower outlet area and the water sprinkling area; Den_airin is the air density entering the tower; Den_airout is the air density leaving the tower.

[0039] As a preferred technical solution, the cooling tower cooling amplitude, cooling tower actual efficiency coefficient, and cooling capacity coefficient are calculated as follows:

[0040] tmp_R=tmp_Twout-T_Wet_bulb

[0041]

[0042] tmp_Ra=Twout_real-T_Wet_bulb

[0043] tmp_Effa=(Twin_real-Twout_real) / (Twin_real-T_Wet_bulb)

[0044] tmp_K_eff=tmp_Effa / tmp_Eff_CoolingTower_Base

[0045] Wherein: tmp_R is the ideal cooling range (approximation) of the cooling tower; tmp_Eff_CoolingTower_Base is the ideal efficiency coefficient of the cooling tower; tmp_Eff_CoolingTower_Base is the actual cooling range (approximation) of the cooling tower; tmp_Effa is the actual efficiency coefficient of the cooling tower; tmp_K_eff is the cooling capacity coefficient of the cooling tower; T_Wet_bulb is the calculated value of the atmospheric wet bulb temperature.

[0046] As a preferred technical solution, the initial value of the water temperature entering the tower is calculated as follows:

[0047] tmp_Twin=tmp_Twin+DeltT

[0048] Where tmp_Twout is the initial value of the water temperature out of the tower, which is calculated as follows:

[0049] tmp_Twout=tmp_Twout+(N-Ω) / 25

[0050] The initial value A_act of the first cooling tower characteristic coefficient changes as follows:

[0051] A_act=A_act-(Twin-tmp_Twin) / 20

[0052] Where Twin is the measured water temperature entering the tower.

[0053] As a second aspect of the present invention, a real-time monitoring system for cooling tower characteristics of a wet cooling unit is provided, wherein the system applies the real-time monitoring method for cooling tower characteristics of a wet cooling unit as described above, specifically comprising:

[0054] Multiple micro-meteorological stations are symmetrically arranged near the target cooling tower to measure the meteorological data around the target cooling tower, including the atmospheric dry-bulb temperature, atmospheric humidity, atmospheric pressure, atmospheric temperature and wind speed around the cooling tower;

[0055] The circulating water flow measuring device is installed on the circulating water pump main pipe to measure the total circulating water flow;

[0056] A relational database that stores the design parameters of the cooling tower, including the diameter D1 at 1 / 2 the height of the filler, the effective height H of the ventilation tower, e , watering area F, inner radius of the upper eaves tower R, characteristic parameter A of the first cooling tower, characteristic parameter m of the second cooling tower and height H0 of the air inlet;

[0057] The power plant real-time database stores the collected real-time data of the power plant operation, including the actual cooling tower inlet water temperature Twin and the actual cooling tower outlet water temperature Twout;

[0058] The wet-bulb temperature of the air entering the tower is obtained and iteratively calculated based on the meteorological data;

[0059] The cooling tower characteristic parameter monitoring module iteratively calculates the small parameters of the cooling tower based on the iterative calculation of the wind speed in the tower, including the first cooling tower characteristic parameter, cooling tower cooling amplitude, cooling tower efficiency, and performs real-time monitoring of the cooling tower characteristics of the wet cooling unit.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1) The real-time performance monitoring scheme of the cooling tower proposed in the present invention is a data calculation and monitoring scheme for the cooling tower characteristics obtained by iterative calculation based on the cooling tower meteorological data, circulating water flow data, and cooling tower inlet and outlet temperature data. By real-time collection and analysis of operating data related to the performance of the cooling tower, it is directly applied to the performance monitoring of the cooling tower. By evaluating the characteristics of the cooling tower in real time, problems affecting the performance of the unit, such as insufficient cooling water and excessive water temperature, can be discovered and solved in a timely manner. This will help improve the overall performance of the wet cooling unit, ensure the stable operation and efficient output of the unit, and reduce energy consumption and operation and maintenance costs.

[0062] 2) The present invention takes into account the environmental side wind conditions and performs iterative calculation of the wind speed in the cooling tower to further enhance the credibility of the calculation results. The wind speed in the cooling tower will directly affect the diffusion rate of water vapor and the heat dissipation efficiency. Too low wind speed will lead to slow water vapor diffusion and low heat dissipation efficiency; too high wind speed may cause water to evaporate too quickly, reducing the cooling effect. However, the wind speed in the cooling tower is a quantity that is difficult to measure. The present invention can calculate the wind speed in the cooling tower in real time through an iterative calculation method, so that the relevant characteristics of the cooling tower can be evaluated more accurately in real time, further enhancing the credibility and reference of the calculation results.

[0063] 3) The method of the present invention has wide applicability and can be applied to different types of wet cooling unit cooling towers. At the same time, the method also has a high level of automation and intelligence, and can easily realize remote monitoring and automatic control. Therefore, the method has broad application prospects and promotion value in similar industries such as electricity, chemical industry, and metallurgy. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a flow chart of a method for real-time monitoring of cooling tower characteristics of a wet cooling unit of the present invention;

[0065] Figure 2 This is a schematic diagram of the distribution of micro-weather stations;

[0066] Figure 3 Schematic diagram for installation of micro weather station;

[0067] Figure 4 This is the installation diagram of the circulating pump insertion electromagnetic flowmeter;

[0068] Figure 5 Enter computational model diagrams for real-time and relational data;

[0069] Figure 6 This is a schematic diagram of iterative calculation of wet bulb temperature;

[0070] Figure 7 Schematic diagram of a real-time monitoring system for cooling tower characteristics of a wet cooling unit in another embodiment of the present invention. DETAILED DESCRIPTION

[0071] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0072] Example 1

[0073] As one embodiment of the present invention, Figure 1This embodiment provides a method for real-time monitoring of cooling tower characteristics of a wet cooling unit, and the specific steps are as follows:

[0074] Step 1: Install three micro-meteorological stations near the target cooling tower. The acquisition module will measure the atmospheric dry-bulb temperature T around the cooling tower. air , atmospheric humidity Humidity, atmospheric pressure P air .like Figure 2-3 As shown in the figure, the three micro-meteorological stations are installed in the symmetrical direction of the cooling tower, about 25 to 30 meters away from the cooling tower, and the height of the weather station is about 1.5 to 2 meters. They mainly simulate the function of natural wind entering to cool the circulating water. At the same time, the data of the three weather stations are redundant with each other, which can avoid the situation where the calculation deviation occurs due to the measurement error of the measuring point. The micro-meteorological station requires 220V power supply and outputs 485 digital signals. After being connected to the I / O cabinet of the nearest DCS, it is converted into a standard 4-20mA signal through the digital-to-analog conversion module and connected to the I / O module of the DCS.

[0075] Setp2: Install a circulating water flow measurement device on the circulating water pump main pipe to measure the total circulating water flow rate as F_CirW: including measuring probes and secondary instruments. If it is a double back pressure unit, one set of measuring devices needs to be installed on each high and low pressure side condenser. Figure 4 As shown in the figure, the insertion electromagnetic flow probe is installed on the circulating water pipeline. A straight pipeline of about 5m is required before and after the installation point to avoid turbulence. The probe is inserted into the center of the circulating water pipeline. After the measuring device is inserted, it is fixedly connected through the base and the ferrule; the measurement signal is connected to the secondary instrument installed on site through a shielded communication cable. The secondary instrument requires a 220V power supply, and the measurement signal is connected to the I / O card of the local control cabinet through a shielded communication cable.

[0076] Step 3: The above data is collected into the real-time database through the power plant OPC communication interface and saved in seconds. At the same time, the real-time database collects some other real-time data of the power plant operation, mainly including the actual cooling tower inlet water temperature Twin and the actual cooling tower outlet water temperature Twout.

[0077] Step 4: The design parameters of the cooling tower are saved in the relational database, including the diameter D1 at 1 / 2 height of the filler, the effective height H of the ventilation tower, and the e , watering area F, inner radius of the upper eaves tower R, characteristic parameter (design value) A of the first cooling tower (this parameter is used to characterize the cooling capacity of the filler, the better the filler or the higher the height, the greater A), characteristic parameter (design value) m of the second cooling tower (this parameter is the characteristic parameter of the internal structure of the cooling tower, and the parameters of different cooling tower structures will be different), air inlet height H0;

[0078] Step 5: Read the required calculation data from the real-time database of the power plant and perform data preprocessing. The main method is the moving average algorithm. At the same time, the meteorological data needs to be processed by the three-center method before moving average. For example, the three wind speed measurement points are taken as the model input measurement points after the moving average calculation.

[0079] The median method mainly determines the size of the three data by sorting the values ​​of the measuring points. According to the median method, the P values ​​measured by the three micro-meteorological stations are air1 , P air , P air3 Get the atmospheric pressure median value P air ; by T air1 、T air2 、T air3 Get the atmospheric dry bulb temperature median value T air ; The intermediate value of atmospheric relative humidity Humidity is obtained from Humidity1, Humidity2, and Humidity3, which is used in the subsequent calculation process. At the same time, the measured data of the power plant will fluctuate to a certain extent within a period of time. At this time, the moving average method is needed to eliminate the influence of these fluctuations. Suppose there is a time series y1, y2, ..., y t …, then we can calculate the average of N numbers by moving them point by point in the order of data points to get a moving average:

[0080]

[0081] In the formula, is the moving average of the tth period; y t is the observed value of the tth period; N is the number of moving average items, that is, the number of observations used to calculate each moving average.

[0082] This formula shows that when t moves forward by one period, a recent data is added, a long-term data is removed, and a new average is obtained. Because it moves forward period by period, it is called the moving average method. Because the moving average can smooth the data, it eliminates the impact of periodic changes and irregular changes.

[0083] Step 6: Iteratively calculate the initial value of the atmospheric wet-bulb temperature T_Wet_bulb0 based on meteorological data. The specific steps are as follows: Figure 5 As shown:

[0084] (6.1) According to the atmospheric dry-bulb temperature T air Calculate the saturated vapor pressure P at atmospheric dry-bulb temperature water2 ;

[0085] K air =273.15+T air

[0086] P water =98070*10 n

[0087] n=0.0141966-3.142305×K1+8.2×K3-0.0024804×K3

[0088] in,

[0089]

[0090] K3=0.0024804×(373.16-K air )

[0091] (6.2) Assume that the initial value of the atmospheric wet-bulb temperature T_Wet_bulb0 is equal to the atmospheric dry-bulb temperature T air ;

[0092] (6.3) According to the initial value of atmospheric wet-bulb temperature T_Wet_bulb0, the saturated vapor pressure P at atmospheric wet-bulb temperature is calculated. water1 , the formula is the same as above;

[0093] (6.4) According to the atmospheric dry-bulb temperature T air , saturated vapor pressure P at atmospheric wet bulb temperature wate , saturated vapor pressure P at atmospheric dry-bulb temperature wate , atmospheric humidity Humidity, atmospheric pressure P air The atmospheric wet bulb temperature T_Wet_bulb is calculated using the following formula:

[0094]

[0095] (6.5) Compare the deviation between the calculated atmospheric wet-bulb temperature T_Wet_bulb and the initial atmospheric wet-bulb temperature T_Wet_bulb0. If it is less than or equal to 0.1, the iteration ends. Otherwise, the initial atmospheric wet-bulb temperature T_Wet_bulb0 is decreased by 0.01 each time (because the initial value of the wet-bulb temperature is the dry-bulb temperature, which must be greater than the wet-bulb temperature) until the accuracy requirement is met and the iteration ends.

[0096] Step 7: Iteratively calculate the cooling tower characteristic parameters. The most important thing is to find the size of the cooling tower theoretical outlet temperature, including the first cooling tower characteristic parameter A_act, cooling tower cooling amplitude, cooling tower efficiency and other data, such as Figure 6 As shown, the main steps are as follows:

[0097] (7.1) Set the initial value of the wind speed in the tower V0, the initial value of the characteristic parameter of the first cooling tower A_act (which can be the design value), and the outflow water temperature tmp_Twout and the inflow water temperature tmp_Twin;

[0098] tmp_Twout=T_Wet_bult0+(14-0.2×T air -1.5×Humidity)

[0099] DeltT=Twin-Twin

[0100] Where: DeltT is the actual water temperature rise at the inlet and outlet of the tower; (7.2) Under the initial wind speed value, the steam-water ratio tmp_Lamda in the tower is calculated as follows:

[0101] tmp_Lamda=F_air / F_CirW

[0102] Where: F_CirW is the measured circulating water flow; F_air is the air volume:

[0103] F_air=3.6×m×V0×Density

[0104] Where m is the watering area; Density is the air density entering the tower;

[0105] (7.3) The cooling tower characteristic number Ω is calculated based on the steam-water ratio tmp_Lamda in the tower, the first cooling tower characteristic parameter A_act and the second cooling tower characteristic parameter m (taking the design value);

[0106] Ω=A_act×tmp_Lamda m

[0107] (7.4) Calculate the cooling number N related to meteorological conditions, and determine whether the cooling number N related to meteorological conditions and the cooling tower characteristic number Ω are equal; if they are not equal, change the tower water temperature tmp_Twout until N and Ω are equal;

[0108]

[0109] Where: h2aa is the specific enthalpy of saturated air with a temperature equivalent to the water temperature tmp_Twout at the outlet of the tower; h1 is the specific enthalpy of wet air entering the tower; hmaa is the specific enthalpy of saturated air with a temperature equivalent to the average water temperature tmp_Tm; hm is the mean specific enthalpy of air in the tower, that is, the average value of the specific enthalpy of wet air entering the tower h1 and the specific enthalpy of wet air leaving the tower h2; h1aa is the specific enthalpy of saturated air with a temperature equivalent to the water temperature tmp_Twin at the outlet of the tower; h2 is the specific enthalpy of wet air leaving the tower;

[0110] (7.5) Calculate the total resistance DeltaP of the cooling tower and the total draft H of the cooling tower, and determine whether they are equal. If they are not equal, change the wind speed V0 in the tower and return to step (7.1) to iterate again until the error between the total draft H and the total draft H is within a certain range;

[0111] The calculation formula is as follows:

[0112] DeltaP=0.5×Resist1×(Den_airin+Den_airout) / 2×V0 2

[0113] Among them, Resist1 is the total resistance coefficient calculated according to the wind speed V0 in the tower, and the calculation formula is as follows:

[0114] Resist1=Coff_Res_a+Coff_Res_b+Coff_Res_e-0.0253×V0 4 -0.2118×V0 3 +5.0962×V0 2 +14.37×V0

[0115] Among them, Coff_Res_a is the resistance coefficient from the air inlet to the tower throat, which is related to the ratio of the cooling tower inlet area to the tower area above the air inlet, as well as the resistance coefficients of the filler, water eliminator, and water distribution system during water sprinkling; Coff_Res_b is the resistance coefficient of the sprinkling rain area, which is related to the water sprinkling density, the effective height of the ventilation tower, and the inner radius of the tower above the air inlet; Coff_Res_e is the tower outlet resistance coefficient, which is related to the tower outlet area and the water sprinkling area; Den_airin is the air density entering the tower; Den_airout is the air density leaving the tower.

[0116] (7.6) Calculate the cooling tower cooling range, actual efficiency coefficient, cooling capacity coefficient and other data. The calculation formula is as follows:

[0117] tmp_R=tmp_Twout-T_Wet_bulb

[0118]

[0119] tmp_Ra=Twout_real-T_Wet_bulb

[0120] tmp_Effa=(Twin_real-Twout_real) / (Twin_real-T_Wet_bulb)

[0121] tmp_K_eff=tmp_Effa / tmp_Eff_CoolingTower_Base

[0122] Wherein: tmp_R is the ideal cooling range (approximation) of the cooling tower; tmp_Eff_CoolingTower_Base is the ideal efficiency coefficient of the cooling tower; tmp_Eff_CoolingTower_Base is the actual cooling range (approximation) of the cooling tower; tmp_Effa is the actual efficiency coefficient of the cooling tower; tmp_K_eff is the cooling capacity coefficient of the cooling tower; T_Wet_bulb is the calculated value of the atmospheric wet bulb temperature.

[0123] At the same time, calculate the initial value of the tower water temperature tmp_Twin, and determine whether the error between the tower water temperature tmp_Twin and the measured tower water temperature Twin is within the allowable range. If the error is not within the allowable range, return to step 7.1 and change the tower wind speed V0 to recalculate. The formula is as follows:

[0124] Calculate the initial value of tower water temperature:

[0125] tmp_Twout=tmp_Twout+(N-Ω) / 25

[0126] Calculate the initial value of the water temperature entering the tower:

[0127] tmp_Twin=tmp_Twin+DeltT

[0128] At the same time, the initial value of the characteristic coefficient of the cooling tower also changes, the formula is as follows:

[0129] A_act=A_act-(Twin-tmp_Twin) / 20

[0130] (7.7) The iteration is completed. After the iteration is completed, the cooling tower characteristic coefficient A_act and other performance data related to the cooling tower such as cooling tower cooling amplitude and cooling tower efficiency are output.

[0131] Through the above scheme, the present invention can be directly applied to the performance monitoring of the cooling tower by real-time collection and analysis of the operating data related to the performance of the cooling tower. The wind speed in the cooling tower can be calculated in real time by an iterative calculation method, so that the relevant characteristics of the cooling tower can be evaluated more accurately in real time, further enhancing the credibility and reference of the calculation results. The cooling tower is an important component of the wet cooling unit, and its performance directly affects the overall performance of the unit. By evaluating the characteristics of the cooling tower in real time, problems affecting the performance of the unit, such as insufficient cooling, excessive water temperature, etc., can be discovered and solved in time. This helps to improve the overall performance of the wet cooling unit and ensure the stable operation and efficient output of the unit. And the method has a wide range of applicability and can be applied to different types of wet cooling unit cooling towers. At the same time, the method also has a high level of automation and intelligence, and is easy to realize remote monitoring and automatic control. This makes the method have a wide range of application prospects and promotion value in industries such as electricity, chemical industry, and metallurgy.

[0132] Example 2

[0133] As another embodiment of the present invention, this embodiment also provides a real-time monitoring system for the cooling tower characteristics of a wet cooling unit according to the method described in the above embodiment. Figure 7 As shown, the system includes:

[0134] Multiple micro-meteorological stations are symmetrically arranged near the target cooling tower to measure the meteorological data around the target cooling tower, including the atmospheric dry-bulb temperature, atmospheric humidity, and atmospheric pressure around the cooling tower;

[0135] The circulating water flow measuring device is installed on the circulating water pump main pipe to measure the total circulating water flow;

[0136] A relational database that stores the design parameters of the cooling tower, including the diameter D1 at 1 / 2 the height of the filler, the effective height H of the ventilation tower, e , watering area F, inner radius of the upper eaves tower R, characteristic parameter A of the first cooling tower, characteristic parameter m of the second cooling tower and height H0 of the air inlet;

[0137] The power plant real-time database stores the collected real-time data of the power plant operation, including the actual cooling tower inlet water temperature Twin and the actual cooling tower outlet water temperature Twout;

[0138] The wet-bulb temperature of the air entering the tower is obtained and iteratively calculated based on the meteorological data;

[0139] The cooling tower characteristic parameter monitoring module obtains the first cooling tower characteristic parameter, cooling tower cooling amplitude, and cooling tower efficiency based on the iterative calculation of the wind speed in the tower, and performs real-time monitoring of the cooling tower characteristics of the wet cooling unit.

[0140] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit, characterized in that the steps include: Measure the meteorological data and circulating water flow around the target cooling tower, collect real-time operation data of the power plant, and obtain the design parameters of the cooling tower; Iteratively calculate the atmospheric wet-bulb temperature based on the measured meteorological data; The characteristic parameters of the cooling tower are calculated iteratively based on the wind speed in the tower, including the characteristic coefficient of the cooling tower, the cooling amplitude of the cooling tower and the efficiency of the cooling tower, and the cooling tower characteristics of the wet cooling unit are monitored in real time.

2. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 1, characterized in that: The method sets up multiple meteorological stations around the target cooling tower, and the measured meteorological data include the atmospheric dry-bulb temperature T around the cooling tower. air , atmospheric humidity and atmospheric pressure P air .

3. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 1, characterized in that: The specific steps of iteratively calculating the atmospheric wet-bulb temperature are as follows: According to the atmospheric dry bulb temperature T air Calculate the saturated vapor pressure P at atmospheric dry-bulb temperature water2 ; Assume that the initial value of the atmospheric wet-bulb temperature T_Wet_bulbO is equal to the atmospheric dry-bulb temperature T air ; The saturated vapor pressure P at the atmospheric wet-bulb temperature is calculated based on the initial value of the atmospheric wet-bulb temperature T_Wet_bulb0 water1 ; According to the atmospheric dry bulb temperature T air , saturated vapor pressure P at atmospheric wet bulb temperature water1 , saturated vapor pressure P at atmospheric dry-bulb temperature water2 , atmospheric humidity Humidity, atmospheric pressure P air Calculate the atmospheric wet bulb temperature T_Wet_bulb; Compare the deviation between the calculated atmospheric wet-bulb temperature T_Wet_bulb and the initial atmospheric wet-bulb temperature T_Wet_bulbO. If it is less than or equal to the set threshold, the iteration ends. Otherwise, the wet-bulb temperature is decreased by the set step size each time until the accuracy requirement is met and the iteration ends.

4. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 1, characterized in that: The specific steps of iteratively calculating the characteristic parameters of the cooling tower are as follows: Set the initial value V0 of the wind speed in the tower, the initial value A_act of the characteristic parameter of the first cooling tower, and the outflow water temperature tmp_Twout and the inflow water temperature tmp_Twin; Calculate the steam-water ratio tmp_Lamda in the tower at the initial value of wind speed; The cooling tower characteristic number Ω is calculated according to the steam-water ratio tmp_Lamda in the tower, the first cooling tower characteristic parameter A_act and the second cooling tower characteristic parameter m; Calculate the cooling number N related to meteorological conditions, and determine whether the cooling number N related to meteorological conditions and the cooling tower characteristic number Ω are equal; if they are not equal, change the tower water temperature tmp_Twout until N and Ω are equal; Calculate the total resistance DeltaP of the cooling tower and the total extraction force H of the cooling tower to determine whether they are equal. If they are not equal, change the wind speed V0 in the tower and re-iterate the calculation until the error between the total resistance DeltaP of the cooling tower and the total extraction force H of the cooling tower is within a certain range. Calculate the cooling tower cooling amplitude and efficiency, and calculate the initial value of the tower water temperature tmp_Twin at the same time, and determine whether the error between the tower water temperature tmp_Twin and the measured tower water temperature Twin is within the allowable range. If the error is not within the allowable range, change the wind speed V0 in the tower and re-iterate the calculation; After the iteration is completed, the cooling tower characteristic coefficient, cooling tower cooling amplitude and cooling tower efficiency are output.

5. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 4, characterized in that: The cooling tower characteristic number Ω is calculated as follows: Ω=A_act×tmmp-Lamda mm Wherein: tmmp_Lamda is the steam-water ratio in the tower; A_act is the characteristic parameter of the first cooling tower; m is the characteristic parameter of the second cooling tower.

6. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 4, characterized in that: The cooling number N related to the meteorological conditions is calculated as follows: In the formula: DeltT is the actual inlet and outlet water temperature rise; h2aa is the saturated air specific enthalpy with a temperature equivalent to the outlet water temperature tmmp_Twout; h1 is the inlet wet air specific enthalpy; hmaa is the saturated air specific enthalpy with a temperature equivalent to the average water temperature tmp_Tm; hm is the mean specific enthalpy of the air in the tower, that is, the average value of the inlet wet air specific enthalpy h1 and the outlet wet air specific enthalpy h2; h1aa is the saturated air specific enthalpy with a temperature equivalent to the inlet water temperature tmp_Twin; h2 is the outlet wet air specific enthalpy.

7. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 4, characterized in that: The total cooling tower resistance DeltaP is calculated as follows: DeltaP=0.5×Resist1×(Den_airin+Den_airout) / 2×V0 2 Among them, Resist1 is the total resistance coefficient calculated according to the wind speed V0 in the tower, and the calculation formula is as follows: Resist1=Coff_Res_a+Coff_Res_b+Coff_Res_e-0.0253×V0 4 -0.2118×V03+5.0962×V0 2 +14.37×V0 Among them, Coff_Res_a is the resistance coefficient from the air inlet to the tower throat, which is related to the ratio of the cooling tower inlet area to the tower area above the air inlet, as well as the resistance coefficients of the filler, water eliminator, and water distribution system during water sprinkling; Coff_Res_b is the resistance coefficient of the sprinkling rain area, which is related to the water sprinkling density, the effective height of the ventilation tower, and the inner radius of the tower above the air inlet; Coff_Res_e is the tower outlet resistance coefficient, which is related to the tower outlet area and the water sprinkling area; Den_airin is the air density entering the tower; Den_airout is the air density leaving the tower.

8. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 4, characterized in that: The cooling tower cooling amplitude, cooling tower actual efficiency coefficient, and cooling capacity coefficient are calculated as follows: tmp_R=tmp_Twout-T_Wet_bulb tmp_Ra=Twout_real-T_Wet_bulb tmp_Effa=(Twin_real-Twout_real) / (Twin_real-T_Wet_bulb) tmp_K_eff=tmp_Effa / tmp_Eff_CoolingTower_Base Wherein: tmp_R is the ideal cooling range (approximation) of the cooling tower; tmp_Eff_CoolingTower_Base is the ideal efficiency coefficient of the cooling tower; tmp_Eff_CoolingTower_Base is the actual cooling range (approximation) of the cooling tower; tmp_Effa is the actual efficiency coefficient of the cooling tower; tmp_K_eff is the cooling capacity coefficient of the cooling tower; T_Wet_bulb is the calculated value of the atmospheric wet bulb temperature.

9. A method for real-time monitoring of cooling tower characteristics of a wet cooling unit according to claim 4, characterized in that: The initial value of the water temperature entering the tower is calculated as follows: tmmp_Twin=tmmp-Twout+D e ltT Where tmmp_Twout is the initial value of the water temperature out of the tower, which is calculated as follows: tmmp_Twout=tmmp_Twout+(N-Ω) / 25 The initial value A_act of the first cooling tower characteristic coefficient changes as follows: A_act=A_act-(Twin-tmmp_Twin) / 20 Where Twin is the measured water temperature entering the tower.

10. A real-time monitoring system for cooling tower characteristics of a wet cooling unit, characterized in that: The system uses the real-time monitoring method for cooling tower characteristics of a wet cooling unit as described in any one of claims 1 to 9, specifically comprising: Multiple micro-meteorological stations are symmetrically arranged near the target cooling tower to measure the meteorological data around the target cooling tower, including the atmospheric dry-bulb temperature, atmospheric humidity, atmospheric pressure, atmospheric temperature and wind speed around the cooling tower; The circulating water flow measuring device is installed on the circulating water pump main pipe to measure the total circulating water flow; A relational database that stores the design parameters of the cooling tower, including the diameter D1 at 1 / 2 the height of the filler, the effective height H of the ventilation tower, e , watering area F, inner radius of the upper eaves tower R, characteristic parameter A of the first cooling tower, characteristic parameter m of the second cooling tower and height H0 of the air inlet; The power plant real-time database stores the collected real-time data of the power plant operation, including the actual cooling tower inlet water temperature Twin and the actual cooling tower outlet water temperature Twout; The wet-bulb temperature of the air entering the tower is obtained and iteratively calculated based on the meteorological data; The cooling tower characteristic parameter monitoring module iteratively calculates the small parameters of the cooling tower based on the iterative calculation of the wind speed in the tower, including the first cooling tower characteristic parameter, cooling tower cooling amplitude, cooling tower efficiency, and performs real-time monitoring of the cooling tower characteristics of the wet cooling unit.

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