CN118801358A - A method and related device for intelligent collaborative operation of a thermal power plant - Google Patents
A method and related device for intelligent collaborative operation of a thermal power plant Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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Abstract
本发明公开了一种火电厂智慧协同运行方法及相关装置，属于能源数字化、智能化领域，包括以下步骤：实时运行数据通过故障监测模型得到监测指标，判断所述监测指标是否超过预设阈值，若超过则进行预警；进行预警时提取实时运行数据的特征，并与故障特征库进行对比，得到故障自愈指令；根据智能巡航模型得到火电机组的最优运行方式和最优运行参数；根据故障自愈指令完成火电机组故障闭环自愈，同时根据最优运行方式和最优运行参数调整火电机组的运行参数和控制方案，完成火电厂智慧协同运行。本发明能够解决火电厂采用现有技术运行时各运行模块融合交互性低的问题。
The present invention discloses a method and related devices for intelligent collaborative operation of a thermal power plant, which belongs to the field of energy digitization and intelligence, and includes the following steps: real-time operation data obtains monitoring indicators through a fault monitoring model, and determines whether the monitoring indicators exceed a preset threshold value, and if so, issues an early warning; extracts the characteristics of the real-time operation data during the early warning, and compares them with the fault feature library to obtain a fault self-healing instruction; obtains the optimal operation mode and optimal operation parameters of the thermal power unit according to the intelligent cruise model; completes the closed-loop self-healing of the thermal power unit fault according to the fault self-healing instruction, and adjusts the operation parameters and control scheme of the thermal power unit according to the optimal operation mode and optimal operation parameters, and completes the intelligent collaborative operation of the thermal power plant. The present invention can solve the problem of low fusion interactivity of each operation module when the thermal power plant adopts the existing technology for operation.
Description
Technical Field
The invention belongs to the field of energy digitization and intellectualization, and particularly relates to an intelligent collaborative operation method and a related device of a thermal power plant.
Background
Under the environment of a novel power system, thermal power peak regulation and frequency modulation become a normal state, and are faced with multiple pressures such as energy saving and consumption reduction, environment protection monitoring and network regulation assessment, and the situation that key systems, equipment and parameters are manually interfered frequently exists, so that labor intensity is high. At present, although domestic and foreign scientific research institutions, colleges and universities and control equipment manufacturers develop a great deal of research, development and application in detection, control, diagnosis, optimization and the like, and corresponding functional modules are formed, the functional modules are relatively independent, have insufficient fusion interactivity and are difficult to support the targets of unmanned intervention and less duty in the production process of the thermal power plant.
Therefore, the method has important significance in deeply analyzing the expected targets and connection relations of all functional modules in the production process of the thermal power plant and researching a cooperative method of intelligent operation modules of the thermal power plant.
Disclosure of Invention
The invention provides an intelligent collaborative operation method and a related device for a thermal power plant, which are used for solving the problem of low fusion interactivity of operation modules when the thermal power plant operates by adopting the prior art.
In order to achieve the above purpose, the invention adopts the following technical scheme:
An intelligent cooperative operation method of a thermal power plant comprises the following steps:
collecting real-time operation data of the thermal power generating unit, obtaining monitoring indexes through a fault monitoring model, judging whether the monitoring indexes exceed a preset threshold, if yes, carrying out early warning, and if not, keeping normal operation of the thermal power generating unit;
Extracting the characteristics of the real-time operation data during early warning, and comparing the characteristics with a fault characteristic library to obtain a fault self-healing instruction;
Establishing an intelligent cruising model, and obtaining an optimal operation mode and optimal operation parameters of the thermal power generating unit according to the intelligent cruising model;
And completing the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and simultaneously adjusting the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant.
In some embodiments, the fault monitoring model is obtained by:
And acquiring historical operation data of the thermal power generating unit, and establishing a fault monitoring model according to the historical operation data and by adopting a neural network fitting algorithm.
The fault feature library is obtained through the following steps:
And according to the historical operation data, common fault information of the thermal power unit is obtained through self-coding fault feature extraction, and a fault feature library is built according to the common faults of the thermal power unit.
In some embodiments, the smart cruise model is built by:
And acquiring the non-operable parameters and the operable parameters of the thermal power generating unit, processing the non-operable parameters and the operable parameters by adopting historical data mining, and establishing an intelligent cruising model.
In some embodiments, the step of obtaining the optimal operation mode and the optimal operation parameter of the thermal power generating unit according to the intelligent cruising model specifically includes:
After the intelligent cruising model outputs safety stability data, economic environmental protection data and flexible mobility data, weighting evaluation or fitness calculation is carried out, and an optimal operation mode and optimal operation parameters are obtained;
When weighting evaluation is adopted, if the preset iteration times are met, an optimal operation mode and optimal operation parameters are obtained, and if the preset iteration times are not met, the operable parameters are optimized and traversed to update the intelligent cruising model;
when the fitness is adopted for calculation, if the calculated fitness meets the preset fitness, an optimal operation mode and an optimal operation parameter are obtained, and if the calculated fitness does not meet the preset fitness, the operable parameter is optimized and traversed to update the intelligent cruise model.
In some embodiments, the optimization traversal employs a particle swarm algorithm or a genetic algorithm.
In some embodiments, the step of extracting the features of the real-time operation data during early warning and comparing the features with a fault feature library to obtain a fault self-healing instruction further includes the following steps:
and when the characteristics of the real-time operation data extracted during early warning are not in the fault characteristic library after comparison, updating the characteristics of the real-time operation data into the fault characteristic library.
In some embodiments, the method further comprises the steps of:
and replacing PID control of the thermal power generating unit with predictive control, fuzzy control, decoupling control or variable structure control, and adjusting the operation parameters and control scheme of the thermal power generating unit by combining the optimal operation mode and the optimal operation parameters.
An intelligent collaborative operation system of a thermal power plant, comprising:
The intelligent monitoring module is used for collecting real-time operation data of the thermal power generating unit, acquiring monitoring indexes by the real-time operation data through a fault monitoring model, judging whether the monitoring indexes exceed a preset threshold, carrying out early warning if the monitoring indexes exceed the preset threshold, and keeping normal operation if the monitoring indexes do not exceed the preset threshold; the method is used for extracting the characteristics of the real-time operation data during early warning and comparing the characteristics with a fault characteristic library to obtain a fault self-healing instruction;
The intelligent cruising module is used for establishing an intelligent cruising model and obtaining an optimal operation mode and optimal operation parameters of the thermal power generating unit according to the intelligent cruising model;
and the intelligent control module is used for completing the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and adjusting the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant.
An electronic device comprising a memory, a processor and a computer program stored in the memory and executable in the processor, the processor implementing the steps of the intelligent coordinated operation method of a thermal power plant when the computer program is executed.
A computer readable storage medium storing a computer program which when executed by a processor implements the steps of the intelligent co-operating method of a thermal power plant.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an intelligent cooperative operation method of a thermal power plant, wherein real-time operation data obtain monitoring indexes through a fault monitoring model, whether the monitoring indexes exceed a preset threshold value is judged, if yes, early warning is carried out, and if not, a thermal power unit keeps normal operation; extracting characteristics of the real-time operation data during early warning, comparing the characteristics with a fault characteristic library to obtain a fault self-healing instruction, then establishing an intelligent cruising model, and obtaining an optimal operation mode and optimal operation parameters of the thermal power generating unit according to the intelligent cruising model; and completing the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and simultaneously adjusting the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant. The invention can discover potential abnormality and faults of equipment in advance, complete online early warning and closed loop fault self-healing, improve man-machine interaction efficiency, avoid the expansion of fault range, reduce non-planned shutdown risk, ensure the long-period safe and stable operation of the fire motor unit, output optimal operation modes and optimal operation parameters through an intelligent cruising model, perform parameter self-adaptive adjustment and strategy intelligent isomerism of the thermal power unit, further effectively improve the adaptability of a control system to complex working conditions and complex disturbance, and ensure the stability and convergence of the control system. Therefore, through the content, the method and the device can solve the problem of low fusion interactivity of each operation module of the thermal power plant, organically cooperate with each other and support the aim of unmanned intervention and less person on duty in the production process of the thermal power plant.
Further, after the intelligent cruising model is adopted to output safety and stability data, economic and environment-friendly data and flexible mobility data, weighted evaluation or fitness calculation is carried out to obtain an optimal operation mode and optimal operation parameters, optimal start-stop, parallel-stop and rotation time of the thermal power unit can be obtained by optimizing, automatic start-stop of equipment and automatic closed-loop optimization of parameter fixed values are completed, and the manual intervention intensity is effectively reduced while the comprehensive performance of the unit is improved.
Furthermore, the PID control is replaced by the predictive control, so that the control system can be optimized, and the adaptability of the control system to complex working conditions is improved.
The invention provides an intelligent cooperative operation system of a thermal power plant, which comprises an intelligent monitoring disc module, an intelligent cruising module and an intelligent control module, wherein three dimensions of monitoring, optimizing and controlling a production process of the thermal power plant are utilized to clearly divide intelligent functional modules, the division of the intelligent functional modules is clear, the expected targets and the connection relations are clear, and the intelligent cooperative operation system can organically cooperate and support targets which are unmanned in the production process of the thermal power plant and have little person on duty.
Drawings
FIG. 1 is a functional schematic diagram of an intelligent monitoring module according to a first embodiment;
FIG. 2 is a functional schematic of an intelligent cruise module according to one embodiment;
FIG. 3 is a functional schematic of the intelligent control module according to the first embodiment;
FIG. 4 is a schematic diagram showing an intelligent monitoring module, an intelligent cruising module and an intelligent control and control integrated organic integration in the first embodiment;
FIG. 5 is a flowchart of a thermal power plant intelligent cooperative operation method according to an embodiment;
Fig. 6 is a schematic structural diagram of an intelligent collaborative operation system of a thermal power plant according to a first embodiment;
fig. 7 is a block diagram of an electronic device employed in the present invention.
Detailed Description
In order that those skilled in the art may better understand the present invention, a further detailed description of the technical solution of the present invention will be provided with reference to the accompanying drawings, which are intended to illustrate, but not to limit, the present invention.
It should be noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present invention are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed or inherent to such process, method, system, article, or apparatus.
Example 1
As shown in fig. 5, the embodiment provides a thermal power plant intelligent cooperative operation method, which includes the following steps:
Step 1: building intelligent thermal power plant intelligent operation necessary functional module of 1+6+N, forming intelligent monitoring panel, intelligent cruising and intelligent control three major functions system. The intelligent monitoring panel is used for discovering potential abnormality or faults of equipment in advance, reporting the potential abnormality or faults in an online early warning mode, improving man-machine interaction efficiency, and simultaneously carrying out active intervention on diagnosed potential faults by simulating manual operation to realize closed loop fault self-healing. The intelligent cruising optimizes the optimal operation mode and the optimal operation fixed value of the system, the equipment and the parameters, generates the optimal start-stop, parallel-backward and rotation time of the equipment, completes the automatic start-stop of the equipment, generates the optimal operation fixed value of the parameters, and completes the real-time closed-loop optimization. The intelligent control improves the adaptability of the control system to complex working conditions through on-line identification of the model and self-adaptive updating of parameters; and meanwhile, the coupling relevance of production process parameters is synthesized, intelligent isomerism is carried out on the control strategy, and the adaptability of the control system to complex disturbance is improved.
Step 2: as shown in FIG. 1, 1+6+N intelligent monitoring panels of intelligent thermal power plants perform online early warning and closed loop fault self-healing, massive historical operation data are collected from thermal power units, and common faults of unit systems, equipment and parameters are extracted through a self-coding fault feature extraction method to form a fault feature library. And simultaneously, based on massive historical operation data, a neural network fitting algorithm is adopted to establish a fault monitoring model, and monitoring indexes are generated through comparison of the fault monitoring model and real-time operation data. If the monitoring index does not exceed a certain threshold, the thermal power unit operates normally; if the monitoring index exceeds a certain threshold, generating early warning, extracting data features of historical operation data by adopting a self-coding fault feature extraction method, comparing the data features of the faults in a fault diagnosis center and a fault feature library, positioning the faults and generating a fault self-healing instruction. Meanwhile, the fault signature library is updated for typical fault types not included in the fault signature library.
Step 3: as shown in FIG. 2, the intelligent cruising equipment of the 1+6+N intelligent thermal power plant automatically optimizes the automatic start-stop and the fixed value, and divides the operating parameters of the thermal power unit into inoperable parameters and operable parameters, wherein the inoperable parameters comprise unit load, coal heat value, ambient temperature and the like, and the operable parameters comprise climbing speed, steam pressure fixed value, grinding mode, boiler oxygen amount and the like. And taking the non-operational parameters and the operational parameters as inputs, establishing an intelligent cruising model based on a historical data mining mode, wherein the output of the model comprises safety stability data, economic environmental protection data and flexible maneuverability data of unit operation. And (3) evaluating the comprehensive performance of the unit operation by adopting a fitness calculation mode, and outputting an optimal operation mode and optimal operation parameters of the thermal power unit if the fitness index meets the preset fitness requirement, wherein the optimal operation mode and the optimal operation parameters comprise an optimal grinding combination mode, an optimal circulating water pump combination mode, an optimal sliding pressure constant value, an optimal oxygen amount constant value and the like. And (3) carrying out sequential control and analog quantity control optimization on equipment needing start-stop, parallel-stop and rotation, so as to realize the automatic start-stop of the equipment when the unit is cruising and shipping in a wide load range. If the fitness index cannot meet the fitness requirement, the genetic algorithm is adopted to further optimize and traverse the operational parameters of the thermal power generating unit.
Step 4: as shown in fig. 3, the intelligent control parameters of the 1+6+n intelligent thermal power plant are adaptively adjusted and intelligently heterogeneous with strategies, and in an intelligent coordination mode, a unit energy balance strategy is constructed according to main steam pressure setting, actual main steam pressure, a pre-reduction steam temperature, separator outlet pressure, speed-limiting afterload instructions and the like, so that an energy instruction and a heat signal which are suitable for a direct-current furnace are formed. And the prediction control is adopted to replace PID control to be used as a boiler feedback controller, and meanwhile, the speed-limiting afterload instruction is adopted to be used as feedforward to form a boiler main control instruction.
Based on a main control instruction of the boiler, combining main steam pressure setting and actual main steam pressure correction to construct a fuel main control static feedforward; constructing a fuel main control dynamic feedforward according to a target load, a speed limit post-load instruction, an energy instruction, a heat signal and a variable load rate; and constructing an energy storage dynamic compensation feedforward by combining a main steam pressure setting, a middle point temperature setting and a speed limiting afterload instruction; and constructing a temperature balance loop of the unit according to the middle point temperature setting, the actual middle point temperature and the load command after speed limiting, forming a temperature command and a temperature signal, and determining the intensity of respectively adopting coal and water to adjust the superheat degree by adopting a distribution coefficient mode. The predictive control is adopted to replace PID control to be used as a water-fuel ratio feedback controller, and three feedforward are combined to form a fuel main control instruction.
Based on the main control instruction of the boiler, the static feed-forward of the water supply main control is constructed by combining the middle point temperature setting, the actual middle point temperature and the correction of the load instruction after speed limiting. And constructing a feed-water main control dynamic feedforward according to a steam temperature before reduction and a speed-limiting afterload instruction, adopting predictive control instead of PID control as a superheat degree feedback controller, and combining the two feedforward to form the feed-water main control instruction.
Step 5: and completing the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and simultaneously adjusting the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant. As shown in fig. 4, the automatic start-stop process of the coal mill is illustrated as an example. The intelligent cruising can decide the optimal start-stop grinding time according to the load working condition of the unit, the heat value of the coal quality and the power consumption of the coal mill, and the one-key start-stop coal mill program control is triggered through sequential control and analog quantity control design. Meanwhile, the deviation of the main steam pressure and the temperature of the middle point is comprehensively considered, the optimal coal adding and subtracting speed is given by optimizing, and the process is completed and regrind is carried out at a proper time. The intelligent control adopts predictive control to construct an intelligent control system of a cold and hot air door, a coal feeding amount and a rotary separation rotating speed according to the output requirement, the warm grinding speed, the coal feeding speed and the grinding outlet temperature control requirement of the coal mill, and improves the adaptability of the start-stop process control of the coal mill to complex working conditions and complex disturbance. The intelligent monitoring disc monitors whether the coal mill has abnormal working conditions such as coal breakage, blocking grinding, spontaneous combustion, air door blocking and the like in real time, simulates operation of operators, such as starting vibration, improving primary air pressure, reducing air temperature of a grinding inlet, rapidly switching a cold air door and the like, actively intervenes in an intelligent control system of the coal mill, and achieves fault closed-loop self-healing. Thereby completing the intelligent cooperative operation of the thermal power plant.
As shown in fig. 6, the embodiment further provides an intelligent collaborative operation system of a thermal power plant, which comprises an intelligent monitoring module, an intelligent cruising module and an intelligent control module, wherein the intelligent monitoring module collects real-time operation data of the thermal power plant, the real-time operation data obtain monitoring indexes through a fault monitoring model, whether the monitoring indexes exceed a preset threshold value is judged, if the monitoring indexes exceed the preset threshold value, early warning is carried out, and if the monitoring indexes do not exceed the preset threshold value, the thermal power plant keeps normal operation; the method is used for extracting the characteristics of the real-time operation data during early warning and comparing the characteristics with a fault characteristic library to obtain a fault self-healing instruction; the intelligent cruising module establishes an intelligent cruising model, and obtains an optimal operation mode and optimal operation parameters of the thermal power unit according to the intelligent cruising model; and the intelligent control module completes the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and adjusts the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant.
Therefore, the embodiment adopts the intelligent monitoring panel of the 1+6+N intelligent thermal power plant to perform online early warning and closed loop fault self-healing, and can analyze and process the production process data of the thermal power plant in a big data analysis and artificial intelligence mode, so that the quality degree indexes of the system, equipment and parameters are transparent, and the man-machine interaction efficiency is improved in an online early warning mode; meanwhile, for the diagnosed potential faults, the simulation manual operation is used for active intervention, so that closed-loop fault self-healing is realized.
In the automatic start-stop and fixed value automatic optimization of the intelligent cruising equipment of the 1+6+N intelligent thermal power plant, the start-stop, parallel-return and rotation time of production equipment is optimized in a historical data mining mode, and the automatic start-stop of the equipment during cruising operation of the unit in a wide load range is realized by combining sequential control and analog quantity control optimization; meanwhile, the safety stability, the economical efficiency, the environmental protection performance and the flexibility of the unit operation are comprehensively considered, the optimal operation parameter fixed value is optimized in a multi-objective optimization mode, and the comprehensive performance of the unit cruising operation in a wide load range is improved.
In the intelligent control parameter self-adaptive adjustment and strategy intelligent isomerism of the 1+6+N intelligent thermal power plant, a predictive control is adopted to replace a traditional PID control algorithm, a control system is optimized, and the adaptability of the control system to complex working conditions is improved through model on-line identification and parameter self-adaptive update; and meanwhile, the coupling relevance of production process parameters is synthesized, intelligent isomerism is carried out on the control strategy, and the adaptability of the control system to complex disturbance is improved.
Finally, an intelligent monitoring module, an intelligent cruising module and an intelligent control module are adopted to perform 'three-in-one' organic cooperation, an optimal operation mode and optimal operation parameters are issued to intelligent control for execution during intelligent cruising, and an execution result is fed back to the intelligent cruising for further iterative optimization; the intelligent monitoring disc discovers abnormal systems, equipment and parameters or faults in advance, actively adjusts an intelligent cruising mode, intervenes in a control loop and realizes fault closed-loop self-healing; the intelligent control preferably executes the intelligent monitoring instruction and then executes the intelligent cruising instruction. The problem of insufficient fusion interactivity between modules can be fully solved, and the targets of unmanned intervention and less unattended operation in the production process of the thermal power plant are fully supported.
The division of the modules in the embodiments of the present invention is schematically only one logic function division, and there may be another division manner in actual implementation, and in addition, each functional module in each embodiment of the present invention may be integrated in one processor, or may exist separately and physically, or two or more modules may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules.
As shown in fig. 7, there is further provided a computer apparatus in the present embodiment, the computer apparatus including a processor and a memory, the memory being configured to store a computer program (the computer program in the present embodiment includes a calculation component and an iteration component, and is capable of performing model calculation and model update), the computer program including program instructions, the processor being configured to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CentralProcessing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital SignalProcessor, DSP), application SPECIFIC INTEGRATED Circuits (ASIC), off-the-shelf Programmable gate arrays (Field-Programmable GATEARRAY, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computational core and control core of the terminal, adapted to implement one or more instructions, particularly adapted to load and execute one or more instructions in a computer storage medium to implement a corresponding method flow or corresponding function; the processor provided by the embodiment of the invention can be used for operating an intelligent cooperative operation method of a thermal power plant.
The present embodiment also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a Memory device in a computer device, for storing programs and data. It is understood that the computer readable storage medium herein may include both built-in storage media in a computer device and extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also stored in the memory space are one or more instructions, which may be one or more computer programs (including program code), adapted to be loaded and executed by the processor. The computer readable storage medium herein may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of a thermal power plant intelligent co-operation method in the above embodiments.
Example two
The difference from the first embodiment is that in step 3 of the intelligent cooperative operation method of the thermal power plant, the fitness calculation is replaced by the weighted evaluation, when the weighted evaluation is adopted, if the preset iteration number is met, an optimal operation mode and an optimal operation parameter are obtained, and if the preset iteration number is not met, the particle swarm algorithm is adopted to optimize and traverse the operable parameter so as to update the intelligent cruise model.
The predictive control in step 4 is replaced with any one of fuzzy control, decoupling control, or variable structure control.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (10)
1. The intelligent cooperative operation method of the thermal power plant is characterized by comprising the following steps of:
collecting real-time operation data of the thermal power generating unit, obtaining monitoring indexes through a fault monitoring model, judging whether the monitoring indexes exceed a preset threshold, if yes, carrying out early warning, and if not, keeping normal operation of the thermal power generating unit;
Extracting the characteristics of the real-time operation data during early warning, and comparing the characteristics with a fault characteristic library to obtain a fault self-healing instruction;
Establishing an intelligent cruising model, and obtaining an optimal operation mode and optimal operation parameters of the thermal power generating unit according to the intelligent cruising model;
And completing the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and simultaneously adjusting the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant.
2. The intelligent collaborative operation method of a thermal power plant according to claim 1, wherein the fault monitoring model is obtained by:
And acquiring historical operation data of the thermal power generating unit, and establishing a fault monitoring model according to the historical operation data and by adopting a neural network fitting algorithm.
The fault feature library is obtained through the following steps:
And according to the historical operation data, common fault information of the thermal power unit is obtained through self-coding fault feature extraction, and a fault feature library is built according to the common faults of the thermal power unit.
3. The intelligent coordinated operation method of a thermal power plant according to claim 1, wherein the intelligent cruising model is built by:
And acquiring the non-operable parameters and the operable parameters of the thermal power generating unit, processing the non-operable parameters and the operable parameters by adopting historical data mining, and establishing an intelligent cruising model.
4. The intelligent collaborative operation method of a thermal power plant according to claim 3, wherein the step of obtaining an optimal operation mode and an optimal operation parameter of a thermal power unit according to the intelligent cruising model comprises the following steps:
After the intelligent cruising model outputs safety stability data, economic environmental protection data and flexible mobility data, weighting evaluation or fitness calculation is carried out, and an optimal operation mode and optimal operation parameters are obtained;
When weighting evaluation is adopted, if the preset iteration times are met, an optimal operation mode and optimal operation parameters are obtained, and if the preset iteration times are not met, the operable parameters are optimized and traversed to update the intelligent cruising model;
when the fitness is adopted for calculation, if the calculated fitness meets the preset fitness, an optimal operation mode and an optimal operation parameter are obtained, and if the calculated fitness does not meet the preset fitness, the operable parameter is optimized and traversed to update the intelligent cruise model.
5. The intelligent collaborative operation method of a thermal power plant according to claim 4, wherein the optimization traversal employs a particle swarm algorithm or a genetic algorithm.
6. The intelligent collaborative operation method according to claim 1, wherein the step of extracting the characteristics of the real-time operation data and comparing the extracted characteristics with a fault characteristic library to obtain a fault self-healing instruction during early warning, further comprises the steps of:
and when the characteristics of the real-time operation data extracted during early warning are not in the fault characteristic library after comparison, updating the characteristics of the real-time operation data into the fault characteristic library.
7. The intelligent collaborative operation method of a thermal power plant according to claim 1, further comprising the steps of:
and replacing PID control of the thermal power generating unit with predictive control, fuzzy control, decoupling control or variable structure control, and adjusting the operation parameters and control scheme of the thermal power generating unit by combining the optimal operation mode and the optimal operation parameters.
8. An intelligent collaborative operation system of a thermal power plant, which is characterized by comprising:
The intelligent monitoring module is used for collecting real-time operation data of the thermal power generating unit, acquiring monitoring indexes by the real-time operation data through a fault monitoring model, judging whether the monitoring indexes exceed a preset threshold, carrying out early warning if the monitoring indexes exceed the preset threshold, and keeping normal operation if the monitoring indexes do not exceed the preset threshold; the method is used for extracting the characteristics of the real-time operation data during early warning and comparing the characteristics with a fault characteristic library to obtain a fault self-healing instruction;
The intelligent cruising module is used for establishing an intelligent cruising model and obtaining an optimal operation mode and optimal operation parameters of the thermal power generating unit according to the intelligent cruising model;
and the intelligent control module is used for completing the fault closed-loop self-healing of the thermal power unit according to the fault self-healing instruction, and adjusting the operation parameters and the control scheme of the thermal power unit according to the optimal operation mode and the optimal operation parameters to complete the intelligent cooperative operation of the thermal power plant.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and operable in the processor, the processor implementing the steps of a thermal power plant intelligent co-operation method according to any one of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the steps of a thermal power plant intelligent co-operation method according to any one of claims 1 to 7.
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| WO2026007604A1 (en) * | 2024-07-01 | 2026-01-08 | 西安热工研究院有限公司 | Intelligent collaborative operation method for thermal power plant, and related apparatus |
| WO2026007601A1 (en) * | 2024-07-01 | 2026-01-08 | 西安热工研究院有限公司 | Intelligent operation method and system for thermal power plant, device, and storage medium |
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