Water power online scale control method and system for condenser

Abstract

The application discloses a water kinetic energy online scale removal control method and system of a condenser. The method comprises the following steps: collecting target condenser thermal operation parameters, circulating water flow rate, circulating water quality characteristic values and the rotating speed of a spiral scale removal device in a heat exchange tube; obtaining the scale thermal resistance of the heat exchange tube based on the condenser thermal operation parameters; constructing an optimal rotating speed interval model, taking the circulating water flow rate, the circulating water quality characteristic values and the scale thermal resistance as inputs, and solving the optimal rotating speed interval of the current spiral scale removal device; and matching the real-time flow rate of the circulating water for the spiral scale removal device based on the solved optimal rotating speed interval, so that the real-time rotating speed of the spiral scale removal device falls within the optimal rotating speed interval. The application can make the spiral scale removal device work in the optimal rotating speed interval, and balance the scale removal effect and energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of online descaling technology for condensers, and particularly relates to a water-energy-based online descaling control method and system for condensers. Background Technology

[0002] The condenser is the core equipment of the cold-end system of a steam turbine generator set. Its heat exchange efficiency directly determines key economic indicators such as the condensing vacuum and heat exchange terminal temperature difference of the unit, thereby affecting the unit's power generation efficiency, energy consumption level, and operational safety. Industry operating data shows that for every 1°C increase in terminal temperature due to fouling on the condenser heat exchange tubes, the unit's coal consumption will increase by approximately 1.5%-2%, and the power generation will decrease by approximately 0.8%-1%.

[0003] In blast furnace gas generator units supporting the steel industry, as well as thermal power units that use surface water as circulating water makeup, the circulating water has high hardness and turbidity. Moreover, the circulating water is in laminar flow under normal operating conditions in the condenser heat exchange tubes, and a boundary water film with a near-zero flow velocity is easily formed at the tube wall. Calcium and magnesium ions and suspended solids in the water are very easy to deposit on the tube wall to form scale, which not only greatly reduces heat exchange efficiency, but also causes under-deposit corrosion, and in severe cases, leads to heat exchange tube leakage and unplanned unit shutdown.

[0004] Traditional offline cleaning technologies include chemical cleaning and high-pressure water jet cleaning. These solutions require the unit to be shut down and are typically carried out once every 1-2 years. Although they can thoroughly remove scale from the heat exchange tubes, the cleaning requires a complete shutdown of the unit, which occupies the unit's effective power generation time. Especially for blast furnace gas generator units, shutdown cleaning will lead to the release of blast furnace gas, resulting in energy waste and environmental pressure. In addition, chemical cleaning is prone to causing corrosion damage to the heat exchange tubes, shortening their service life. At the same time, the cleaning waste liquid has the problems of high environmental treatment costs and high compliance risks.

[0005] The passive water-powered spiral descaling device is a new type of online descaling technology developed in recent years. Its principle is to arrange a spiral ribbon structure inside the heat exchange tube. The spiral device is driven to rotate by the kinetic energy of the circulating water itself, which changes the water flow in the tube from laminar flow to turbulent flow, destroys the boundary layer of scale formation, and realizes online descaling without stopping the machine, without the need for an external power source.

[0006] However, deep peak shaving has become the norm in the thermal power industry. The unit load usually fluctuates frequently in the range of 20%-100% of the rated load. The circulating water flow rate and velocity change significantly with the load. Under low load conditions, the water flow rate is insufficient, and the speed of the spiral device is below the critical descaling threshold, which cannot effectively eliminate the laminar boundary layer, and the descaling effect is completely ineffective. Under high load conditions, the water flow rate is too high, and the speed of the spiral device exceeds the reasonable range, which leads to a quadratic increase in the flow resistance in the heat exchange tubes. The power consumption of the circulating water pump increases significantly, and the power generation benefits brought by descaling are completely offset by the additional power consumption, or even result in negative benefits. Summary of the Invention

[0007] The purpose of this invention is to provide a method and system for online descaling control of condensers using water kinetic energy, which partially solves or alleviates the above-mentioned deficiencies in the prior art, enabling the spiral descaling device to operate in the optimal speed range and balancing the descaling effect and energy consumption.

[0008] To solve the aforementioned technical problems, the present invention specifically adopts the following technical solution: A first aspect of the present invention is to provide a method for online descaling control of a condenser using water kinetic energy, applicable to a condenser with a passive spiral descaling device installed inside the heat exchange tubes, comprising: Collect the thermal operating parameters of the target condenser, the circulating water flow rate, the characteristic values ​​of the circulating water quality, and the rotation speed of the spiral descaling device inside the heat exchange tubes; Based on the condenser thermal operating parameters, the fouling thermal resistance of the heat exchange tubes is obtained; the condenser thermal operating parameters include the steam-side condensation heat transfer coefficient, the water-side convection heat transfer coefficient, the heat exchange tube wall thermal resistance, the total heat exchange tube area, the logarithmic mean temperature difference, the real-time steam flow rate, the condenser exhaust enthalpy, and the condensate enthalpy. An optimal speed range model is constructed, and the optimal speed range of the current spiral descaling device is obtained by solving the problem using circulating water flow rate, circulating water quality characteristic value, and fouling thermal resistance as inputs. Based on the optimal speed range obtained from the solution, the real-time flow rate of circulating water is matched to the spiral descaling device so that the real-time speed of the spiral descaling device falls within the optimal speed range.

[0009] Furthermore, the method for obtaining the fouling thermal resistance of the heat exchange tube is to use the formula:

[0010] Calculate the fouling thermal resistance of the heat exchanger tubes; where R f For fouling thermal resistance, K total Let α be the overall heat transfer coefficient of the condenser. o α is the condensation heat transfer coefficient on the steam side. i R is the water-side convective heat transfer coefficient. p The thermal resistance of the heat exchange tube wall; The overall heat transfer coefficient of the condenser is calculated using the following formula:

[0011] Calculate; where Φ is the total heat transfer of the condenser, A is the total heat transfer area of ​​the heat exchange tubes, and ΔT m The logarithmic mean temperature difference; The formula for the total heat transfer utilization of the condenser is as follows: Φ=D*(h s -h c ) Calculate; where D is the steam flow rate, hs For the enthalpy of condenser exhaust steam, h c This refers to the enthalpy of condensation.

[0012] Furthermore, a Kalman filter algorithm is used to remove non-fouling interference from the fouling thermal resistance.

[0013] Furthermore, the optimal speed range model includes: Optimize the objective function: minF loss (t)=c*n s (t) 2 *v(t) 2 ; Where F loss (t) represents the flow resistance loss caused by the spiral descaling device, c is the flow resistance coefficient, and n s (t) represents the real-time rotational speed of the spiral descaling device, and v(t) represents the real-time flow rate of the circulating water; The constraints are: F clean (t)≥F set； Where F clean (t) is the real-time descaling effect evaluation function, F set This is the preset minimum threshold for cleaning effectiveness; The real-time descaling effect evaluation function satisfies:

[0014] Where k1, k2, and k3 are preset weighting coefficients, Rf(t) is the real-time fouling thermal resistance, and W(t) is the characteristic value of circulating water quality.

[0015] Furthermore, it also includes: Predict the fouling thermal resistance using current and historical data; If the predicted fouling thermal resistance exceeds the preset fouling warning threshold, the preset minimum fouling effect threshold in the optimal speed range model is increased, and the upper limit of the optimal speed range is expanded.

[0016] Furthermore, an LSTM time-series prediction model based on attention mechanism optimization is constructed, using historical operating data and real-time fouling status characteristics for a preset duration as input to the model, thereby predicting the fouling thermal resistance within a preset early warning period.

[0017] Furthermore, the NSGA-III multi-objective genetic algorithm is used to solve the Pareto optimal solution set of the optimal speed range model, and the optimal speed range under the current operating conditions is obtained by screening.

[0018] Furthermore, the method for matching the real-time flow rate of circulating water to the spiral descaling device is to use the following formula: v=p*n s / (C*60); Calculate the circulating water velocity; where n s denoted as rotational speed, v as circulating water flow rate, p as screw pitch of the spiral descaling device, and C as rotational speed correction coefficient.

[0019] Furthermore, the speed correction coefficient is calculated using the following formula: C = C0 * C1 * C2 * C3 Calculation; where C0 is the reference speed correction factor, C1 is the scaling condition correction factor, C2 is the water quality and Reynolds number correction factor, and C3 is the equipment health condition correction factor.

[0020] This invention also provides a water-powered online descaling control system for condensers, comprising: The parameter acquisition module is used to collect the thermal operating parameters of the target condenser, the circulating water flow rate, the characteristic values ​​of the circulating water quality, and the rotation speed of the spiral descaling device in the heat exchange tubes. The fouling thermal resistance calculation module is used to obtain the fouling thermal resistance of the heat exchange tubes based on the condenser thermal operating parameters. The condenser thermal operating parameters include the steam-side condensation heat transfer coefficient, the water-side convection heat transfer coefficient, the heat exchange tube wall thermal resistance, the total heat exchange tube area, the logarithmic mean temperature difference, the real-time flow rate of the main steam, the condenser exhaust enthalpy, and the enthalpy of the condensate. The optimal speed range acquisition module is used to construct the optimal speed range model. Taking the circulating water flow rate, circulating water quality characteristic value, and fouling thermal resistance as inputs, it solves to obtain the optimal speed range of the current spiral descaling device. The conversion module is used to match the real-time flow rate of circulating water to the spiral descaling device based on the optimal speed range obtained by the solution, so that the real-time speed of the spiral descaling device falls within the optimal speed range.

[0021] Beneficial effects: This invention, based on the hydrodynamic driving characteristics of a passive spiral descaling device, constructs a dual-objective optimization model with the core objectives of minimizing flow resistance loss and ensuring the descaling effect meets standards. It combines this with the NSGA-III multi-objective genetic algorithm to solve for the globally optimal speed range, and achieves precise conversion from the optimal speed range to the circulating water flow rate through a multi-dimensional dynamically corrected speed-flow velocity coupled engineering model. Compared to existing passive descaling devices with fixed structures and fixed speed ranges, this invention is adaptable to the deep peak-shaving operation range of thermal power units from 20% to 100% of their rated load. It resolves the contradiction between descaling failure due to insufficient water flow rate under low-load conditions and the contradiction between the sudden increase in flow resistance and the waste of circulating water pump power consumption due to excessively high speed under high-load conditions.

[0022] This invention, based on the condenser thermal balance principle and total thermal resistance decomposition model, accurately separates the real-time fouling thermal resistance of heat exchange tubes. It then uses a Kalman filter algorithm to completely eliminate non-scaling interferences such as unit load fluctuations, sudden changes in circulating water temperature, vacuum system leaks, and sensor measurement noise. This solves the industry problem of existing technologies that can only indirectly judge scaling through macroscopic indicators such as terminal temperature difference and vacuum degree, suffer from severe coupling of interference factors, and have significant lag in scaling judgment. Simultaneously, this invention, through an attention-mechanism-optimized LSTM time-series prediction model, can achieve advanced prediction of scaling trends 7-30 days in advance, triggering enhanced scaling removal strategies ahead of time. This fundamentally inhibits the formation and deposition of scale, completely eliminating problems such as condenser vacuum deterioration and increased terminal temperature difference caused by scaling. After implementation, the condenser terminal temperature difference can be stably controlled within 3°C for a long period, ensuring the unit operates in optimal economic condition throughout its entire operating cycle. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. The elements or parts in the drawings are not necessarily drawn to scale. Obviously, the drawings described below are some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0024] Figure 1 This is a flowchart of the present invention; Figure 2 This is a structural diagram of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] In this document, suffixes such as "module," "part," or "unit" used to denote elements are used only for the purpose of illustrative purposes and have no specific meaning in themselves. Therefore, "module," "part," or "unit" may be used interchangeably.

[0027] In this document, the terms "upper," "lower," "inner," "outer," "front," "rear," "one end," and "the other end," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the present invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0028] In this document, unless otherwise explicitly specified and limited, the terms "installed," "equipped with," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0029] In this document, "and / or" includes any and all combinations of one or more of the listed related items.

[0030] In this article, "multiple" means two or more, that is, it includes two, three, four, five, etc.

[0031] Example 1: like Figure 1 As shown, this embodiment provides a method for online descaling control of a condenser using water kinetic energy, applied to a condenser with a passive spiral descaling device installed inside the heat exchange tubes. The specific steps include: S1 collects real-time thermal operating parameters of the target condenser, circulating water flow rate, circulating water quality characteristics, and rotational speed of the spiral descaling device inside the heat exchange tubes. The condenser thermal operating parameters include the steam-side condensation heat transfer coefficient, the water-side convective heat transfer coefficient, the heat exchange tube wall thermal resistance, the total heat exchange tube area, the logarithmic mean temperature difference, the real-time steam flow rate, the condenser exhaust enthalpy, and the condensate enthalpy.

[0032] In this embodiment, the condenser thermal operating parameters are collected in real time through the power plant's DCS system, including the steam-side condensation heat transfer coefficient α. o Water-side convective heat transfer coefficient α i The thermal resistance R of the heat exchange tube wall p Total heat exchange area A of heat exchange tubes; Logarithmic mean temperature difference ΔT m Real-time steam flow rate of steam turbine (D), enthalpy of condenser exhaust steam (h) s enthalpy of condensate h c Among them, the steam-side condensation heat transfer coefficient α o Fixed values ​​for condenser design are provided by the equipment manufacturer; heat exchanger tube wall thermal resistance R pThe constant is calculated based on the heat exchanger tube material, wall thickness, and thermal conductivity; the condenser exhaust enthalpy hs and condensate enthalpy hc are calculated in real time using the corresponding pressure and temperature collected by the DCS system through the IAPWS-IF97 water and steam thermodynamic property tables; the logarithmic mean temperature difference ΔT m The circulating water inlet temperature, circulating water outlet temperature, and condenser exhaust temperature are collected by the DCS system and calculated in real time.

[0033] The circulating water velocity v is calculated by combining the total circulating water flow rate Q collected by the DCS system with the number of heat exchange tubes n and the inner diameter d of the heat exchange tubes in a single process.

[0034] The circulating water quality characteristic value W(t) is obtained by weighted calculation after normalization of the circulating water turbidity, hardness and conductivity collected by online water quality monitoring instruments. The value ranges from 0 to 1. The larger the value, the worse the water quality and the higher the risk of scaling.

[0035] Real-time rotation speed n of the passive spiral descaling device s In this embodiment, the average speed of all spiral devices in the heat exchange tubes is taken as the real-time speed for overall control by collecting data in real time through passive RFID speed tags. At the same time, the speed data of individual devices is stored for fault diagnosis.

[0036] S2 obtains the fouling thermal resistance of the heat exchange tubes based on the thermal operating parameters of the condenser.

[0037] Based on the condenser thermal operating parameters collected in step S1, the total heat transfer and total heat transfer coefficient of the condenser are calculated sequentially. Finally, the real-time fouling thermal resistance of the heat exchange tubes is obtained, and non-fouling interference is eliminated using a Kalman filter algorithm. The specific steps are as follows: S21 calculates the total heat transfer Φ of the condenser using the following formula: Φ=D*(h s -h c ); Where D is the steam flow rate, h s For the enthalpy of condenser exhaust steam, h c This refers to the enthalpy of condensation.

[0038] S22 Calculate the overall heat transfer coefficient K of the condenser. total The calculation formula is:

[0039] Where Φ is the total heat transfer of the condenser, A is the total heat transfer area of ​​the heat exchange tubes, and ΔT m The temperature difference is the logarithmic mean.

[0040] S23 separates the real-time fouling thermal resistance Rf of the heat exchange tube, and the calculation formula is:

[0041] Among them, R f For fouling thermal resistance, K total Let α be the overall heat transfer coefficient of the condenser. o α is the condensation heat transfer coefficient on the steam side. i R is the water-side convective heat transfer coefficient. p This refers to the thermal resistance of the heat exchange tube wall.

[0042] S24 uses a Kalman filter algorithm to remove non-fouling interference from the fouling thermal resistance.

[0043] In this embodiment, a Kalman filter algorithm is used to remove non-scaling interferences from the fouling thermal resistance, including unit load fluctuations, sudden changes in circulating water temperature, vacuum system leaks, and sensor measurement noise, to obtain the clean fouling thermal resistance corresponding only to pipe wall scaling. Kalman filtering is existing technology and will not be described in detail in this invention.

[0044] S3 constructs an optimal speed range model, using circulating water flow rate, circulating water quality characteristics, and fouling thermal resistance as inputs, to solve for the optimal speed range of the current spiral descaling device.

[0045] The purpose of this step is to construct an optimal speed range model. Using the circulating water flow velocity v and circulating water quality characteristic value W(t) collected in step S1, and the real-time fouling thermal resistance Rf(t) output in step S2 as inputs, the optimal speed range of the passive spiral descaling device under the current operating conditions is obtained [n]. s_min ,n s_max The specific implementation method is as follows: A dual-objective optimization model is constructed, with minimizing flow resistance loss as the optimization objective and achieving the required descaling effect as the constraint condition, as detailed below: Optimize objective function: minF loss (t)=c*n s (t) 2 *v(t) 2 ; Where F loss (t) represents the flow resistance loss caused by the spiral descaling device, c is the flow resistance coefficient, and n s (t) represents the real-time rotational speed of the spiral descaling device, and v(t) represents the real-time flow rate of the circulating water.

[0046] The constraints are: F clean (t)≥F set； Where F clean (t) is the real-time descaling effect evaluation function, F set This is the preset minimum threshold for cleaning effectiveness; The real-time descaling effect evaluation function satisfies:

[0047] Where k1, k2, and k3 are preset weighting coefficients, Rf(t) is the real-time fouling thermal resistance, and W(t) is the characteristic value of circulating water quality.

[0048] In this embodiment, the NSGA-III multi-objective genetic algorithm is used to solve the Pareto optimal solution set of the optimal speed range model. The population size is set to 100, the number of iterations is set to 50, the crossover probability is 0.8, and the mutation probability is 0.1. After obtaining the Pareto optimal solution set, the fuzzy membership function method is used to screen out the compromise solution that balances the minimum flow resistance loss and the optimal descaling effect, and finally the optimal speed range [n] under the current operating conditions is obtained. s_min ,n s_max ].

[0049] S4 Scaling Trend Prediction and Preventive Scaling Removal.

[0050] An attention-based optimized LSTM time-series prediction model was constructed, using historical operating data and real-time fouling status characteristics for a preset duration as input to predict fouling thermal resistance within a preset warning period. The model structure includes an input layer, two LSTM layers, an attention mechanism layer, a fully connected layer, and an output layer. The model was trained and validated using historical operating data from the generating unit.

[0051] When the fouling thermal resistance predicted by the model at any future time point exceeds the preset fouling warning threshold, an enhanced descaling trigger signal is generated, increasing the preset minimum descaling effect threshold F in the optimal speed range model. set Furthermore, the upper limit of the optimal speed range is expanded to enhance the turbulence intensity inside the pipe and achieve preventive descaling. In this embodiment, the descaling warning threshold is set to twice the baseline fouling thermal resistance of the clean pipe.

[0052] Based on the optimal speed range obtained from the solution, S5 matches the real-time flow rate of circulating water to the spiral descaling device, so that the real-time speed of the spiral descaling device falls within the optimal speed range.

[0053] The purpose of this step is to address the optimal speed range [n] obtained in step S3. s_min ,n s_max To match the real-time flow rate of the circulating water to the passive spiral descaling device, ensuring that the real-time rotational speed of the spiral descaling device remains stable within the optimal speed range, the specific implementation method is as follows: S51 constructs a rotational speed-flow velocity coupled engineering model based on the hydrodynamic driving characteristics of the passive spiral descaling device. The model formula is as follows: v=p*n s / (C*60); Where, n sdenoted as rotational speed, v as circulating water flow rate, p as screw pitch of the spiral descaling device, and C as rotational speed correction coefficient.

[0054] S52 calculates the real-time speed correction coefficient C using the following formula: C = C0 * C1 * C2 * C3 Wherein, C0 is the reference speed correction factor, C1 is the scaling condition correction factor, C2 is the water quality and Reynolds number correction factor, and C3 is the equipment health condition correction factor.

[0055] The calculation and calibration methods for each coefficient are as follows: The reference speed correction factor C0 is calibrated under steady-state rated operating conditions of the condenser clean tube, with the rated flow velocity of the circulating water v0 fixed and the stable operating speed n of the spiral descaling device collected. s0 Substituting into the rotational speed-flow velocity coupling model, the calculation yields... ; The fouling condition correction factor C1 is calculated based on real-time fouling thermal resistance, and the formula is as follows: ; Among them, R f_base R is the baseline fouling thermal resistance for clean tubing. f_filtered The output of step S2 is the filtered clean dirt thermal resistance.

[0056] The formula for calculating the water quality and Reynolds number correction factor C2 is as follows:

[0057] Where R e0 R is the reference Reynolds number under rated operating conditions. e k is the real-time Reynolds number of the circulating water. w This is the water quality correction factor, calculated by normalizing the turbidity and hardness of the circulating water, with a value range of 0.8-1.0.

[0058] Under normal operating conditions, the health status correction coefficient of the device is C3=1; when the spiral descaling device experiences jamming, debris entanglement, or blade deformation, the correction coefficient is reduced according to the fault level, with a reduction range of 0.3-0.9.

[0059] The conversion from the optimal speed range of S53 to the circulating water flow rate.

[0060] Substituting the rotational speed-flow velocity coupling model into the upper and lower limits of the optimal rotational speed range, the target flow velocity control range of the circulating water [v] is calculated. t_min ,v t_max ]. S54 circulating water flow rate matching control.

[0061] The calculated target flow velocity control range [v t_min ,vt_max The input is sent to the variable frequency control system of the circulating water pump. By adjusting the operating frequency of the circulating water pump, the total flow rate of the circulating water is adjusted so that the real-time flow rate of the circulating water in the heat exchange tube is stably within the target flow rate control range, thereby making the real-time speed of the passive spiral descaling device stably within the optimal speed range.

[0062] S55 closed-loop verification and iterative optimization.

[0063] The actual operating speed of the spiral descaling device is collected by passive RFID tags, and the speed deviation rate δ is calculated by comparing it with the optimal speed range. The formula is as follows:

[0064] Where n s_actual n represents the actual operating speed. s_mid The median of the optimal speed range is used; the preset deviation threshold is 5%. When δ>5%, it is determined to be a conversion deviation. The real-time speed correction coefficient C is automatically updated iteratively, and the target flow velocity range is recalculated until the speed deviation rate is controlled within 5%. The real-time fouling thermal resistance is updated synchronously, and the change rate of fouling thermal resistance before and after the iteration is compared. When the decrease rate of fouling thermal resistance is lower than the preset fouling efficiency threshold, the optimal speed range is re-solved, and the flow rate conversion and matching are performed again to form a complete adaptive closed-loop control.

[0065] Example 2: like Figure 2 As shown, this embodiment provides a water-powered online descaling control system for a condenser, including: The parameter acquisition module is used to collect the thermal operating parameters of the target condenser, the circulating water flow rate, the characteristic values ​​of the circulating water quality, and the rotation speed of the spiral descaling device in the heat exchange tubes. The fouling thermal resistance calculation module is used to obtain the fouling thermal resistance of the heat exchange tubes based on the condenser thermal operating parameters. The condenser thermal operating parameters include the steam-side condensation heat transfer coefficient, the water-side convection heat transfer coefficient, the heat exchange tube wall thermal resistance, the total heat exchange tube area, the logarithmic mean temperature difference, the real-time flow rate of the main steam, the condenser exhaust enthalpy, and the enthalpy of the condensate. The optimal speed range acquisition module is used to construct the optimal speed range model. Taking the circulating water flow rate, circulating water quality characteristic value, and fouling thermal resistance as inputs, it solves to obtain the optimal speed range of the current spiral descaling device. The conversion module is used to match the real-time flow rate of circulating water to the spiral descaling device based on the optimal speed range obtained by the solution, so that the real-time speed of the spiral descaling device falls within the optimal speed range.

[0066] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a computer terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0068] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for online descaling control of a condenser using water kinetic energy, applied to a condenser with a passive spiral descaling device installed inside the heat exchange tubes, characterized in that, include: Collect the target condenser thermal operating parameters, circulating water flow rate, circulating water quality characteristics, and rotation speed of the spiral descaling device inside the heat exchange tubes; the condenser thermal operating parameters include steam-side condensation heat transfer coefficient, water-side convective heat transfer coefficient, heat exchange tube wall thermal resistance, total heat exchange tube area, logarithmic mean temperature difference, real-time steam flow rate, condenser exhaust enthalpy, and condensate enthalpy. Based on the condenser thermal operating parameters, the fouling thermal resistance of the heat exchange tubes is obtained. An optimal speed range model is constructed, and the optimal speed range of the current spiral descaling device is obtained by solving the problem using circulating water flow rate, circulating water quality characteristic value, and fouling thermal resistance as inputs. Based on the optimal speed range obtained from the solution, the real-time flow rate of circulating water is matched to the spiral descaling device so that the real-time speed of the spiral descaling device falls within the optimal speed range.

2. The method for online descaling control of a condenser using water kinetic energy according to claim 1, characterized in that, The method for obtaining the fouling thermal resistance of heat exchange tubes is to use the formula: Calculate the fouling thermal resistance of the heat exchanger tubes; where R f For fouling thermal resistance, K total Let α be the overall heat transfer coefficient of the condenser. o α is the condensation heat transfer coefficient on the steam side. i R is the water-side convective heat transfer coefficient. p The thermal resistance of the heat exchange tube wall; The overall heat transfer coefficient of the condenser is calculated using the following formula: Calculate; where Φ is the total heat transfer of the condenser, A is the total heat transfer area of ​​the heat exchange tubes, and ΔT m The logarithmic mean temperature difference; The formula for the total heat transfer utilization of the condenser is as follows: Φ=D*(h s -h c ) Calculate; where D is the steam flow rate, h s For the enthalpy of condenser exhaust steam, h c It is the enthalpy of condensation.

3. The method for online descaling control of a condenser using water kinetic energy according to claim 2, characterized in that, The Kalman filter algorithm is used to remove non-fouling interference from the fouling thermal resistance.

4. The method for online descaling control of a condenser using water kinetic energy according to claim 1, characterized in that, The optimal speed range model includes: Optimize the objective function: minF loss (t)=c*n s (t) 2 *v(t) 2 ; Where F loss (t) represents the flow resistance loss caused by the spiral descaling device, c is the flow resistance coefficient, and n s (t) represents the real-time rotational speed of the spiral descaling device, and v(t) represents the real-time flow rate of the circulating water; The constraints are: F clean (t)≥F set； Where F clean (t) is the real-time descaling effect evaluation function, F set This is the preset minimum threshold for cleaning effectiveness; The real-time descaling effect evaluation function satisfies: Where k1, k2, and k3 are preset weighting coefficients, Rf(t) is the real-time fouling thermal resistance, and W(t) is the characteristic value of circulating water quality.

5. The method for online descaling control of a condenser using water kinetic energy according to claim 1, characterized in that, Also includes: Predict the fouling thermal resistance using current and historical data; If the predicted fouling thermal resistance exceeds the preset fouling warning threshold, the preset minimum fouling effect threshold in the optimal speed range model is increased, and the upper limit of the optimal speed range is expanded.

6. The method for online descaling control of a condenser based on water kinetic energy according to claim 5, characterized in that, An LSTM time-series prediction model based on attention mechanism optimization is constructed. The model is input with historical operating data and real-time fouling status characteristics for a preset duration, so as to predict the fouling thermal resistance within a preset early warning period.

7. The method for online descaling control of a condenser using water kinetic energy according to claim 1, characterized in that, The NSGA-III multi-objective genetic algorithm is used to solve the Pareto optimal solution set of the optimal speed range model, and the optimal speed range under the current operating conditions is obtained by screening.

8. The method for online descaling control of a condenser using water kinetic energy according to claim 1, characterized in that, The method for matching the real-time flow rate of circulating water to the spiral descaling device is to use the following formula: v=p*n s / (C*60); Calculate the circulating water velocity; where n s denoted as rotational speed, v as circulating water flow rate, p as screw pitch of the spiral descaling device, and C as rotational speed correction coefficient.

9. The method for online descaling control of a condenser based on water kinetic energy according to claim 8, characterized in that, The speed correction coefficient is calculated using the following formula: C = C0 * C1 * C2 * C3 Calculation; where C0 is the reference speed correction factor, C1 is the scaling condition correction factor, C2 is the water quality and Reynolds number correction factor, and C3 is the equipment health condition correction factor.

10. A water-powered online descaling control system for a condenser, characterized in that, include: The parameter acquisition module is used to collect the thermal operating parameters of the target condenser, the circulating water flow rate, the characteristic values ​​of the circulating water quality, and the rotation speed of the spiral descaling device in the heat exchange tubes. The fouling thermal resistance calculation module is used to obtain the fouling thermal resistance of the heat exchange tubes based on the condenser thermal operating parameters. The condenser thermal operating parameters include the steam-side condensation heat transfer coefficient, the water-side convection heat transfer coefficient, the heat exchange tube wall thermal resistance, the total heat exchange tube area, the logarithmic mean temperature difference, the real-time flow rate of the main steam, the condenser exhaust enthalpy, and the enthalpy of the condensate. The optimal speed range acquisition module is used to construct the optimal speed range model. Taking the circulating water flow rate, circulating water quality characteristic value, and fouling thermal resistance as inputs, it solves to obtain the optimal speed range of the current spiral descaling device. The conversion module is used to match the real-time flow rate of circulating water to the spiral descaling device based on the optimal speed range obtained by the solution, so that the real-time speed of the spiral descaling device falls within the optimal speed range.

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