Power plant circulating water anti-freezing system suitable for cold region

Abstract

The invention relates to the technical field of circulating water anti-freezing, and discloses a power plant circulating water anti-freezing system suitable for a cold region, and the system comprises a temperature sensing module, an anti-freezing heating module, a water flow disturbance module, an ice layer processing module, an intelligent regulation and control center and a fault safety module; when the circulating water system of the power plant operates in a cold region, the internal water temperature and external environment parameters of key nodes of a circulating water pipe network are monitored in real time, and a low-temperature early warning signal is generated based on a temperature field reconstruction algorithm of machine learning, so that abnormal temperature fluctuation can be recognized in time, early warning delay and false alarm caused by wind speed and humidity interference are avoided, and the working efficiency is improved. And in the circulating water anti-freezing process, the output power of the flexible electric heating body is dynamically adjusted through a graded heating mechanism, and the turbulence generator is linked to optimize water flow distribution, adapt to thermal inertia change of a pipeline and prevent the risk of local icing caused by sudden temperature drop.

Description

Technical Field

[0001] The invention relates to the technical field of circulating water antifreeze, and in particular to a power plant circulating water antifreeze system suitable for cold regions. Background Art

[0002] There are two main types of circulating water: industrial and domestic. Both are primarily used to conserve water. Industrial circulating water is primarily used in cooling water systems, hence the name "circulating cooling water." Circulating cooling water systems are a crucial component of power plants, and their antifreeze performance is directly linked to the safety and efficiency of the plant's operations. They are crucial infrastructure for maintaining stable operation.

[0003] At present, since the circulating water antifreeze systems of power plants in cold regions operate in extremely low temperature environments, the distributed sensors in the temperature sensing module cannot eliminate the interference of ambient wind speed and humidity fluctuations on temperature data in real time when monitoring water temperature changes. When the sensor data deviates due to strong wind heat dissipation and frost, it will cause low temperature warning signal delays and false alarms, and the accuracy and timeliness of the warning cannot be guaranteed.

[0004] Therefore, a power plant circulating water antifreeze system suitable for cold areas is proposed to solve the above problems. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a power plant circulating water antifreeze system suitable for cold areas. The power plant circulating water antifreeze system provided by the present invention solves the problems of low temperature warning signal delay and false alarm, and the inability to ensure the accuracy and timeliness of the warning raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solutions: a power plant circulating water antifreeze system suitable for cold regions, the system comprising: The temperature sensing module collects the internal water temperature and external ambient temperature parameters of key nodes in the circulating water network in real time. When the internal water temperature falls below the preset temperature threshold, a low temperature warning signal is generated and output to the antifreeze heating module; The antifreeze heating module activates a hierarchical heating mechanism upon receiving the low temperature warning signal, performs contact heat conduction on the circulating water through a flexible electric heating body, and generates a disturbance activation instruction based on the internal temperature change rate and outputs it to the water flow disturbance module; a water flow disturbance module, which activates a turbulence generator in response to the disturbance activation instruction, prevents local icing by periodically adjusting the flow velocity distribution, and feeds back pipeline flow state data to the ice layer processing module; An ice layer processing module receives the pipeline flow data and uses ice layer detection technology to detect the thickness of the ice layer on the pipe wall. When the ice layer thickness is greater than or equal to its safety limit, it triggers a mechanical scraping and high-frequency oscillation collaborative ablation operation, and simultaneously uploads ice layer status parameters to the intelligent control center; The intelligent control center integrates meteorological prediction data, ice layer state parameters and real-time operation parameters, constructs a pipe network thermodynamic model and dynamically generates optimal heating strategy instructions, disturbance frequency instructions and ice layer processing timing instructions, which are fed back to the anti-freezing heating module, water flow disturbance module and ice layer processing module, respectively. The fault safety module automatically isolates the fault pipe section and switches to the standby circulation channel when detecting abnormal sudden drop of local pipe temperature, and sends corresponding state alarm information to the intelligent control center.

[0007] Preferably, the temperature sensing module comprises: A distributed temperature sensor array is arranged equidistantly along the axial direction of the circulating water pipe network, covering straight pipe sections, elbows and valve connections. An environmental parameter acquisition unit is installed on the outer wall of the pipe to synchronously obtain wind speed and humidity data. A temperature field reconstruction algorithm based on machine learning is used to deduce the real-time temperature distribution of the entire pipe network according to sparse monitoring point data.

[0008] Preferably, the hierarchical heating mechanism of the anti-freezing heating module comprises: Primary heating mode: when the water temperature is in the range of 0℃ to -5℃, start the basic heat preservation power to maintain the water temperature. Secondary heating mode: when the water temperature is lower than -5℃ and the temperature drop rate exceeds 0.5℃ / min, enable the stepwise power-up strategy until the temperature rises to the safe range, and the power adjustment follows the following linear control law: ; Wherein is the real-time heating power, is the power-temperature proportional coefficient, is the difference between the current water temperature and the freezing point, is the basic power offset; Tertiary heating mode: when the ambient temperature is continuously lower than -15℃ for more than 2 hours, switch to full power operation and coordinate the water flow disturbance module to enhance heat exchange efficiency.

[0009] Preferably, the flexible electric heating body adopts a multi-layer composite structure, comprising: A heat-conducting silicone layer adhered to the outer wall of the pipe; A network of carbon nanotube heating wires embedded in the heat-conducting silicone layer, whose topological distribution density is self-adaptively adjusted according to the pipe curvature; An insulating reflective film covering the surface layer to reduce heat loss to the environment.

[0010] Preferably, the water flow disturbance module comprises a turbulence generator. An array of micro-vortex blades installed on the inner wall of the pipe is driven by a servo motor to generate swirling flow; The throttle valve group with adjustable aperture periodically changes the local flow cross-sectional area to form a pulsed water flow impact; The disturbance frequency and amplitude are optimized based on the CFD computational fluid dynamics model to ensure full antifreeze coverage at the lowest energy consumption.

[0011] Preferably, the activation logic of the turbulence generator is: When the heating power is increased to level 2 or above, the blade rotation frequency is automatically matched as a function of the heating power; When it is detected that the standard deviation of the water temperature distribution exceeds 0.8°C, the throttle valve group is started to perform regional flow rate correction.

[0012] Preferably, the collaborative ablation operation of the ice layer processing module includes: Mechanical scraping unit: A retractable blade driven by a memory alloy propels the blade axially along the inner wall of the pipe to physically remove the attached ice layer. High-frequency oscillator: emits 20-40kHz ultrasonic waves during the scraping operation, inducing resonance and fragmentation of the ice crystal structure; Negative pressure recovery device: real-time suction of peeled ice chips to prevent secondary condensation.

[0013] Preferably, the ice detection technology includes: Three sets of probes are distributed 120° around the key nodes of the pipeline for ice detection; Time domain reflectometry is used to measure ice thickness with a resolution of 0.1 mm; Establish an ice thickness growth prediction model and combine it with historical icing data to predict the timing of starting de-icing operations.

[0014] Preferably, the operation optimization method of the intelligent control center includes: Access to 72-hour cold wave warning data issued by the Meteorological Observatory; Construct a thermal inertia matrix for the pipe network to quantify the heat capacity and heat dissipation characteristics of different pipe sections; A heating-disturbance-deicing coordinated strategy is dynamically generated through a reinforcement learning algorithm. The objective function is the Pareto optimality of maximizing antifreeze reliability and minimizing energy consumption. The optimization objective is defined by the following function: ; in, To comprehensively optimize the target value, is the antifreeze reliability weight, is the energy efficiency weight, is the antifreeze reliability index, is the total energy consumption of the system.

[0015] Preferably, the fail-safe module specifically includes: Fail-safe mechanism: When the system detects that the temperature of a local pipe section drops abnormally and exceeds the preset safety tolerance threshold, it automatically isolates the pipe section and activates the backup circulation channel; Energy recovery unit: Utilizes low-temperature water generated during the ablation process to conduct cascade heat exchange with waste heat from the power plant; Digital twin monitoring interface: Visualizes the real-time temperature field, ice distribution, and energy consumption data of the pipeline network, and supports manual strategy intervention.

[0016] Compared with the existing technology, the present invention provides a power plant circulating water antifreeze system suitable for cold regions, which has the following beneficial effects: 1. In the present invention, when the power plant circulating water system operates in cold areas, by real-time monitoring of the water temperature and ambient temperature at key nodes of the circulating water network and generating a low-temperature warning signal based on a temperature field reconstruction algorithm using machine learning, abnormal temperature fluctuations can be identified in a timely manner, warning delays and false alarms caused by wind speed and humidity interference can be avoided, the accuracy of low-temperature warnings and the timeliness of response can be improved, and the safe operation continuity of the system in extreme environments can be guaranteed.

[0017] 2. In the present invention, during the antifreeze process of circulating water, the output power of the flexible electric heater is dynamically adjusted through a graded heating mechanism, and the turbulence generator is linked to optimize the water flow distribution, adapt to the changes in the thermal inertia of the pipeline, and prevent the risk of local freezing caused by a sudden drop in temperature. At the same time, a real-time feedback mechanism is used to compensate for the heat conduction loss, ensure the coordinated efficiency of heating and disturbance operations, reduce the unplanned downtime rate and maintain stable operation of the equipment.

[0018] 3. In the present invention, in the overall control link of the system, the meteorological forecast data and real-time operating parameters are integrated through the intelligent control center to dynamically generate heating, disturbance and de-icing coordination strategies, and combined with the automatic isolation function of the fault safety mechanism, to achieve accurate matching of ice growth prediction and ablation operation, avoid ice debris residue and secondary icing problems, optimize anti-freeze reliability, improve energy utilization efficiency, and enhance the system's adaptability under complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a structural diagram of a power plant circulating water antifreeze system suitable for cold regions according to the present invention. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0021] Specific examples: Please refer to Figure 1 A circulating water antifreeze system for power plants in cold regions. The system architecture adopts a modular collaborative design and implements antifreeze through closed-loop control logic. Specifically, it includes: Temperature sensing module: As the system perception layer, it collects real-time data on the internal water temperature and external environmental parameters of key nodes in the circulating water network, including elbows, valves, and straight pipe sections that are prone to freezing. When the internal water temperature falls below the preset temperature threshold, it immediately generates a highly timely low-temperature warning signal and transmits it to the antifreeze heating module.

[0022] The antifreeze heating module, as one of the execution units, activates a pre-set, graded heating mechanism upon receiving a low-temperature warning signal. It utilizes a flexible electric heater for efficient contact heat transfer to the circulating water. It also possesses intelligent judgment capabilities, dynamically generating disturbance activation instructions based on the internal water temperature change rate and the monitored temperature drop rate. These instructions are then transmitted to the water flow disturbance module, triggering water flow intervention.

[0023] Water flow disturbance module: responds to the disturbance activation command from the antifreeze heating module, starts driving the turbulence generator, and periodically adjusts the velocity distribution of the water flow in the pipeline, including creating swirl and pulse flow, breaking the laminar flow state, ensuring sufficient mixing of the water body, and preventing the risk of local freezing caused by stagnant water flow; at the same time, the pipeline flow state data is fed back to the ice layer processing module.

[0024] Ice layer processing module: Receives pipeline flow data from the water flow disturbance module and uses ice layer detection technology to actively detect the thickness of the ice layer formed on the pipe wall. When the ice layer thickness is greater than or equal to its safety limit, it will affect the circulation and thermal insulation performance. At this time, a collaborative ablation operation combining physical mechanical scraping and high-frequency energy oscillation is immediately triggered to remove the ice layer. At the same time, key ice layer status parameters, including thickness, location, and growth trend, are uploaded to the intelligent control center. The ice layer status parameters specifically include: Ice thickness parameter: Time domain reflectometry is used to measure the ice thickness on the pipe wall. This parameter represents the actual physical thickness of the ice layer and is the key indicator for determining whether the ice layer exceeds the limit. When the thickness exceeds the safety threshold, the ablation operation is triggered. The measurement is based on three sets of probes distributed 120° around the key nodes of the pipeline, ensuring full circumference coverage without blind spots. Ice layer location parameter: This parameter indicates the specific location of the ice layer in the pipeline, including axial coordinates and circumferential distribution. This parameter is used to locate high-risk areas, guide the directional operation of mechanical scraping units and high-frequency oscillators, and avoid waste of ice removal resources. Ice growth trend parameters: These are generated by the ice thickness growth prediction model, including ice growth rate and predicted future ice conditions. This model combines real-time water temperature, flow rate, ambient temperature, and historical ice formation data to predict when to initiate de-icing operations and enable preventive intervention.

[0025] The Intelligent Control Center, the decision-making brain of the system, integrates multi-dimensional data sources, including external weather forecasts, internal ice state parameters, and real-time operating parameters, to construct a thermodynamic model of the pipeline network that reflects its actual thermodynamic characteristics. Based on this model, the Intelligent Control Center dynamically calculates and generates optimal control instructions in real time, including heating strategy instructions, disturbance frequency instructions, and de-icing timing instructions. These instructions are fed back to the antifreeze heating module, water flow disturbance module, and ice processing module, respectively, directing the coordinated operation of each execution module.

[0026] Fail-safe module: As a safety guarantee layer, it monitors the system operation status in real time. When it detects an abnormal drop in local pipeline temperature that exceeds the preset tolerance range, indicating a rupture or serious blockage, it immediately executes the emergency procedure: automatically isolate the faulty pipe section, cut off the water flow in the faulty pipe section, and switch to the preset backup circulation channel to ensure uninterrupted operation of the main system. At the same time, it sends corresponding detailed status alarm information to the intelligent control center.

[0027] The architecture and function of the temperature sensing module are to build a high-precision, full-coverage temperature monitoring network, including a distributed temperature sensor array, an environmental parameter acquisition unit, an environmental interference compensator, and a supporting temperature field reconstruction algorithm. Specifically: Distributed temperature sensor array: Using the principle of axially equidistant distribution, it is densely deployed throughout the circulating water network, focusing on covering weak links with complex thermodynamic characteristics and prone to freezing, including straight pipe sections where laminar low-temperature areas are prone to form, elbows where eddy currents are prone to heat dissipation, and valve connections where local low temperatures are prone to occur due to the structure.

[0028] Environmental parameter acquisition unit: installed at a specific location on the outer wall of the pipeline, it synchronously collects key environmental parameters that directly affect the heat dissipation of the pipeline, including ambient temperature, wind speed and humidity data. The ambient temperature determines the heat exchange rate between the pipeline and the environment, the wind speed affects the convective heat dissipation intensity, and the humidity affects the frost and condensation rates.

[0029] Environmental interference compensator: Receives raw data from distributed temperature sensors and environmental parameters, calculates air cooling deviation and frosting deviation through physical models, and outputs corrected water temperature. The specific compensation logic is as follows: ; in, The water temperature measured by the sensor is is the real-time wind speed, is the wind cooling coefficient, is the ambient humidity, is the critical humidity for frost formation, is the frost coefficient; The corrected data is input into the temperature field reconstruction algorithm to eliminate monitoring errors caused by environmental fluctuations; The temperature field reconstruction algorithm based on machine learning deduces the real-time temperature distribution of the entire pipeline network based on sparse monitoring point data: Based on machine learning technology, using a limited number of sensor node data from sparse monitoring points, the algorithm intelligently deduces and reconstructs the real-time, continuous temperature distribution map of the inner and outer surfaces of the entire pipeline network, overcoming the problem of limited physical sensor distribution and realizing global temperature visualization monitoring.

[0030] The tiered heating mechanism of the antifreeze heating module intelligently adjusts the heating power according to the severity of the frost damage risk: Level 1 heating mode, preventive insulation: When the water temperature is in the critical range near the freezing point, 0°C to -5°C, the risk of freezing begins to appear, and the system starts to activate the lowest power gear: basic insulation power. The main purpose is to maintain the water temperature stable and prevent it from dropping further. The energy consumption is relatively low.

[0031] Secondary heating mode, active heating: When the water temperature is below the -5°C safety line and the temperature drops rapidly at a rate exceeding 0.5°C / min, indicating a strong cold snap or sudden failure, the system will be judged as a high-risk state and immediately activate a step-by-step power increase strategy. Its power regulation follows the following linear control law: ;in, For real-time heating power, is the power-temperature proportionality coefficient, is the difference between the current water temperature and the freezing point, is the basic power offset; it can be seen that the real-time heating power increases linearly with the increase of temperature difference until the water temperature is pulled back to the safe range.

[0032] Three-level heating mode, full defense: When encountering continuous extreme cold, with the ambient temperature below -15°C and lasting for more than 2 hours, the system will determine it as the highest risk level, switch to the maximum power operation state, and actively link the water flow disturbance module to maximize heat exchange efficiency by enhancing water flow disturbance, ensuring that heat can be quickly and evenly transferred to all parts of the water body.

[0033] The flexible electric heater adopts a multi-layer composite structure design, which takes into account both efficient heat transfer and energy saving. It includes a thermal conductive silicone layer, a carbon nanotube heating wire network and an insulating reflective film. Specifically: Thermal conductive silicone layer: As the base layer, it fits directly and tightly to the outer wall of the pipe. Its high thermal conductivity and flexibility ensure low thermal resistance contact between the heating body and the pipe surface, maximizing heat transfer efficiency.

[0034] The carbon nanotube heating filament network serves as the core heating layer, embedded within the thermally conductive silicone layer. It utilizes a topological design whose distribution density adapts to the pipe curvature. The heating filament density is adaptively adjusted based on the pipe's surface geometry, including straight sections and elbows. The wiring is denser in elbows, where curvature is greater and heat dissipation is faster, to provide greater thermal compensation. The wiring is relatively sparse in straight sections to save energy.

[0035] Insulating reflective film: As the outermost covering, its function is to form a thermal barrier and reduce heat loss to the environment: on the one hand, it reduces the ineffective loss of heat generated by the heating body to the external environment through low thermal conductivity; on the other hand, it reflects the radiant heat back to the direction of the pipeline through high reflectivity. The dual effects improve the utilization rate of thermal energy.

[0036] The turbulence generator of the water flow disturbance module actively intervenes in the flow field using a variety of physical methods, including a micro-vortex blade array, a throttle valve group with adjustable aperture, and supporting CFD model optimization: Micro vortex blade array: fixed at a specific position on the inner wall of the pipe, the blades are driven to rotate by a servo motor, artificially creating a controllable vortex motion in the flow channel, breaking the original laminar flow state, forcing the upper and lower layers of water to mix, and eliminating temperature stratification and stagnant areas.

[0037] Adjustable aperture throttle valves: By periodically and regularly changing the cross-sectional area of ​​a specific pipe section—that is, adjusting the aperture size—they create a pulsed flow. This cyclical contraction-expansion effect generates intense turbulence, scouring the pipe walls and preventing the boundary layer water from cooling too quickly.

[0038] The disturbance frequency and amplitude are optimized based on the CFD computational fluid dynamics model to ensure full antifreeze coverage with minimum energy consumption: On the premise of ensuring full antifreeze coverage with no dead water areas, the most energy-efficient disturbance operating parameter combination is calculated, including the optimal rotation frequency range of the blades, the optimal opening and closing cycle and opening variation amplitude of the throttle valve, and the disturbance amplitude, to ensure the optimal antifreeze disturbance effect with minimum energy consumption.

[0039] The activation logic of the turbulence generator lies in the intelligent linkage between its response strategy and the system operating status, including heating linkage logic and temperature uniformity correction logic, specifically: Heating linkage logic: When the heating power of the antifreeze heating module is increased to the second level or above, indicating that stronger heat transfer is needed, the turbulence generator automatically starts and automatically matches the blade rotation frequency as a function of the heating power. Its key feature is that the blade rotation frequency Set to real-time heating power function, ,in The greater the heating power, the higher the required heat exchange efficiency and the corresponding higher the blade rotation frequency, ensuring that the heat can be quickly diffused along with the strongly disturbed water flow.

[0040] Temperature uniformity correction logic: When the system detects significant variations in water temperature distribution at different locations in the pipeline, with a standard deviation exceeding 0.8°C, this indicates temperature non-uniformity, which can easily lead to localized overcooling and icing. At this point, the throttle valve group in a specific area is activated to adjust the local flow resistance, changing the water flow velocity and flow distribution in that area. This proactively corrects the regional flow velocity, promotes mixing of hot and cold water, and evens out the overall water temperature distribution.

[0041] The collaborative ablation operation of the ice treatment module is to remove the ice layer on the pipe wall by a multi-mechanism composite method, including: Mechanical scraping unit: The actuator is a retractable blade driven by a memory alloy. Its working mechanism is that the blade moves in a controlled, spiral trajectory along the inner wall of the pipe, directly stripping away ice adhering to the pipe wall using physical cutting force. It is suitable for processing thick and strongly cohesive ice layers.

[0042] High-frequency oscillator: While the mechanical scraper is operating, it emits ultrasonic waves in a specific frequency range of 20-40kHz toward the ice-water interface and within the ice layer. These high-frequency mechanical waves penetrate the ice layer, causing the ice crystal structure to resonate, breaking and fragmenting its internal bonds. This reduces the overall strength of the ice layer and its adhesion to the pipe wall, assisting and enhancing the mechanical scraping effect.

[0043] Negative pressure recovery device: This device generates and maintains local negative pressure near the scraping and ultrasonic crushing operations, instantly removing the ice chips and ice-water mixture produced by the peeling and crushing process. The mixture is then transported to a collection and processing unit via a dedicated pipeline. This prevents the removed ice chips from re-aggregating and settling in nearby pipe sections, leading to secondary condensation and blockage.

[0044] When detecting the thickness of ice on the pipe wall, ice detection technology is used for high-precision measurement and prediction: Probe placement strategy: Key pipeline nodes for ice detection were identified, including ice-prone elbows, upstream of valves, and low-velocity sections. Three sets of ultrasonic probes were evenly distributed around these critical nodes at a 120-degree angle. This triangular layout covers the entire circumference of the pipeline, eliminating blind spots and improving the comprehensiveness and reliability of ice thickness measurements.

[0045] Time Domain Reflectometry: This technology uses the time difference between ultrasonic waves reflecting off the ice-water interface and the ice-tube wall interface to calculate ice thickness. By measuring the time interval between ultrasonic emission and reflected signal reception, combined with the speed of sound waves in ice, the system calculates ice thickness with a resolution of up to 0.1 mm, meeting high-precision monitoring requirements.

[0046] Ice Thickness Growth Prediction Model: Based on real-time and historical monitoring data, including current ice thickness, water temperature, flow velocity, ambient temperature, and historical icing patterns, and incorporating principles of thermodynamics and mass transfer, a data-driven ice thickness growth prediction model is developed. This model predicts the growth trend and rate of ice over a specific timeframe, intelligently calculates and determines the optimal time to initiate de-icing operations, and proactively intervenes before the ice reaches a critical thickness, enabling preventative de-icing.

[0047] Methods for optimizing the operation of the intelligent control center: External meteorological integration: Real-time access and analysis of authoritative cold wave warning data issued by the meteorological department, covering the next 72 hours, and using key forecast information on extreme low temperatures, wind speed, and precipitation as important long-term prediction inputs to make the system predictive.

[0048] Construct a thermodynamic model of the pipeline network: Construct a "thermal inertia matrix" to characterize the thermal characteristics of the pipeline network. This matrix reflects the differences in thermal response speed and insulation difficulty of each pipe section during the cooling process by quantitatively calculating the heat capacity (heat storage capacity) of different pipe sections in the pipeline network: heat storage capacity and heat dissipation characteristics: heat exchange rate with the environment.

[0049] Reinforcement learning optimization: Using reinforcement learning algorithm, the algorithm continuously learns the real-time operation data of the system, including the effects and energy consumption of heating, disturbance, and de-icing operations. Its objective function is the Pareto optimality of maximizing antifreeze reliability and minimizing energy consumption. The specific goal is defined as the comprehensive optimization target value : ; in, To comprehensively optimize the target value, is the antifreeze reliability index, is the total energy consumption of the system (heating + disturbance + de-icing), represents the pursuit of minimization of energy consumption; α represents antifreeze reliability The weight of β is 0.7, which is a quantitative evaluation index of the system's ability to prevent icing and successfully de-icing, including trouble-free operation time and ice limit occurrence rate; β represents the weight of energy efficiency, which is 0.3.

[0050] The algorithm dynamically generates a heating-disturbance-deicing coordinated strategy, including the optimal heating strategy instruction, disturbance frequency instruction, and deicing timing instruction, striving to reduce the total energy consumption of the system while ensuring high reliability α weight β effect.

[0051] The fail-safe module enables emergency response and efficiency improvements, including: Failure safety mechanism: Real-time monitoring of the system temperature field. When an abnormal temperature drop is detected in a local pipe section, and the drop rate and absolute value exceed the preset safety tolerance threshold, indicating that the pipe is prone to rupture and serious ice blockage, the system immediately and automatically triggers the protection program: quickly close the isolation valves at both ends of the faulty pipe section to physically isolate it from the main circulation system, and automatically open the preset backup pipeline valve to direct the water flow to the backup circulation channel to ensure uninterrupted cooling function of the power plant. Alarm information including fault location and severity level is reported to the intelligent control center in real time.

[0052] Energy Recovery Unit: This unit utilizes low-temperature water generated during ice melt as a cooling source, exchanging heat with low-grade waste heat from the power plant, including low-parameter steam, flue gas waste heat, and equipment heat dissipation. This recovers some of the previously wasted cooling and waste heat, improving the system's overall energy efficiency.

[0053] Digital Twin Monitoring Interface: This interface builds and visualizes a digital twin of the pipeline network system. This interface integrates and graphically presents real-time operational data, including the network's real-time temperature field (temperature distribution cloud map), ice distribution (ice thickness and location markers), and energy consumption data for each module, providing operators with global situational awareness. The interface also supports authorized personnel to perform manual policy intervention, including adjusting parameter weights, manually starting and stopping equipment, and setting special operating modes, enhancing human-machine collaboration.

[0054] Based on the above disclosure and in combination with practical applications, the operating steps of the power plant circulating water antifreeze system suitable for cold regions of the present invention are as follows: Step 1: Real-time perception of global status and initial risk assessment After the system is started, the temperature sensing module continuously collects water temperatures and external ambient temperatures at key nodes in the circulating water network through a distributed sensor array. The environmental parameter acquisition unit simultaneously monitors the heat dissipation conditions on the outer walls of the pipes. A temperature field reconstruction algorithm integrates multi-source data to generate a cloud map of the temperature distribution across the entire network. When the water temperature at any node approaches a preset threshold, a low-temperature warning signal is generated and transmitted to the antifreeze heating module at the execution layer.

[0055] Step 2: Dynamic activation of hierarchical antifreeze strategy After receiving the low temperature warning signal, the antifreeze heating module initiates a graded response based on the temperature drop rate and absolute value: Level 1 insulation mode: When the water temperature is in the critical range of 0℃ to -5℃, the lowest power flexible electric heating is enabled, the carbon nanotube heating wire network operates at basic power, and the insulating reflective film reduces heat loss to maintain stable water temperature.

[0056] Secondary Heating Mode: When the water temperature drops below -5°C and the rate of temperature drop exceeds 0.5°C / min, the heating power is increased according to a linear control law, and the water disturbance module is simultaneously activated to activate the turbulence generator. The micro-vortex blades increase their rotation frequency in proportion to the heating power, forcing the water to mix.

[0057] Level 3 defense mode: When the ambient temperature is lower than -15℃ and lasts for more than 2 hours, it switches to maximum power heating, and the throttle valve group simultaneously starts pulse water flow impact to eliminate the low-temperature stagnation area.

[0058] Step 3: Intelligent Detection and Collaborative Ice Melting The water flow disturbance module provides real-time feedback of pipeline flow data to the ice processing module. A circumferentially distributed set of ultrasonic probes uses time-domain reflectometry to measure ice thickness on the pipe wall. An ice thickness growth prediction model combines water temperature, flow velocity, and historical data to predict ice formation trends. When ice thickness exceeds a safety threshold: The high-frequency oscillator emits 20-40kHz ultrasonic waves to induce resonance and fragmentation of the ice layer; The memory alloy drives the mechanical scraper to spiral along the pipe wall to peel off the residual ice; The negative pressure recovery device sucks ice chips in real time to prevent secondary condensation and blockage.

[0059] Step 4: Multi-objective collaborative optimization decision-making The intelligent control center integrates weather forecasts, ice status and real-time operating parameters to build a dynamic thermal inertia matrix model. The reinforcement learning algorithm continuously learns historical operation data, including heating energy consumption, disturbance effects, and de-icing efficiency, to form a comprehensive objective function. To optimize the orientation: Prioritize the anti-freeze reliability weight α, which is achieved by extending the trouble-free operation time and reducing the incidence of ice overrun; Collaboratively optimize the energy efficiency weight β to minimize the total energy consumption of the system; Dynamically generate the Pareto optimal instruction set for heating power level, blade speed, and de-icing timing to ensure a balance between antifreeze effect and energy consumption control.

[0060] Step 5: Fault Emergency Response and System Protection The fail-safe module scans for abnormal temperature drop signals in real time, indicating pipeline rupture and ice blockage. Once the tolerance threshold is triggered: Automatically close the isolation valve of the faulty pipe section and switch to the backup circulation channel; The energy recovery unit is activated, using the low-temperature water generated by ablation to perform cascade heat exchange with the waste heat from the power plant; The digital twin monitoring interface marks the fault location in real time, pushes alarms synchronously, and records operation logs.

[0061] Step 6: Continuous Learning and Strategic Evolution After each cold wave cycle ends, the system automatically analyzes the operating data: Statistics on energy consumption distribution and antifreeze failure events of each module; Evaluate the actual effects of α and β weights and optimize the objective function parameters; Update the thermal inertia matrix and ice thickness prediction model parameters to improve the decision-making accuracy of the next cycle.

[0062] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0063] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A power plant circulating water antifreeze system suitable for cold regions, characterized by: The system includes: The temperature sensing module collects the internal water temperature and external ambient temperature parameters of key nodes in the circulating water network in real time. When the internal water temperature falls below the preset temperature threshold, a low temperature warning signal is generated and output to the antifreeze heating module; The antifreeze heating module activates a hierarchical heating mechanism upon receiving the low temperature warning signal, performs contact heat conduction on the circulating water through a flexible electric heating body, and generates a disturbance activation instruction based on the internal temperature change rate and outputs it to the water flow disturbance module; a water flow disturbance module, which activates a turbulence generator in response to the disturbance activation instruction, prevents local icing by periodically adjusting the flow velocity distribution, and feeds back pipeline flow state data to the ice layer processing module; An ice layer processing module receives the pipeline flow data and uses ice layer detection technology to detect the thickness of the ice layer on the pipe wall. When the ice layer thickness is greater than or equal to its safety limit, it triggers a mechanical scraping and high-frequency oscillation collaborative ablation operation, and simultaneously uploads ice layer status parameters to the intelligent control center; The intelligent control center integrates meteorological forecast data, ice state parameters, and real-time operating parameters to build a thermodynamic model of the pipe network and dynamically generate optimal heating strategy instructions, disturbance frequency instructions, and de-icing timing instructions, which are fed back to the antifreeze heating module, water flow disturbance module, and ice layer processing module respectively; The fault safety module automatically isolates the faulty pipe section and switches to the backup circulation channel when it detects an abnormal drop in local pipeline temperature, and at the same time sends corresponding status alarm information to the intelligent control center.

2. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The temperature sensing module includes: A distributed temperature sensor array is evenly spaced along the axial direction of the circulating water network, covering straight pipe sections, elbows, and valve connections; An environmental parameter acquisition unit installed on the outer wall of the pipeline is used to synchronously obtain wind speed and humidity data; The temperature field reconstruction algorithm based on machine learning deduces the real-time temperature distribution of the entire pipeline network based on sparse monitoring point data.

3. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The hierarchical heating mechanism of the antifreeze heating module includes: Level 1 heating mode: When the water temperature is between 0℃ and -5℃, the basic heat preservation power is activated to maintain the water temperature; Secondary heating mode: When the water temperature is below -5°C and the temperature drop rate exceeds 0.5°C / min, a step-by-step power increase strategy is activated until the temperature returns to a safe range. The power regulation follows the following linear control law: ； in For real-time heating power, is the power-temperature proportionality coefficient, is the difference between the current water temperature and the freezing point, is the basic power offset; Level 3 heating mode: When the ambient temperature remains below -15°C for more than 2 hours, the system switches to full power and activates the water flow disturbance module to enhance heat exchange efficiency.

4. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The flexible electric heating body adopts a multi-layer composite structure, including: A thermally conductive silicone layer adhered to the outer wall of the pipe; The topological distribution density of the carbon nanotube heating wire network embedded in the thermally conductive silicone layer is adaptively adjusted according to the curvature of the pipe; The surface is covered with a heat-insulating reflective film to reduce heat loss to the environment.

5. The power plant circulating water antifreeze system suitable for cold regions according to claim 1 is characterized by: The turbulence generator of the water flow disturbance module includes: An array of micro-vortex blades installed on the inner wall of the pipe is driven by a servo motor to generate swirling flow; The throttle valve group with adjustable aperture periodically changes the local flow cross-sectional area to form a pulsed water flow impact; The disturbance frequency and amplitude are optimized based on the CFD computational fluid dynamics model to ensure full antifreeze coverage at the lowest energy consumption.

6. The power plant circulating water antifreeze system suitable for cold regions according to claim 5, characterized in that: The activation logic of the turbulence generator is: When the heating power is increased to level 2 or above, the blade rotation frequency is automatically matched as a function of the heating power; When it is detected that the standard deviation of the water temperature distribution exceeds 0.8°C, the throttle valve group is started to perform regional flow rate correction.

7. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The collaborative ablation operation of the ice layer processing module includes: Mechanical scraping unit: A retractable blade driven by a memory alloy propels the blade axially along the inner wall of the pipe to physically remove the attached ice layer. High-frequency oscillator: emits 20-40kHz ultrasonic waves during the scraping operation, inducing resonance and fragmentation of the ice crystal structure; Negative pressure recovery device: real-time suction of peeled ice chips to prevent secondary condensation.

8. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The ice detection technology includes: Three sets of probes are distributed 120° around the key nodes of the pipeline for ice detection; Time domain reflectometry is used to measure ice thickness with a resolution of 0.1 mm; Establish an ice thickness growth prediction model and combine it with historical icing data to predict the timing of starting de-icing operations.

9. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The operation optimization method of the intelligent control center includes: Access to 72-hour cold wave warning data issued by the Meteorological Observatory; Construct a thermal inertia matrix for the pipe network to quantify the heat capacity and heat dissipation characteristics of different pipe sections; A heating-disturbance-deicing coordinated strategy is dynamically generated through a reinforcement learning algorithm. The objective function is the Pareto optimality of maximizing antifreeze reliability and minimizing energy consumption. The optimization objective is defined by the following function: ； in, To comprehensively optimize the target value, is the antifreeze reliability weight, is the energy efficiency weight, is the antifreeze reliability index, is the total energy consumption of the system.

10. The power plant circulating water antifreeze system suitable for cold regions according to claim 1, characterized in that: The fail-safe module specifically includes: Fail-safe mechanism: When the system detects that the temperature of a local pipe section drops abnormally and exceeds the preset safety tolerance threshold, it automatically isolates the pipe section and activates the backup circulation channel; Energy recovery unit: Utilizes low-temperature water generated during the ablation process to conduct cascade heat exchange with waste heat from the power plant; Digital twin monitoring interface: Visualizes the real-time temperature field, ice distribution, and energy consumption data of the pipeline network, and supports manual strategy intervention.

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