Intelligent thermal power plant monitoring method and system based on Internet of Things

Abstract

The invention relates to the technical field of thermal power plant management, and particularly discloses an intelligent thermal power plant monitoring method and system based on the Internet of Things, and the system comprises an environmental protection monitoring module, an energy consumption analysis module, an alarm management module, a configuration monitoring module, a data discrimination module, and a system management module. The environmental protection monitoring module is responsible for monitoring whether flue gas dust reaches emission standards or not and whether emission reduction facilities are put into operation according to supervision requirements or not, and the energy consumption analysis module is responsible for completing calculation and statistics of power supply coal consumption of each unit and providing energy consumption analysis and optimization suggestions; the system can monitor the operation state and performance parameters of each key device of a thermal power plant in real time, determines that an emission reduction facility is put into operation according to supervision requirements, timely identifies the abnormal operation or fault of the device, gives out an early warning, prevents the expansion of the device fault and the increase of downtime, analyzes massive operation data through machine learning and data mining technologies, and achieves the real-time monitoring of the thermal power plant. Decision support and optimization suggestions are provided, energy utilization is optimized, emission is reduced, and the influence on the environment is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermal power plant management, and specifically relates to a smart thermal power plant monitoring method and system based on the Internet of Things. Background Art

[0002] The consumption of primary energy such as coal and natural gas is one of the important costs of thermal power plants, and the pollutants generated during the combustion of these energy sources have become the main source of pollution in power plants. The work of thermal power plants has three steps. The first step is to convert chemical energy into thermal energy. Burning fossil fuels in the boiler generates thermal energy, which is absorbed by water and turns into water vapor. The second step is to convert thermal energy into mechanical energy. The thrust generated by high-temperature steam drives the turbine to rotate. The third step is to convert mechanical energy into electrical energy. The rotation of the turbine drives the generator rotor to rotate, and electrical energy is generated by cutting the magnetic lines of force.

[0003] Under the "dual carbon" goal, the country's emission supervision efforts have been continuously strengthened, and the standard limits for environmental protection emissions have become lower and lower. The combustion products of primary energy sources such as coal and natural gas have brought increasing pressure on the operation costs of environmental protection facilities and emission reductions to thermal power companies. At the same time, it has also increased the environmental supervision pressure on environmental protection departments. It is very necessary to comprehensively monitor the operation of each unit's environmental protection facilities, the emission of pollutants, and the energy consumption level of the unit, so that units that meet environmental protection standards and have low energy consumption levels can generate more electricity, and units that do not meet environmental protection standards and have high energy consumption levels can generate less electricity.

[0004] Therefore, it is necessary to propose a smart thermal power plant monitoring method and system based on the Internet of Things to solve the problems existing in the prior art.

[0005] The above information disclosed in this background technology is only used to increase the understanding of the background technology of the present invention and therefore, it may include information that does not constitute the prior art known to ordinary technicians in this field. Summary of the invention

[0006] The purpose of the present invention is to provide a smart thermal power plant monitoring method and system based on the Internet of Things to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A smart thermal power plant monitoring system based on the Internet of Things comprises: an environmental monitoring module, an energy consumption analysis module, an alarm management module, a configuration monitoring module, a data identification module, and a system management module. The environmental monitoring module is responsible for monitoring whether the flue gas dust meets the emission standard and whether the emission reduction facilities are put into operation according to the regulatory requirements. The energy consumption analysis module is responsible for completing the calculation and statistics of the coal consumption of each unit, providing energy consumption analysis and optimization suggestions. The alarm management module is responsible for monitoring the operating status and performance parameters of the thermal power plant, providing real-time safety warnings and emergency response measures. The configuration monitoring module is used to comprehensively display the operating data of each unit to realize convenient monitoring of the operating status of all units. The data identification module is responsible for acquiring and transmitting the operating data of the thermal power plant, and detecting the fault of the measuring point through data verification. The system management module is responsible for coordinating and managing the operation and interaction of each functional module in the system, and providing a multi-level access control and identity authentication mechanism.

[0009] Preferably, the environmental monitoring module uses Spark Streaming to process and analyze real-time data in order to quickly respond to parameter changes, and introduces automation technology to automatically adjust equipment operating parameters according to monitoring data and analysis results to optimize energy efficiency and environmental impact.

[0010] Preferably, the energy consumption analysis module uses an efficient computing engine to calculate the calculation model of each performance indicator according to the set calculation cycle based on the received real-time data, and calculates the energy consumption data that can truly reflect the economic performance of the unit through stable operating condition judgment and set screening conditions.

[0011] The calculated energy consumption data is displayed in real time on the user interface of the monitoring system so that the operator can understand the energy consumption in real time. Typical energy consumption calculations include calculations of electricity consumption, fuel consumption, and heat energy consumption. For example, electricity consumption can be calculated by multiplying power by operating time, and fuel consumption can be calculated by using fuel flow and fuel calorific value.

[0012] Preferably, the alarm management module has upper and lower limit exceeding alarms for all real-time data or indicators, and monitors the internal and external safety conditions of the thermal power plant. It combines automation technology to automatically implement emergency response measures at the same time as the alarm to ensure the safety of personnel and facilities.

[0013] The alarm management module includes start-up and shutdown alarms, value over-limit alarms, and node alarms. When the unit is started or shut down, an alarm message is sent to the relevant system users in the form of a pop-up window or text message; when the indicator value exceeds the set upper and lower limits or alarm value, the value turns red to prompt the user to check the abnormality of the measuring point in time, and the start and end time, over-limit duration, maximum value and other information are counted, so as to retain basic information for problem finding and fault analysis; when a network node has data interruption or data is not updated, a pop-up alarm is given, and the alarm information is pushed to the maintenance personnel so that the problem can be discovered and solved in time.

[0014] Preferably, the configuration monitoring module integrates data analysis tools to perform trend analysis, helping to improve the overall operating efficiency of the thermal power plant, predicting the operating status of the thermal power plant based on historical data through machine learning, and providing managers with intelligent decision support and operation optimization suggestions in combination with upper and lower limit violations.

[0015] Preferably, the data identification module adopts a combination of the Internet of Things and data mining to obtain real-time data of different focuses of the thermal power plant. Through the superposition of upper and lower limit tests, standard deviation tests, and 53H method tests, the measurement point failure can be detected in time, and the measurement point maintenance can be arranged in time.

[0016] Preferably, the system management module supports customized report generation function, provides data analysis and visualization according to the needs of managers and decision makers, provides regular system maintenance plans and remote support services to ensure the stability and reliability of the system, manages the user permissions and role allocation of the system, ensures that different users can access the data and functions they need, while ensuring data security and privacy protection, supports configuration and adjustment of system parameters, such as data collection frequency, alarm thresholds, communication protocols, etc., and can dynamically schedule and optimize system resources according to needs to improve system performance and efficiency.

[0017] A smart thermal power plant monitoring method based on the Internet of Things, comprising:

[0018] Step 1: Collect various data in real time through the Internet of Things technology, and transmit the collected data to the data center through the network dedicated line as the main channel;

[0019] Step 2: After data is screened and preprocessed, it is calculated and counted, and the results are stored in the relational database and the real-time database respectively;

[0020] Step 3: Use data mining to process real-time collected data and apply machine learning to extract useful information and patterns hidden in the data;

[0021] Step 4: Set up an alarm mechanism to generate alarms based on preset parameters and conditions to ensure that administrators can respond and handle exceptions quickly;

[0022] Step 5: Continuously optimize the operating procedures and equipment configuration of the thermal power plant based on the analysis results to avoid or reduce possible failures and losses.

[0023] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor implements a smart thermal power plant monitoring system based on the Internet of Things as described above.

[0024] A terminal device includes a processor and a computer-readable storage medium, the processor is used to implement various instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded and executed by the processor in any one of the above-mentioned smart thermal power plant monitoring systems based on the Internet of Things.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present invention can monitor the operating status and performance parameters of key equipment in thermal power plants in real time, determine whether emission reduction facilities are put into operation in accordance with regulatory requirements, promptly identify equipment operating abnormalities or failures and issue early warnings to prevent the expansion of equipment failures and the increase of downtime. It can analyze massive amounts of operating data through machine learning and data mining technology, provide decision support and optimization suggestions, and thus optimize energy utilization and reduce emissions, reduce the impact on the environment, promote the development of thermal power plants in a cleaner and more efficient direction, and promote the realization of sustainable development goals.

[0027] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a framework diagram of the smart thermal power plant monitoring system of the present invention;

[0029] Figure 2 This is a flow chart of the smart thermal power plant monitoring method of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0031] Embodiment 1:

[0032] See also Figure 1-Figure 2 As shown, a smart thermal power plant monitoring system based on the Internet of Things includes: an environmental monitoring module, an energy consumption analysis module, an alarm management module, a configuration monitoring module, a data identification module, and a system management module. The environmental monitoring module is responsible for monitoring whether the flue gas dust meets the emission standards and whether the emission reduction facilities are put into operation according to regulatory requirements. The energy consumption analysis module is responsible for completing the calculation and statistics of the coal consumption of each unit, providing energy consumption analysis and optimization suggestions. The alarm management module is responsible for monitoring the operating status and performance parameters of the thermal power plant, providing real-time safety warnings and emergency response measures. The configuration monitoring module is used to comprehensively display the operating data of each unit to achieve convenient monitoring of the operating conditions of all units. The data identification module is responsible for acquiring and transmitting the operating data of the thermal power plant, and detecting measurement point failures through data verification. The system management module is responsible for coordinating and managing the operation and interaction of various functional modules in the system, and providing a multi-level access control and identity authentication mechanism.

[0033] The environmental monitoring module uses Spark Streaming to process and analyze real-time data in order to quickly respond to parameter changes. It introduces automation technology to automatically adjust equipment operating parameters based on monitoring data and analysis results to optimize energy efficiency and environmental impact.

[0034] By using the flue gas parameters at the chimney inlet (such as smoke concentration at the chimney inlet), it is determined whether the current flue gas parameter emissions meet the standards. Real-time alarms are given to units that exceed the standards and detailed historical alarm inquiries are provided so that relevant personnel can promptly understand the information of exceeding the standards and take timely treatment measures. In addition, through statistical analysis of environmental monitoring parameters and the operation of environmental protection facilities, units that exceed the standards can be queried according to different cycles. If the online power data of the high-voltage side gateway meter of the main transformer of each unit is collected from the power grid dispatching technical support system, the environmental power can be calculated.

[0035] The energy consumption analysis module uses an efficient computing engine to calculate the calculation model of each performance indicator according to the set calculation cycle based on the received real-time data, and calculates the energy consumption data that can truly reflect the economic performance of the unit through stable operating condition judgment and set screening conditions.

[0036] The screening conditions include equipment operating status (normal operating status, equipment stability), environmental conditions (ambient temperature and humidity, air density), fuel characteristics (fuel quality and calorific value, fuel flow and supply quality), electrical parameters (voltage and frequency), and data collection cycle (data collection frequency).

[0037] The alarm management module has upper and lower limit exceeding alarms for all real-time data or indicators, and monitors the internal and external safety of the thermal power plant. Combined with automation technology, it automatically implements emergency response measures at the same time as the alarm to ensure the safety of personnel and facilities.

[0038] The configuration monitoring module integrates data analysis tools for trend analysis to help improve the overall operating efficiency of thermal power plants. It uses machine learning to predict the operating status of thermal power plants based on historical data, and provides managers with intelligent decision support and operation optimization suggestions based on upper and lower limit violations.

[0039] The data identification module uses a combination of the Internet of Things and data mining to obtain real-time data of different focuses of thermal power plants. Through the superposition of upper and lower limit tests, standard deviation tests, and 53H method tests, it can detect measurement point failures in a timely manner and arrange measurement point maintenance in a timely manner.

[0040] In the data mining process, we first scan the data stored in the data center, generate candidate item sets, and calculate the support of each data in the item set. The formula is as follows:

[0041]

[0042] Among them, P(X) and P(Y) represent the probability of information data X and Y appearing respectively, and P(X∪Y) is the probability of information data X and Y appearing at the same time. Compare the relationship between the data support and the minimum data support. If the data support is higher than the minimum support, the frequent item set can be directly obtained, otherwise exit the data mining program. According to the above process, multiple candidate item sets and frequent item sets are connected and generated until no new candidate item sets are generated, and the mining is completed.

[0043] Example: The mining process of flue gas circulation emission data is as described above. To realize the automatic mining of flue gas circulation emission data, the maximum number of data mining iterations is set to 50, the mining time interval is 0.5s, and the mining program is automatically exited when the maximum number of iterations is reached. The mining results of flue gas circulation emission data can be expressed as:

[0044]

[0045] Among them, M i and Q i They are the quality of coal and its lower calorific value respectively.

[0046] The system management module supports customized report generation, provides data analysis and visualization according to the needs of managers and decision makers, and provides regular system maintenance plans and remote support services to ensure system stability and reliability.

[0047] A smart thermal power plant monitoring method based on the Internet of Things, comprising:

[0048] Step 1: Collect various data in real time through the Internet of Things technology, and transmit the collected data to the data center through the network dedicated line as the main channel;

[0049] Step 2: After data is screened and preprocessed, it is calculated and counted, and the results are stored in the relational database and the real-time database respectively;

[0050] Step 3: Use data mining to process real-time collected data and apply machine learning to extract useful information and patterns hidden in the data;

[0051] Step 4: Set up an alarm mechanism to generate alarms based on preset parameters and conditions to ensure that administrators can respond and handle exceptions quickly;

[0052] Step 5: Continuously optimize the operating procedures and equipment configuration of the thermal power plant based on the analysis results to avoid or reduce possible failures and losses.

[0053] The data collected in real time is transmitted to the data center through the Internet of Things protocol (such as MQTT, CoAP, etc.). Encryption and authentication mechanisms are used to prevent data leakage and tampering, ensure the security and reliability of data transmission, and provide detailed information on abnormal data and recommended repair measures based on abnormal situations to help operation and maintenance personnel respond and handle problems quickly. During the optimization process, based on real-time data and historical analysis, optimization suggestions for unit operation are provided, including energy conservation and emission reduction and equipment maintenance plans.

[0054] From the above, it can be seen that the present invention can monitor the operating status and performance parameters of key equipment in thermal power plants in real time, determine whether emission reduction facilities are put into operation according to regulatory requirements, promptly identify abnormal equipment operation or failures and issue early warnings, prevent the expansion of equipment failures and the increase of downtime, analyze massive operating data through machine learning and data mining technology, provide decision support and optimization suggestions, and thus optimize energy utilization and reduce emissions, reduce the impact on the environment, promote the development of thermal power plants in a cleaner and more efficient direction, and promote the realization of sustainable development goals.

[0055] Embodiment 2:

[0056] An embodiment of the present invention also provides a terminal device, including a processor and a computer-readable storage medium, the processor is used to implement various instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and executing any of the above-mentioned smart thermal power plant monitoring system based on the Internet of Things.

[0057] The embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, each process of the above-mentioned smart thermal power plant monitoring system embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. Among them, the computer-readable storage medium, such as read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random ACGess Memory, referred to as RAM), a disk or an optical disk, etc.

[0058] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0059] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a program, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A way to specify functions in one or more boxes.

[0060] In the drawings of the embodiments disclosed in the present invention, only the structures involved in the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

[0061] Although 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 the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart thermal power plant monitoring system based on the Internet of Things, characterized in that: include: Environmental monitoring module, energy consumption analysis module, alarm management module, configuration monitoring module, data identification module, system management module. The environmental monitoring module is responsible for monitoring whether the flue gas dust meets the emission standards and whether the emission reduction facilities are put into operation according to regulatory requirements. The energy consumption analysis module is responsible for completing the calculation and statistics of the coal consumption of each unit, providing energy consumption analysis and optimization suggestions. The alarm management module is responsible for monitoring the operating status and performance parameters of the thermal power plant, providing real-time safety warnings and emergency response measures. The configuration monitoring module is used to comprehensively display the operating data of each unit to achieve convenient monitoring of the operating conditions of all units. The data identification module is responsible for the acquisition and transmission of the operating data of the thermal power plant, and detects the fault of the measuring point through data verification. The system management module is responsible for coordinating and managing the operation and interaction of various functional modules in the system, and providing a multi-level access control and identity authentication mechanism.

2. According to claim 1, a smart thermal power plant monitoring system based on the Internet of Things is characterized by: The environmental monitoring module uses Spark Streaming to process and analyze real-time data in order to quickly respond to parameter changes. It introduces automation technology to automatically adjust equipment operating parameters according to monitoring data and analysis results to optimize energy efficiency and environmental impact.

3. According to claim 2, a smart thermal power plant monitoring system based on the Internet of Things is characterized by: The energy consumption analysis module uses an efficient computing engine to calculate the calculation model of each performance indicator according to the set calculation cycle based on the received real-time data, and calculates the energy consumption data that can truly reflect the economic performance of the unit through stable operating condition judgment and set screening conditions.

4. According to claim 3, a smart thermal power plant monitoring system based on the Internet of Things is characterized by: The alarm management module has upper and lower limit exceeding alarms for all real-time data or indicators, and monitors the internal and external safety conditions of the thermal power plant. Combined with automation technology, it automatically implements emergency response measures at the same time as the alarm to ensure the safety of personnel and facilities.

5. According to claim 4, a smart thermal power plant monitoring system based on the Internet of Things is characterized by: The configuration monitoring module integrates data analysis tools to perform trend analysis, helping to improve the overall operating efficiency of the thermal power plant. It predicts the operating status of the thermal power plant based on historical data through machine learning, and provides managers with intelligent decision support and operation optimization suggestions in combination with upper and lower limit violations.

6. The smart thermal power plant monitoring system based on the Internet of Things according to claim 5 is characterized by: The data identification module adopts the combination of Internet of Things and data mining to obtain real-time data of different focuses of the thermal power plant. Through the superposition of upper and lower limit inspection, standard deviation inspection and 53H method inspection, the fault of the measuring point can be detected in time, and the maintenance of the measuring point can be arranged in time.

7. The smart thermal power plant monitoring system based on the Internet of Things according to claim 6 is characterized by: The system management module supports customized report generation, provides data analysis and visualization according to the needs of managers and decision makers, and provides regular system maintenance plans and remote support services to ensure the stability and reliability of the system.

8. A smart thermal power plant monitoring method based on the Internet of Things, characterized in that: include: Step 1: Collect various data in real time through the Internet of Things technology, and transmit the collected data to the data center through the network dedicated line as the main channel; Step 2: After data is screened and preprocessed, it is calculated and counted, and the results are stored in the relational database and the real-time database respectively; Step 3: Use data mining to process real-time collected data and apply machine learning to extract useful information and patterns hidden in the data; Step 4: Set up an alarm mechanism to generate alarms based on preset parameters and conditions to ensure that administrators can respond and handle exceptions quickly; Step 5: Continuously optimize the operating procedures and equipment configuration of the thermal power plant based on the analysis results to avoid or reduce possible failures and losses.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the processor implements the smart thermal power plant monitoring system based on the Internet of Things as described in claims 1-7.

10. A terminal device, characterized in that: A smart thermal power plant monitoring system based on the Internet of Things comprises a processor and a computer-readable storage medium, the processor is used to implement each instruction; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded and executed by the processor according to any one of claims 1-7.

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