Thermal power plant circulating water flow management system based on big data

Abstract

The invention relates to the technical field of flow management, and discloses a thermal power plant circulating water flow management system based on big data, which realizes omnibearing real-time monitoring of circulating water in each area, accurate collection of flow data, judgment of abnormity and diagnosis and compensation through a real-time monitoring end, effectively solves the problem of lack of real-time monitoring in the traditional technology, and improves the real-time monitoring efficiency. The traffic data is compared in real time and the data of the next period is predicted by depending on the big data analysis capability of the traffic analysis end, the limitation of the traditional management technology is broken through, the management efficiency and the management and control refinement level are improved, and the early warning self-control end formulates and accurately executes a traffic plan based on the prediction result; the number of starting and stopping circulating pumps is judged in advance, a traditional extensive adjusting mode is changed, and energy loss is reduced. And the display switching module is matched to intuitively present monitoring pictures of each area, so that workers are assisted to quickly respond to decisions, and the management and control convenience and efficiency are further improved.

Description

Technical Field

[0001] This invention belongs to the field of flow management technology, specifically a thermal power plant circulating water flow management system based on big data. Background Technology

[0002] Circulating water flow control in thermal power plants targets the circulating water systems used for cooling and various industrial applications. It involves precisely regulating water flow through control equipment to ensure heat exchange efficiency while guaranteeing safe and energy-efficient system operation. However, current circulating water flow management systems in thermal power plants still face several pressing challenges: the lack of effective real-time monitoring systems makes it difficult to detect leaks, blockages, and abnormal parameters in the circulating water system in a timely manner, potentially leading to escalation of malfunctions; traditional management strategies fail to fully integrate modern information technologies such as data analysis and remote monitoring, resulting in cumbersome and inefficient management processes that hinder refined control; and with the dynamic changes in turbine load and circulating water temperature, existing solutions often regulate flow by directly starting and stopping several circulating pumps, a highly energy-intensive operation that contradicts the need for energy-saving operation.

[0003] To address some of the aforementioned issues, existing technologies have proposed a multi-stage energy-saving utilization system for circulating water in thermal power plants, as disclosed in Chinese Patent Publication No. CN115522605A. This system, through the installation of a water storage tank and a compatible linkage structure with the thermal power plant equipment, enables automatic replenishment of water within the tank. This avoids water shortages caused by the inability to return water in a timely manner, ensuring continuous cooling of the power plant equipment. Furthermore, it replenishes water lost during the cooling process, reducing continuous water consumption. Simultaneously, it improves the thermal energy utilization rate of the circulating water and treats the return water, reducing the risk of pipe blockage and heat waste caused by impurities. However, this technical solution still has significant shortcomings: it fails to address the core issue of the lack of real-time monitoring, making it unable to promptly detect dynamic anomalies in system operation; it does not integrate modern information technology to optimize management strategies, resulting in limited improvements in management efficiency; and it does not offer an effective solution to the energy waste problem associated with the start-up and shutdown regulation of the circulating pumps, failing to achieve comprehensive energy saving and efficient management.

[0004] Existing technologies cannot simultaneously solve the core problems in thermal power plant circulating water flow management, such as the lack of real-time monitoring, low management efficiency, and energy waste, making it difficult to balance system safety, efficiency, and energy conservation. Therefore, developing a technical solution that can achieve real-time and accurate monitoring, integrate modern information technology to improve management efficiency, and optimize adjustment methods to reduce energy consumption, thereby solving all the above-mentioned dilemmas, has become an urgent technical challenge in the field of thermal power plant circulating water systems. Summary of the Invention

[0005] This invention provides a big data-based circulating water flow management system for thermal power plants, which solves the problems of lack of real-time monitoring and management efficiency in the management of circulating water flow in thermal power plants.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A big data-based circulating water flow management system for thermal power plants includes a real-time monitoring terminal, a flow analysis terminal, and an early warning and automatic control terminal, wherein the real-time monitoring terminal, the flow analysis terminal, and the early warning and automatic control terminal are all equipped with a display switching module; The real-time monitoring terminal is used to monitor the circulating water in different areas of the thermal power plant in real time and collect basic data of circulating water flow, determine whether the basic data of circulating water flow is abnormal, and diagnose the cause of the abnormality in real time when it is abnormal, and perform diagnosis and compensation for the cause of the abnormality. The flow analysis terminal is used to monitor the updated data of circulating water flow in thermal power plants in real time, set standard data for circulating water flow, perform real-time data analysis on the updated data and standard data, and predict the circulating water flow based on the circulating water flow in each time period, and automatically generate updated data for the circulating water flow in the next cycle. The early warning and automatic control terminal is used to automatically generate updated data of the circulating water flow rate for the next cycle, formulate a circulating water flow rate plan, record the time required for the plan to be executed through a timer, execute the plan through a countdown, and track the circulating water flow rate after the plan is executed in real time, track the execution result of the circulating water flow rate plan, and predict the number of circulating pumps to start and stop in advance. The display switching module is used to display real-time monitoring images of circulating water flow in different areas.

[0007] Preferably, the real-time monitoring terminal includes a regional monitoring module, an object identification module, and a traffic diagnosis module; The regional monitoring module includes a circulating water monitoring unit and a data acquisition unit; The circulating water monitoring unit is used to detect the basic data of the circulating water flow rate of the thermal power plant in real time through sensors and detectors. The basic data includes conductivity, pH value, temperature, liquid level and concentration ratio. The data acquisition unit is used to receive basic data on the current circulating water flow rate of the thermal power plant in real time through a data receiver.

[0008] Preferably, the object recognition module includes an object recognition unit and an anomaly recording unit; The object recognition unit is used to set the standard data of the circulating water flow rate of the thermal power plant at the current moment, calculate the difference between the standard data and the basic data, and if the difference = 0, it is determined that the basic data of the circulating water flow rate at the current moment is normal; if the difference ≠ 0, it is determined that the basic data of the circulating water flow rate at the current moment is abnormal. The anomaly recording unit is used to record the basic data for determining the current circulating water flow rate in real time through the data tracker, and to identify abnormal data.

[0009] Preferably, the flow diagnosis module includes a diagnosis compensation unit; The diagnostic compensation unit is used to compensate the basic data that identifies abnormal data. The data compensation method is as follows: if the difference is positive, the corresponding basic value is increased; if the difference is negative, the corresponding basic value is decreased.

[0010] Preferably, the traffic analysis terminal includes a traffic monitoring module, a traffic analysis module, and a traffic prediction module; The traffic monitoring module includes a traffic monitoring unit and a traffic threshold unit; The flow monitoring unit is used to monitor the basic data of circulating water flow in real time through the data tracker and the circulating water flow monitor; The flow threshold unit is used to set standard data for the circulating water flow rate.

[0011] Preferably, the flow analysis module is used to perform data analysis on the standard data and basic data of circulating water flow. The data analysis method is as follows: Step 1: Calculate the correction difference between the standard data and the baseline data of the circulating water flow rate at the current moment. The calculation formula is as follows:

[0012] in, This represents the correction difference between the standard data and the baseline data of the circulating water flow rate at the current moment. Indicates the first The basic data of the current circulating water flow rate at a given moment. Indicates the first The basic data of the current circulating water flow rate at a given moment. Indicates the first The lower limit of standard data for circulating water flow rate at a given time. Indicates the first The standard upper limit of circulating water flow rate at any given time. Indicates the first The lower limit of standard data for circulating water flow rate at a given time. Indicates the first The upper limit of standard data for circulating water flow rate at any given moment; Step 2: Calculate the degree of change in the basic data of the circulating water flow. The calculation formula is as follows:

[0013] in, Indicates the first The degree of change in the basic data of circulating water flow at each moment. Indicates the first Basic data of circulating water flow at time 1 and time 2 Correction difference of basic circulating water flow data at each time point Indicates the first Basic data of circulating water flow at time 1 and time 2 The correction difference of the basic data of circulating water flow rate at each time point.

[0014] Preferably, the traffic prediction module includes an analysis and prediction unit and a prediction generation unit; The analysis and prediction unit is used to predict the number of circulating pumps that start and stop in each cycle of circulating water flow. Based on the standard of one quarter as a cycle, the number of pumps that start and stop in the second cycle can be calculated from the number of pumps that start and stop in the first cycle using the exponential smoothing method.

[0015] in, It is the equilibrium constant, and =[0, 1], The number of circulating pumps started and stopped indicates the circulating water flow rate in the first cycle. This indicates the number of times the circulating pump starts and stops in the first cycle. Indicates the number of circulating pumps in the first cycle; The prediction generation unit is used to automatically generate the number of circulating pumps to start and stop in the next cycle based on the analysis and prediction results.

[0016] Preferably, the early warning self-control terminal includes a plan formulation module, a plan execution module, an execution timing module, and an execution tracking module; The contingency plan formulation module includes a contingency plan receiving unit and an execution timing unit; The contingency plan receiving unit is used to receive the number of cycles without starting or stopping in real time through the data receiver, and generate the contingency plan execution timing instruction according to the corresponding time. The execution timing unit is used to prepare the pre-plan instruction with a standard countdown using a timer, and to execute the pre-plan 10 seconds before the standard countdown preparation.

[0017] Preferably, the contingency plan execution module includes a duration calculation unit, which is used to calculate the countdown duration for contingency plan execution in real time using a timer; The execution timing module includes a countdown unit, which is used to track the time difference of the plan execution in real time through a timer.

[0018] Preferably, the execution tracking module includes a contingency plan execution unit, an execution tracking unit, and a tracking and early warning unit; The contingency plan execution unit is used to automatically execute the contingency plan 10 seconds before the countdown begins, starting and stopping the corresponding number of circulating pumps. The execution tracking unit is used to track the execution data of the plan in real time through the data tracker. The execution data includes the turbine load value and whether the circulating water temperature has changed. The difference between the turbine load value and the standard load value is calculated. If the difference = 0, the execution data of the plan is determined to be valid. If the difference ≠ 0, the execution data of the plan is determined to be invalid. The principle of whether the circulating water temperature has changed is the same. The tracking and early warning unit is used to formulate a second execution plan when the execution data of the plan is determined to be invalid, until the execution data of the plan is valid.

[0019] Compared with existing technologies, this invention has the following beneficial effects: This invention provides a big data-based circulating water flow management system for thermal power plants. Through a real-time monitoring terminal, it achieves comprehensive real-time monitoring of circulating water in all areas, accurately collects flow data, identifies anomalies, and diagnoses and compensates for them. This effectively solves the problem of missing real-time monitoring in traditional technologies, preventing the escalation of faults and ensuring system stability. Relying on the big data analysis capabilities of the flow analysis terminal, it compares flow data in real time and predicts data for the next cycle, breaking through the limitations of traditional management technologies and improving management efficiency and control precision. The early warning and automatic control terminal formulates and accurately executes flow plans based on the prediction results, predicting the number of circulating pumps to start and stop in advance, changing the traditional extensive adjustment mode and reducing energy consumption. The display and switching module intuitively presents the monitoring screens of each area, assisting staff in quick response and decision-making, further improving the convenience and efficiency of control.

[0020] Furthermore, by setting up a real-time monitoring terminal, the circulating water flow management of thermal power plants can be carried out by real-time monitoring of the circulating water in different areas of the thermal power plant and collecting basic data on the circulating water flow. This allows for the identification of whether the basic data on the circulating water flow is abnormal, and the diagnosis of the cause of the abnormality in real time. This enables the circulating water flow system of thermal power plants to be effectively monitored in real time, and abnormalities in the circulating water flow system to be detected in a timely manner. The causes of the abnormalities can be diagnosed and compensated in a timely manner to ensure the stable operation of the circulating water flow.

[0021] Furthermore, by setting up a flow analysis terminal, the circulating water flow management of thermal power plants can be carried out by monitoring the updated data of the circulating water flow in real time, setting standard data for the circulating water flow, performing real-time data analysis on the updated data and standard data, and automatically generating updated data for the circulating water flow of the next cycle. This enables the management of circulating water flow in advance. Compared with traditional management strategies, this approach can make full use of modern information technology and improve the management efficiency of the circulating water flow system through data analysis and remote monitoring technology.

[0022] Furthermore, by setting up an early warning automatic control terminal, when managing the circulating water flow in thermal power plants, the system automatically generates updated data of the circulating water flow for the next cycle, formulates circulating water flow plans, records the time required for the plan to be executed through a timer, executes the plan through a countdown, and tracks the circulating water flow after the plan is executed in real time. This allows for the prediction of the number of circulating pumps to start and stop in advance, reducing energy waste. At the same time, changes in turbine load and circulating water temperature do not need to be adjusted by directly starting and stopping several circulating pumps. The system can provide early warning of the number of circulating pumps to start and stop, ensuring the stability of circulating water flow management in thermal power plants. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the overall system architecture of a thermal power plant circulating water flow management system based on big data, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the architecture of a real-time monitoring terminal for a thermal power plant circulating water flow management system based on big data, according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the flow analysis terminal of a thermal power plant circulating water flow management system based on big data, according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the early warning and automatic control terminal of a thermal power plant circulating water flow management system based on big data, according to an embodiment 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 embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0027] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0028] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0029] like Figure 1 As shown, this embodiment of the invention provides a big data-based circulating water flow management system for thermal power plants, including a real-time monitoring terminal, a flow analysis terminal, and an early warning and automatic control terminal. The real-time monitoring terminal, the flow analysis terminal, and the early warning and automatic control terminal are all equipped with a display switching module. The real-time monitoring terminal is used to monitor the circulating water in different areas of the thermal power plant in real time and collect basic data of circulating water flow, determine whether the basic data of circulating water flow is abnormal, and diagnose the cause of the abnormality in real time when it is abnormal, and perform diagnosis and compensation for the cause of the abnormality. The flow analysis terminal is used to monitor the updated data of circulating water flow in thermal power plants in real time, set the standard data of circulating water flow, perform real-time data analysis on the updated data and the standard data, and predict the circulating water flow based on the circulating water flow in each time period, and automatically generate the updated data of circulating water flow for the next cycle. The early warning and automatic control terminal is used to automatically generate updated data of the circulating water flow for the next cycle, formulate circulating water flow plan, record the time required for the plan to be executed through a timer, execute the plan through a countdown, and track the circulating water flow after the plan is executed in real time, track the execution result of the circulating water flow plan, and predict the number of circulating pumps to start and stop in advance. The display switching module is used to display real-time monitoring screens of circulating water flow in different areas.

[0030] The real-time monitoring terminal enables comprehensive real-time monitoring of circulating water in all areas, accurately collecting flow data, identifying anomalies, and diagnosing and compensating for them. This effectively solves the problem of insufficient real-time monitoring in traditional technologies, preventing the escalation of faults and ensuring system stability. Leveraging the big data analysis capabilities of the flow analysis terminal, it compares flow data in real time and predicts data for the next cycle, breaking through the limitations of traditional management techniques and improving management efficiency and control precision. The early warning and automatic control terminal formulates and accurately executes flow plans based on the prediction results, predicting the number of circulating pumps to start and stop in advance, changing the traditional extensive adjustment mode and reducing energy consumption. The display and switching module intuitively presents the monitoring screens of each area, assisting staff in quick response and decision-making, further improving the convenience and efficiency of control.

[0031] In one possible implementation: For example, such as Figure 2 The real-time monitoring terminal shown includes a regional monitoring module, an object identification module, and a traffic diagnosis module; The regional monitoring module includes a circulating water monitoring unit and a data acquisition unit; The circulating water monitoring unit is used to detect the basic data of the circulating water flow rate of the thermal power plant in real time through sensors and detectors. The basic data includes conductivity, pH value, temperature, liquid level and concentration ratio. The data acquisition unit is used to receive basic data on the current circulating water flow rate of the thermal power plant in real time through a data receiver.

[0032] Interpretive, it constructs a real-time monitoring foundation link of full-dimensional acquisition and precise reception. The acquired basic data comprehensively reflects the stability of circulating water quality and the system's operating status. Compared with the limitations of traditional single-indicator monitoring, multi-dimensional indicator collaborative acquisition can accurately capture early signals of potential hazards such as equipment corrosion and scaling. The real-time data reception mechanism avoids the expansion of faults caused by data delays, providing a highly timely and complete data source for subsequent anomaly handling, thereby improving the reliability and practicality of real-time monitoring from the source.

[0033] In one possible implementation: For example, the object recognition module includes an object recognition unit and an exception recording unit; The object recognition unit is used to set the standard data of the circulating water flow rate of the thermal power plant at the current moment, calculate the difference between the standard data and the basic data, and if the difference = 0, it is determined that the basic data of the circulating water flow rate at the current moment is normal; if the difference ≠ 0, it is determined that the basic data of the circulating water flow rate at the current moment is abnormal. The anomaly recording unit is used to record the basic data for determining the current circulating water flow rate in real time through the data tracker, and to identify abnormal data.

[0034] Interpretive analysis establishes an objective anomaly judgment benchmark through quantified differences, replacing the traditional subjective judgment mode that relies on human experience. Simultaneously, a data tracking and labeling mechanism is introduced to achieve full-process coverage of anomaly tracing. The judgment standard of a 0-degree difference eliminates the ambiguity and individual differences inherent in experience-based judgments, ensuring the consistency and accuracy of anomaly identification. Real-time recording and labeling functions address the pain point of difficulty in tracing the root cause after anomalies occur in traditional technologies, facilitating staff to quickly locate the occurrence points and impact range of leaks, blockages, and other problems, significantly improving the response efficiency and targeting of anomaly handling.

[0035] In one possible implementation: For example, the traffic diagnostic module includes a diagnostic compensation unit; The diagnostic compensation unit is used to compensate the base data that identifies abnormal data. The data compensation method is as follows: if the difference is positive, the corresponding base value is increased; if the difference is negative, the corresponding base value is decreased.

[0036] Explanatoryly, a closed-loop intervention mechanism of anomaly identification and proactive compensation is constructed. Targeted numerical adjustment strategies correct abnormal data, preventing the accumulation of anomalies from causing a chain reaction in system control. This overcomes the passive limitation of traditional technologies that can only detect anomalies but cannot intervene in a timely manner. Proactive compensation can quickly restore the stability of circulating water operating parameters, reducing the risks of decreased heat exchange efficiency and accelerated equipment corrosion caused by parameter deviations. It also reduces production losses caused by abnormal downtime for maintenance, further enhancing the safety and continuity of system operation.

[0037] In one possible implementation: For example, such as Figure 3 As shown, the traffic analysis terminal includes a traffic monitoring module, a traffic analysis module, and a traffic prediction module; The traffic monitoring module includes a traffic monitoring unit and a traffic threshold unit; The flow monitoring unit is used to monitor basic data of circulating water flow in real time through a data tracker and a circulating water flow monitor; The flow threshold unit is used to set standard data for circulating water flow rate.

[0038] The explanatory and clear pre-processing logic for flow analysis ensures the reliability of the analyzed data and the consistency of the comparison benchmark through the collaboration of dedicated monitoring equipment and independent threshold setting modules. The application of dedicated monitoring equipment improves the continuity and accuracy of basic data collection and avoids the errors of traditional general-purpose equipment monitoring. The independent flow threshold unit solves the problems of vague standard data setting and susceptibility to human interference in traditional technologies, providing a stable and unified reference benchmark for subsequent data analysis and ensuring the scientific and rigorous nature of data analysis from a process perspective.

[0039] In one possible implementation: For example, the flow analysis module is used to perform data analysis on the standard data and basic data of circulating water flow. The data analysis method is as follows: Step 1: Calculate the correction difference between the standard data and the baseline data of the circulating water flow rate at the current moment. The calculation formula is as follows:

[0040] in, This represents the correction difference between the standard data and the baseline data of the circulating water flow rate at the current moment. Indicates the first The basic data of the current circulating water flow rate at a given moment. Indicates the first The basic data of the current circulating water flow rate at a given moment. Indicates the first The lower limit of standard data for circulating water flow rate at a given time. Indicates the first The standard upper limit of circulating water flow rate at any given time. Indicates the first The lower limit of standard data for circulating water flow rate at a given time. Indicates the first The upper limit of standard data for circulating water flow rate at any given moment; Step 2: Calculate the degree of change in the basic data of the circulating water flow. The calculation formula is as follows:

[0041] in, Indicates the first The degree of change in the basic data of circulating water flow at each moment. Indicates the first Basic data of circulating water flow at time 1 and time 2 Correction difference of basic circulating water flow data at each time point Indicates the first Basic data of circulating water flow at time 1 and time 2 The correction difference of the basic data of circulating water flow rate at each time point.

[0042] Explanatory, a refined data analysis model is constructed through two-step quantitative calculation. The correction difference calculation can eliminate the interference caused by fluctuations in the basic data, while the change degree calculation can accurately capture the trend changes in traffic data, realizing a deeper understanding from data collection to pattern mining. This completely breaks away from the traditional extensive and experience-based data analysis mode. The quantitative logic can accurately locate the deviation and rate of change of traffic data, providing a high-precision analytical basis for subsequent traffic prediction, avoiding control deviations caused by inaccurate data analysis, and promoting the transformation of traffic management from passive response to accurate prediction.

[0043] In one possible implementation: For example, the traffic prediction module includes an analysis and prediction unit and a prediction generation unit; The analysis and prediction unit is used to predict the number of circulating pumps that start and stop in each cycle of circulating water flow. Based on the standard of one quarter as a cycle, the exponential smoothing method is used to calculate the number of pumps that start and stop in the second cycle based on the number of pumps that start and stop in the first cycle.

[0044] in, It is the equilibrium constant, and =[0, 1], The number of circulating pumps started and stopped indicates the circulating water flow rate in the first cycle. This indicates the number of times the circulating pump starts and stops in the first cycle. Indicates the number of circulating pumps in the first cycle; The prediction generation unit is used to automatically generate the number of circulating pumps to start and stop in the next cycle based on the analysis and prediction results.

[0045] Explanatoryly, an exponential smoothing method is introduced to construct a predictive model. This method, which gives higher weight to recent data, is combined with historical data on circulating pump operation to accurately predict the number of pump starts and stops. Furthermore, it adapts to the cyclical changes in thermal power plant load on a quarterly basis. Compared to traditional simple moving average prediction methods, exponential smoothing better adapts to the fluctuations in circulating water flow, improving prediction accuracy. Predicting the number of pump starts and stops in advance solves the problem of lagging traditional control, making subsequent contingency plans more forward-looking. This provides core support for precise control and reducing ineffective starts and stops, further solidifying the technical foundation for energy-saving operation.

[0046] In one possible implementation: For example, such as Figure 4 As shown, the early warning and self-control terminal includes a contingency plan formulation module, a contingency plan execution module, an execution timing module, and an execution tracking module; The contingency plan formulation module includes a contingency plan receiving unit and an execution timing unit; The contingency plan receiving unit is used to receive the number of cyclic non-stop instructions in real time through the data receiver, and generate the contingency plan execution timing instructions according to the corresponding time. The execution timing unit is used to prepare the pre-planned instructions by using a timer for a standard countdown, and to execute the pre-planned instructions 10 seconds before the standard countdown preparation.

[0047] Explanatoryly, an orderly control process of command reception, timed preparation, and advance execution is constructed. The countdown preparation provides buffer time, and the execution 10 seconds in advance ensures real-time matching between control actions and changes in system operating conditions. This solves the problems of chaotic processes and delayed response in traditional control. The timed preparation mechanism ensures the standardization of plan execution and avoids operational errors caused by hasty control. The advance execution design can timely match the dynamic changes of turbine load and circulating water temperature, reduce energy waste and equipment damage caused by control delays, and improve the timeliness and safety of flow control.

[0048] In one possible implementation: For example, the contingency plan execution module includes a duration calculation unit, which is used to calculate the countdown duration for contingency plan execution in real time through a timer; The execution timing module includes a countdown unit, which is used to track the time difference of the plan execution in real time through a timer.

[0049] Explanatory, the process control of contingency plan execution is achieved through real-time time parameter tracking. Duration calculation and time difference tracking form a dual time monitoring dimension, ensuring the controllability of execution progress and filling the gap of lack of process monitoring in traditional contingency plan execution. Real-time time data allows staff to accurately grasp the execution progress, promptly identify and correct time deviations, and avoid control failures caused by execution exceeding or exceeding the time limit. The dual monitoring dimension improves the accuracy of time control, ensures the stability and reliability of contingency plan execution, and provides basic time-dimensional data for subsequent effect verification.

[0050] In one possible implementation: For example, the execution tracking module includes a contingency plan execution unit, an execution tracking unit, and a tracking early warning unit; The contingency plan execution unit is used to automatically execute the contingency plan 10 seconds before the countdown begins, starting and stopping the corresponding number of circulating pumps. The execution tracking unit is used to track the execution data of the plan in real time through the data tracker. The execution data includes the turbine load value and whether the circulating water temperature has changed. The difference between the turbine load value and the standard load value is calculated. If the difference = 0, the execution data of the plan is considered valid. If the difference ≠ 0, the execution data of the plan is considered invalid. The principle of whether the circulating water temperature has changed is the same. The tracking and early warning unit is used to formulate a new execution plan when the execution data of the plan is deemed invalid, until the execution data of the plan is valid.

[0051] Explanatory, using turbine load and circulating water temperature as two core operating parameters as the basis for effect verification, ensures precise matching between control and actual operating conditions, completely solving the shortcomings of traditional control that emphasizes execution but neglects verification. Real-time tracking can quickly determine the effectiveness of the plan, and the mechanism for secondary plan formulation can promptly correct control deviations, ensuring that the flow always adapts to changes in operating conditions. The closed-loop system significantly improves the accuracy of control, avoids energy waste caused by ineffective control, further ensures the stability and energy-saving effect of system operation, and achieves refined management and control of the entire process.

[0052] In this invention, a big data-based circulating water flow management system for thermal power plants monitors circulating water in different areas of the power plant in real time and collects basic circulating water flow data. It identifies anomalies in the basic circulating water flow data and diagnoses the causes of anomalies in real time. This allows the circulating water flow system to effectively monitor in real time, promptly detect anomalies, and provide timely diagnosis and compensation to ensure stable operation of the circulating water flow. Sensors and detectors monitor the basic circulating water flow data in real time, including conductivity, pH value, temperature, liquid level, and concentration ratio. Abnormal data is compensated. Data trackers and circulating water flow monitors monitor the basic circulating water flow data in real time. Data analysis is performed on the standard circulating water flow data and the basic circulating water flow data to predict the number of circulating pumps starting and stopping in each cycle. Using a quarter as a cycle, exponential smoothing is employed to predict the number of start-ups and shutdowns in the first cycle. The system calculates the number of pumps to be started and stopped in the second cycle. By monitoring the updated data of the circulating water flow in the thermal power plant in real time and setting standard data for the circulating water flow, the system performs real-time data analysis on the updated data and standard data, and automatically generates updated data for the circulating water flow in the next cycle. This allows for proactive management of the circulating water flow. Compared to traditional management strategies, this system fully utilizes modern information technology, improving the management efficiency of the circulating water flow system through data analysis and remote monitoring. The system receives real-time commands for the number of pumps to be started and stopped through a data receiver, and generates timed commands for the execution of contingency plans based on the corresponding time. When the countdown is 10 seconds in advance, the contingency plan is automatically executed, starting and stopping the corresponding number of circulating pumps. The execution data of the contingency plan is tracked in real time through a data tracker. The execution data includes changes in turbine load and circulating water temperature, allowing for early warning of the number of pumps to be started and stopped, reducing energy waste. Furthermore, changes in turbine load and circulating water temperature do not require direct adjustment by starting and stopping several circulating pumps, enabling early warning of the number of pumps to be started and stopped, and ensuring the stability of the circulating water flow management in the thermal power plant.

[0053] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0054] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A big data-based circulating water flow management system for thermal power plants, characterized in that, It includes a real-time monitoring terminal, a traffic analysis terminal, and an early warning and automatic control terminal, all of which are equipped with a display switching module. The real-time monitoring terminal is used to monitor the circulating water in different areas of the thermal power plant in real time and collect basic data of circulating water flow, determine whether the basic data of circulating water flow is abnormal, and diagnose the cause of the abnormality in real time when it is abnormal, and perform diagnosis and compensation for the cause of the abnormality. The flow analysis terminal is used to monitor the updated data of circulating water flow in thermal power plants in real time, set standard data for circulating water flow, perform real-time data analysis on the updated data and standard data, and predict the circulating water flow based on the circulating water flow in each time period to automatically generate updated data for the circulating water flow in the next cycle. The early warning control terminal is used to automatically generate updated data of the circulating water flow rate for the next cycle, formulate a circulating water flow rate plan, record the time required for the plan to be executed through a timer, execute the plan through a countdown, and track the circulating water flow rate after the plan is executed in real time, track the execution result of the circulating water flow rate plan, and predict the number of circulating pumps to start and stop in advance. The display switching module is used to display real-time monitoring images of circulating water flow in different areas.

2. The thermal power plant circulating water flow management system based on big data according to claim 1, characterized in that, The real-time monitoring terminal includes a regional monitoring module, an object identification module, and a traffic diagnosis module; The regional monitoring module includes a circulating water monitoring unit and a data acquisition unit; The circulating water monitoring unit is used to detect the basic data of the circulating water flow rate of the thermal power plant in real time through sensors and detectors. The basic data includes conductivity, pH value, temperature, liquid level and concentration ratio. The data acquisition unit is used to receive basic data on the current circulating water flow rate of the thermal power plant in real time through a data receiver.

3. The thermal power plant circulating water flow management system based on big data according to claim 2, characterized in that, The object recognition module includes an object recognition unit and an anomaly recording unit; The object recognition unit is used to set the standard data of the circulating water flow rate of the thermal power plant at the current moment, calculate the difference between the standard data and the basic data, and if the difference = 0, it is determined that the basic data of the circulating water flow rate at the current moment is normal; if the difference ≠ 0, it is determined that the basic data of the circulating water flow rate at the current moment is abnormal. The anomaly recording unit is used to record the basic data for determining the current circulating water flow rate in real time through the data tracker, and to identify abnormal data.

4. A big data-based circulating water flow management system for thermal power plants according to claim 3, characterized in that, The traffic diagnosis module includes a diagnosis compensation unit; The diagnostic compensation unit is used to compensate the basic data that identifies abnormal data. The data compensation method is as follows: if the difference is positive, the corresponding basic value is increased; if the difference is negative, the corresponding basic value is decreased.

5. A thermal power plant circulating water flow management system based on big data as described in claim 1, characterized in that, The traffic analysis terminal includes a traffic monitoring module, a traffic analysis module, and a traffic prediction module; The traffic monitoring module includes a traffic monitoring unit and a traffic threshold unit; The flow monitoring unit is used to monitor the basic data of circulating water flow in real time through the data tracker and the circulating water flow monitor; The flow threshold unit is used to set standard data for the circulating water flow rate.

6. A thermal power plant circulating water flow management system based on big data according to claim 5, characterized in that, The flow analysis module is used to analyze the standard data and basic data of circulating water flow. The data analysis method is as follows: Step 1: Calculate the correction difference between the standard data and the baseline data of the circulating water flow rate at the current moment. The calculation formula is as follows: in, This represents the correction difference between the standard data and the baseline data of the circulating water flow rate at the current moment. Indicates the first The basic data of the current circulating water flow rate at a given moment. Indicates the first The basic data of the current circulating water flow rate at a given moment. Indicates the first The lower limit of standard data for circulating water flow rate at a given time. Indicates the first The standard upper limit of circulating water flow rate at any given time. Indicates the first The lower limit of standard data for circulating water flow rate at a given time. Indicates the first The upper limit of standard data for circulating water flow rate at any given moment; Step 2: Calculate the degree of change in the basic data of the circulating water flow. The calculation formula is as follows: in, Indicates the first The degree of change in the basic data of circulating water flow at each moment. Indicates the first Basic data of circulating water flow at time 1 and time 2 The correction difference of the basic data of circulating water flow rate at each time point. Indicates the first Basic data of circulating water flow at time 1 and time 2 The correction difference of the basic data of circulating water flow rate at each time point.

7. A thermal power plant circulating water flow management system based on big data as described in claim 6, characterized in that, The traffic prediction module includes an analysis and prediction unit and a prediction generation unit; The analysis and prediction unit is used to predict the number of circulating pumps that start and stop in each cycle of circulating water flow. Based on the standard of one quarter as a cycle, the number of pumps that start and stop in the second cycle can be calculated from the number of pumps that start and stop in the first cycle using the exponential smoothing method. in, It is the equilibrium constant, and =[0, 1], The number of circulating pumps started and stopped indicates the circulating water flow rate in the first cycle. This indicates the number of times the circulating pump starts and stops in the first cycle. Indicates the number of circulating pumps in the first cycle; The prediction generation unit is used to automatically generate the number of circulating pumps to start and stop in the next cycle based on the analysis and prediction results.

8. A thermal power plant circulating water flow management system based on big data according to claim 1, characterized in that, The early warning self-control terminal includes a contingency plan formulation module, a contingency plan execution module, an execution timing module, and an execution tracking module; The contingency plan formulation module includes a contingency plan receiving unit and an execution timing unit; The contingency plan receiving unit is used to receive the number of cycles without starting or stopping in real time through the data receiver, and generate the contingency plan execution timing instruction according to the corresponding time. The execution timing unit is used to prepare the pre-plan instruction with a standard countdown using a timer, and to execute the pre-plan 10 seconds before the standard countdown preparation.

9. A big data-based circulating water flow management system for thermal power plants according to claim 8, characterized in that, The contingency plan execution module includes a duration calculation unit, which is used to calculate the countdown duration for contingency plan execution in real time using a timer; The execution timing module includes a countdown unit, which is used to track the time difference of the plan execution in real time through a timer.

10. A big data-based circulating water flow management system for thermal power plants according to claim 9, characterized in that, The execution tracking module includes a contingency plan execution unit, an execution tracking unit, and a tracking and early warning unit; The contingency plan execution unit is used to automatically execute the contingency plan 10 seconds before the countdown begins, starting and stopping the corresponding number of circulating pumps. The execution tracking unit is used to track the execution data of the plan in real time through the data tracker. The execution data includes the turbine load value and whether the circulating water temperature has changed. The difference between the turbine load value and the standard load value is calculated. If the difference = 0, the execution data of the plan is determined to be valid. If the difference ≠ 0, the execution data of the plan is determined to be invalid. The principle of whether the circulating water temperature has changed is the same. The tracking and early warning unit is used to formulate a second execution plan when the execution data of the plan is determined to be invalid, until the execution data of the plan is valid.

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