System and method for improving automatic control level of generator set

Abstract

The invention discloses a system and method for improving the automatic control level of a generator set. The system comprises a thermal control measuring point and control equipment module, a DCS transformation capacity expansion module, a DCS control system optimization module and a control logic improvement optimization module. The method comprises the steps of installation of measuring point equipment, capacity expansion of a DCS system, optimization of a control algorithm, improvement of control logic and the like, accurate data acquisition is realized through a sensor and corollary equipment, hardware capacity expansion of the DCS system is carried out to improve the data processing capability, and a Kalman filtering data fusion technology and a genetic algorithm are adopted to optimize data processing and control parameters. The control logic is improved by utilizing a Petri network logic model and a simulation test, so that the data acquisition accuracy is remarkably improved, the heat efficiency of the generator set is improved, the fluctuation range of steam parameters is narrowed, the control response speed is improved, and the flexibility, reliability and operation economy of automatic control of the generator set are effectively improved; the method is suitable for upgrading and reconstruction of various generator set control systems.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of automatic control of generator sets, and particularly relates to a system and method for improving the automatic control level of a generator set, which can be widely applied to the control system upgrading and reconstruction scene of various types of generator sets such as coal-fired and gas-fired generator sets. BACKGROUND

[0002] In the modern power industry system, as the core equipment of power generation, the stability and efficiency of the generator set directly affect the reliability and economy of power supply. With the continuous expansion of the power system scale, the increasing complexity of the power grid structure, and the continuous rise of user requirements for power quality, the traditional generator set control system gradually reveals many drawbacks. From the perspective of primary equipment, the existing measurement point configuration has obvious deficiencies. Taking temperature measurement points as an example, the temperature sensor used by some traditional systems has a measurement accuracy of only ±1℃, which cannot accurately capture the subtle temperature changes of key equipment under complex working conditions; the accuracy of pressure measurement points is generally ±1% FS, and in a high-pressure and high-dynamic operating environment, it cannot provide accurate data support for automatic control. This single type of measurement point and limited accuracy result in information loss or deviation when the control system monitors the operating state of the generator set, and further lead to slow response and inaccurate adjustment of automatic control.

[0003] In terms of DCS control system hardware, the problem of outdated equipment is prominent. Taking a generator set with a service life of more than 5 years as an example, the analog input / output card channel of the DCS system is limited in number, which can only meet the data acquisition needs of basic measurement points and is difficult to meet the data processing requirements of newly added equipment and measurement points; the data transmission rate of the communication module is only 100 Mbps, and when facing a large amount of real-time data transmission, problems such as data congestion and packet loss are likely to occur, which seriously restricts the real-time monitoring and rapid response capability of the system to the operating state of the generator set. At the control logic level, traditional design is mostly based on fixed rules and experience, and lacks intelligent adaptive capability. When the load of the generator set changes significantly in a short time, such as from full load to 50% load, the traditional control logic cannot timely and effectively adjust the control strategy, resulting in a main steam temperature fluctuation range of ±10℃, which not only affects the operating efficiency of the generator set and increases coal consumption, but also threatens the safe and stable operation of the equipment and shortens the service life of the equipment. Therefore, it is a key problem to be solved in the power industry to adaptively transform the control system of the generator set and improve its automatic control level. SUMMARY

[0004] The application aims at realizing deep integration and precise adaptation of primary equipment and intelligent control system by overall upgrading of control system primary equipment and deep optimization of control logic, thereby significantly enhancing flexibility, reliability and intelligent degree of automatic control of generator set, effectively reducing operation cost, improving power generation efficiency and providing solid guarantee for stability, safety and high efficiency of power supply.

[0005] In order to realize the above-mentioned purpose, the application is realized by the following technical scheme:

[0006] The application is a system for improving automatic control level of generator set, comprising a DCS control system, characterized in that the DCS control system is additionally provided with a thermal control measuring point and control equipment module, a DCS reform and capacity expansion module, a DCS control system optimization module and a control logic improvement and optimization module.

[0007] The thermal control measuring point and control equipment module comprises temperature measuring points, pressure measuring points and flow measuring points, and a platinum resistance temperature sensor with a model of PT100 corresponding to the temperature measuring points, a temperature transmitter with a model of SBWR, a piezoresistive pressure sensor with a model of CYB130 corresponding to the pressure measuring points, a pressure transmitter with a model of 3051, an electromagnetic flowmeter with a model of LDG corresponding to the flow measuring points and a flow transmitter with a model of FX-100, for improving flexibility and reliability of automatic control.

[0008] The DCS reform and capacity expansion module comprises 8 analog input and output card pieces with a model of Xinhua Control XDPS-400e, 12 digital input and output card pieces with a model of Xinhua Control XDPS-400e, 2 Ethernet communication modules with a model of MOXA EDS-516A, 3 Profibus communication modules with a model of Siemens 6ES7972-0BA52-0XA0 and a control cabinet, for expanding capacity of the control system.

[0009] The DCS control system optimization module adopts a Kalman filter data fusion technology based on a formula

[0010] X k|k =X k|k-1 +K k (Z k -H k X k|k-1 ) and a genetic algorithm optimization strategy with a fitness function to optimize the unit DCS control system; wherein in the Kalman filter formula, X k|k is an optimal estimation value at k moment, X k|k-1 is a prediction value at k moment, K k is a Kalman gain and Z kis the measured value at time k, H k is a measurement matrix; in the genetic algorithm fitness function, E is the objective function value, w i is a weight coefficient, e i is an error;

[0011] The control logic improvement optimization module improves and optimizes the logic of the unit DCS control system by establishing a Petri net logic model and performing MATLAB / Simulink simulation test, so as to realize the change of the control logic and mode.

[0012] Preferably, the measurement accuracy of the temperature measuring point is ±0.1 DEG C, the measurement accuracy of the pressure measuring point is ±0.25% FS, and the measurement accuracy of the flow measuring point is ±0.5%.

[0013] Preferably, each of the analog input / output cards has 16 channels, and a single digital input / output card supports 32 digital channels.

[0014] Preferably, the Ethernet communication module supports 1000Mbps high-speed data transmission, and the Profibus communication module supports a communication rate of 12Mbps.

[0015] Preferably, the control cabinet is internally provided with a power distribution unit with a model of Delta DVP-ES2 and a network switch with a model of Huawei S5720-36C-EI-24S-AC.

[0016] The method for improving the automatic control level of the generator set comprises the following steps:

[0017] Step one: install a platinum resistance temperature sensor with a model of PT100, a temperature transmitter with a model of SBWR, a piezoresistive pressure sensor with a model of CYB130, a pressure transmitter with a model of 3051, an electromagnetic flowmeter with a model of LDG, a flow transmitter with a model of FX-100, and corresponding temperature measuring points, pressure measuring points and flow measuring points, to improve the flexibility and reliability of automatic control;

[0018] Step two: increase 8 analog input / output cards with a model of Xinhua Control XDPS-400e, 12 digital input / output cards with a model of Xinhua Control XDPS-400e, 2 Ethernet communication modules with a model of MOXA EDS-516A, 3 Profibus communication modules with a model of Siemens 6ES7972-0BA52-0XA0, expand the control system, and increase 2 control cabinets with a model of Weitu TS8837.320;

[0019] Step three: for the newly added temperature measuring point, pressure measuring point, flow measuring point and corresponding sensor and transmitter, the Kalman filter data fusion technology based on public X k|k = X k|k-1 + K k (Z k -H k X k|k-1 ) is adopted, and the genetic algorithm optimization strategy with fitness function is adopted to optimize the unit DCS control system.

[0020] Step four: for the change of control logic and mode, the Petri net logic model is established, and MATLAB / Simulink simulation test is carried out to improve and optimize the logic of the unit DCS control system.

[0021] Preferably, in step one, the installation position of the temperature measuring point includes the boiler superheater header at each stage, and the steam cylinder body of the steam turbine; the installation position of the pressure measuring point includes the main steam pipeline and the steam extraction pipeline; the installation position of the flow measuring point includes the feedwater pipeline and the condensate pipeline.

[0022] Preferably, in step two, when installing the analog input / output card, according to the definition of the wiring terminal, the output signals of the temperature sensor, the pressure sensor and the flow transmitter are connected to the corresponding analog input channel, and three-wire or four-wire wiring method is adopted; when installing the digital input / output card, the start / stop signal and the state feedback signal of the equipment are connected to the digital input channel, and the control instruction signal is led out from the digital output channel to the actuator.

[0023] Preferably, in step three, when the Kalman filter data fusion technology is adopted, the Kalman filter parameters are first initialized according to the system state equation and the measurement equation, including setting the state estimation covariance matrix P0 as the unit matrix, setting the process noise covariance matrix Q as 0.01I according to the system dynamic characteristics, setting the measurement noise covariance matrix R as 0.1I according to the sensor accuracy, and I is the unit matrix; when the genetic algorithm optimization strategy is adopted, the population size is set to 50, the crossover probability is set to 0.8, the mutation probability is set to 0.05, and the maximum iteration number is set to 100 times.

[0024] Preferably, in step four, when the Petri net logic model is established, the system state is defined by the library, the event trigger is represented by the transition, and the relationship between the state and the event is represented by the arc; when the MATLAB / Simulink simulation test is carried out, the simulation system including the boiler model, the steam turbine model, the generator model and the auxiliary machine model is built, and various working conditions such as the unit from 50% load to 80% load and the power grid frequency fluctuation ±0.5Hz are set to test.

[0025] Beneficial effects: Data collection precision: Through the thermal control measuring point and control equipment module, high-precision temperature, pressure, and flow sensors and supporting transmitters are deployed, such as PT100 platinum resistance temperature sensors with a measurement accuracy of ±0.1℃, CYB130 pressure resistance pressure sensors with an accuracy of ±0.25%FS, etc. Compared with traditional systems, the accuracy of data collection is significantly improved, providing solid data support for automatic control, enabling the control system to more accurately perceive the unit operating state.

[0026] Hardware performance upgrade: The DCS transformation and expansion module adds analog and digital input and output cards and high-speed communication modules, such as 8 new China XDPS-400e analog input and output cards, 2 MOXA EDS-516A Ethernet communication modules supporting 1000Mbps transmission, etc. The system's data processing and transmission capabilities are greatly enhanced, with data transmission delay reduced by more than 60%, effectively solving the problems of data loss and slow response caused by hardware deficiencies in the original system.

[0027] Data processing and control optimization: The DCS control system optimization module uses Kalman filter data fusion technology and genetic algorithm to fuse and process collected data and optimize control parameters. Kalman filtering improves data stability by an average of 40%, and genetic algorithm optimization improves unit thermal efficiency by 2.3%-5.8%, reduces steam parameter fluctuation range by 30%-60%, significantly improving system control accuracy and operational economy.

[0028] Intelligent adaptation of control logic: The control logic improvement and optimization module uses Petri net logic model and MATLAB / Simulink simulation testing to reconstruct and optimize control logic. Under varying load conditions, control response speed is improved by 50% and control accuracy is improved by 40%, effectively ensuring stable operation of the unit under complex conditions and reducing equipment failure rate.

[0029] Significant effect of method implementation: Through clear implementation steps, from measuring point device installation, DCS system transformation and expansion to algorithm optimization and field debugging, the integrity and effectiveness of system transformation are ensured. In actual cases, after the transformation of a 1000MW coal-fired unit, the steam turbine speed and main steam pressure fluctuation under varying load conditions are significantly reduced, and the operation stability and efficiency are greatly improved. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present application will be described below in conjunction with specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0031] The application provides a system for improving the automatic control level of a generator set, which is mainly used for reforming a DCS control system used in a traditional power plant, and is composed of the following four core modules in the reforming process:

[0032] The thermal control measuring point and control equipment module: the module is constructed by deploying high-precision thermal control measuring points and supporting equipment, and a comprehensive and accurate operation parameter monitoring system is constructed. A platinum resistance temperature sensor with a model of PT100 is used as a temperature measuring point, the measuring range of the temperature measuring point covers -200℃-850℃, the measuring accuracy can reach ±0.1℃ in the full range, a temperature transmitter with a model of SBWR is used, the temperature signal can be stably converted into a standard 4-20mA current signal, and the accuracy and stability of data transmission are ensured; a pressure resistance pressure sensor with a model of CYB130 is used as a pressure measuring point, the range can be flexibly set according to actual needs, the accuracy is as high as ±0.25%FS, a pressure transmitter with a model of 3051 is used, high-precision acquisition and reliable transmission of the pressure signal are realized; an electromagnetic flowmeter with a model of LDG is used as a flow measuring point, the measuring accuracy is ±0.5%, the range is 0-10000m 3 / h, a flow transmitter with a model of FX-100 is used, and the flow data of various working mediums can be accurately measured. The measuring points and the equipment work cooperatively, the key operation parameters such as the boiler superheated steam temperature, the turbine inlet pressure and the feed water flow can be accurately and timely collected, rich and reliable data basis is provided for the automatic control system, and the flexibility and reliability of the automatic control are effectively improved.

[0033] DCS expansion module: This module upgrades the control system with full- range hardware expansion. Eight XDPS-400e analog input / output cards from Xinhua Control are added, each with 16 channels to meet the precise acquisition of a large number of new measurement points and the accurate output of control commands. Twelve XDPS-400e digital input / output cards are also added, each supporting 32 digital channels to efficiently handle digital signals such as device start / stop and status feedback. Two MOXA EDS-516A Ethernet communication modules are deployed to support 1000Mbps high-speed data transmission and achieve high-speed and stable data interaction with external intelligent devices. Three Profibus communication modules from Siemens (6ES7972-0BA52-0XA0) are installed to ensure reliable communication with fieldbus devices at a communication rate of up to 12Mbps. Additionally, two control cabinets from Weituo (TS8837.320) are added, each integrated with a power distribution unit from Delta (DVP-ES2) to provide stable and reliable power supply for the system. A network switch from Huawei (S5720-36C-EI-24S-AC) is also equipped to optimize the network architecture and improve data exchange efficiency. By optimizing internal wiring and heat dissipation design, a stable operating environment is created for hardware devices, and the data processing capacity and overall control capacity of the DCS control system are improved, ensuring efficient management and precise control of new equipment and measurement points.

[0034] DCS control system optimization module: To handle the massive data generated by the newly added thermal control measurement points and devices, this module employs advanced data processing and optimization techniques. The Kalman filter data fusion technology based on the formula X k|k = X k|k-1 + K k (Z k - H k X k|k-1 ) is introduced to accurately construct system state equations and measurement equations, fuse multiple source heterogeneous data such as temperature, pressure, and flow, effectively suppress data noise interference, and significantly improve data accuracy and reliability. Meanwhile, the genetic algorithm optimization strategy with fitness function is adopted to globally optimize key control parameters in the DCS control system, aiming to maximize the thermal efficiency of the generator set and optimize the stability of steam parameters. Based on the real-time operating state of the unit, control parameters are dynamically adjusted, control strategies are optimized, and the processing efficiency and control accuracy of the system for complex data are significantly improved, achieving efficient and stable operation of automatic control.

[0035] The control logic improvement optimization module: when the control logic and mode change due to load adjustment, equipment maintenance and other reasons during the operation of the generator set, the module uses Petri net logical modeling method to formally and accurately describe the control system logic. By defining the library to represent the system state, the transition to represent the event trigger, and the arc to represent the relationship between the state and the event, the logical association and execution sequence of each control link are clearly presented. With the help of MATLAB / Simulink simulation platform, according to the actual operation parameters of the generator set, a high-precision simulation model including the boiler, steam turbine, generator and auxiliary equipment is built. Set the unit from 50% load to 80% load, power grid frequency fluctuation ± 0.5 Hz and other complex conditions for simulation test, based on the simulation results, the control logic parameters and structure are optimized and adjusted to ensure that the control logic can accurately adapt to the control requirements of the generator set under different operating conditions, significantly improving the accuracy and reliability of automatic control.

[0036] Correspondingly, the application also provides a method for improving the automatic control level of a generator set, and the specific implementation steps are as follows:

[0037] Step one: add new thermal control measuring points and equipment installation: at the key parts of the boiler steam-water system, steam turbine body and auxiliary system of the generator set, strictly according to the installation specification and design requirements, deploy temperature measuring points, pressure measuring points and flow measuring points, and install corresponding type sensors and transmitters. The temperature measuring points are installed at the key positions of the boiler superheater header, the reheater inlet and outlet, the steam cylinder body of the steam turbine, the bearing seat and the like; the pressure measuring points are arranged in the main steam pipeline, the feedwater pipeline, the extraction steam pipeline and the condensate pipeline; the flow measuring points are arranged in the feedwater pipeline, the desuperheating water pipeline, the circulating water pipeline and the condensate pipeline. Taking the installation of the temperature measuring point at the outlet of the boiler superheater as an example, a platinum resistance temperature sensor with a model of PT100 is accurately inserted into the center position of the superheater pipeline to ensure sufficient contact with the steam, a three-wire connection method is used, the sensor signal is transmitted to a temperature transmitter with a model of SBWR through a special shielded cable, and after conversion by the temperature transmitter, the signal is connected to the analog input channel of the DCS control system, thereby completing the high-quality construction of the data acquisition link and realizing the comprehensive and accurate acquisition of the operation parameters of the generator set, laying a solid data foundation for automatic control.

[0038] Step two: DCS system transformation and expansion: During the DCS system shutdown transformation stage, first, the original system architecture is comprehensively evaluated and deeply planned to determine a scientific and reasonable expansion scheme. According to the design requirements, 8 pieces of XDPS-400e analog input / output card, 12 pieces of XDPS-400e digital input / output card, 2 pieces of MOXA EDS-516A Ethernet communication module and 3 pieces of Profibus communication module of Siemens 6ES7972-0BA52-0XA0 are installed in turn. During the installation process of the analog input / output card, strictly according to the definition of the wiring terminal, the output signals of the temperature sensor, pressure sensor and flow transmitter are accurately connected to the corresponding analog input channel, and the three-wire or four-wire wiring method is adopted to ensure the accuracy and anti-interference of signal transmission; when installing the digital input / output card, the start / stop signal and state feedback signal of the equipment are connected to the digital input channel, and the control command signal is accurately led out from the digital output channel to the actuator. At the same time, 2 pieces of Weitu TS8837.320 control cabinet are reasonably arranged in place, and devices such as power distribution unit of Delta DVP-ES2 and network switch of Huawei S5720-36C-EI-24S-AC are installed inside the cabinet, the cable laying path is carefully planned, and clear and standardized identification management is done to ensure the smooth completion of the hardware architecture upgrade of the DCS control system and greatly improve the data processing and control capability of the system.

[0039] Step three: DCS control system optimization implementation: For the newly added thermal control measurement points and the data collected by the equipment, integrate the Kalman filter data fusion algorithm program module and the genetic algorithm optimization program at the software level of the DCS control system.

[0040] X k = AX k-1 + BU k-1 + W k-1 and the observation equation Z k = HX k + V k , combined with the actual operation characteristics of the generator set, the Kalman filter parameters are initialized. The state estimation covariance matrix P0 is set as the unit matrix This indicates that the estimation of the system state has a large uncertainty in the initial stage; the process noise covariance matrix Q is set to reflects the degree of random disturbance of the internal state change of the system; the measurement noise covariance matrix R is set to reflects the error level in the sensor measurement process.

[0041] Taking the fusion of boiler reheat steam temperature and flow data as an example, the system acquires signals in real time through temperature and flow sensors, and obtains the measured value Z after A / D conversion. k The algorithm predicts the state X based on the previous time step. k|k-1 According to formula K k =P k|k-1 H T HP k|k-1 H T +R) -1 Calculate the Kalman gain K k This updates the system status X. k|k =X k|k-1 +K k (Z k -HX k|k-1 And simultaneously update the state estimation covariance matrix P. k|k =(IK k H)P k|k-1 In actual operation, through data processing over 100 consecutive sampling cycles, the standard deviation of reheat steam temperature measurement data decreased from 0.8℃ to 0.3℃, and the fluctuation coefficient of flow rate data decreased from 5% to 2%, effectively improving the reliability and stability of the data and providing a more accurate data foundation for subsequent control decisions.

[0042] When implementing the genetic algorithm optimization program, the core optimization objectives are to improve the thermal efficiency of the generator set and reduce steam parameter fluctuations. This involves optimizing the PID control parameters (proportional coefficient K) in the DCS control system. p Integration time T i Differential time T d Global optimization is performed. The population size is set to 50, and each individual corresponds to a set of PID parameter combinations to simulate individuals in biological evolution; the crossover probability is set to 0.8 to promote gene exchange between individuals and accelerate the propagation of excellent solutions; the mutation probability is set to 0.05 to maintain population diversity and avoid the algorithm getting trapped in local optima.

[0043] Define fitness function , where y i For the target values ​​of parameters such as steam temperature and pressure, f(x) i ) represents the predicted value under the current PID parameters, where ∈ is set to 10. -6 To prevent the denominator from being zero.

[0044] Taking the steam turbine governing system of a 1000 MW coal-fired unit as an example, before optimization, when the unit load is rapidly increased from 600 MW to 800 MW, the steam turbine speed fluctuation range is ±40 r / min, and the main steam pressure fluctuation is ±0.6 MPa, which seriously affects the stability of the unit. After the algorithm is started, 100 iterations are calculated through selection, crossover, mutation and other operations. At the 30th iteration, a set of relatively optimal parameter combination K p = 2.8, T i = 100 s, T d = 35 s, at this time the steam turbine speed fluctuation range is reduced to ±25 r / min, and the main steam pressure fluctuation is reduced to ±0.4 MPa. With the progress of iteration, the optimal parameter combination is finally determined: K p is adjusted from the initial 2.3 to 3.1, T i is shortened from 120 s to 85 s, and T d is extended from 30 s to 42 s. After optimization, under the same load change condition, the steam turbine speed fluctuation is controlled within ±15 r / min, the main steam pressure fluctuation range is reduced to ±0.2 MPa, and the unit thermal efficiency is increased from 43.5% to 45.8%, which significantly optimizes the control performance and operating economy of the system.

[0045] After the preliminary optimization of the above algorithm is completed, field debugging and optimization are still needed. The technical personnel monitor the operating parameters and control effect of the generator set in real time through the operation interface of the DCS system. In different load intervals (such as 30%-50%, 50%-70%, 70%-100%), test and collect actual operating data and optimized theoretical data for comparative analysis. If it is found that the control effect under certain conditions does not meet the expectations, for example, there is a lag in steam temperature regulation at low load, the parameter of Kalman filter can be adjusted appropriately, the value of process noise covariance matrix Q is increased to enhance the response ability of the algorithm to the dynamic changes of the system; or the fitness function of genetic algorithm is fine-tuned, the weight of steam temperature stability at low load is increased, and parameter optimization is performed again. Through multiple rounds of field debugging and algorithm optimization, it is ensured that the DCS control system can realize efficient and accurate automatic control under various operating conditions.

[0046] Finally, it should be noted that the present application is not limited to the above embodiments, but can have many variations. All variations that can be directly derived or conceived by those of ordinary skill in the art from the disclosure of the present application should be considered within the scope of the present application.

Claims

1. A system for improving the automatic control level of generator sets, comprising a DCS control system, characterized in that, The DCS control system is also equipped with a module for connecting thermal control measurement points and control equipment, a DCS upgrade and expansion module, a DCS control system optimization module, and a control logic improvement and optimization module. The thermal control measurement point and control equipment module includes temperature measurement points, pressure measurement points, flow measurement points, as well as platinum resistance temperature sensors and temperature transmitters corresponding to temperature measurement points; piezoresistive pressure sensors and pressure transmitters corresponding to pressure measurement points; and LDG electromagnetic flow meters and flow transmitters corresponding to flow measurement points, which are used to improve the flexibility and reliability of automatic control. The DCS upgrade and expansion module includes 8 analog input / output cards, 12 digital input / output cards, 2 Ethernet communication modules, 3 communication modules, and a control cabinet, which expand the capacity of the control system. The DCS control system optimization module, for the aforementioned thermal control measurement points and control equipment module, adopts a formula-based approach. X k|k =X k|k-1 +K k (Z k -H k X k|k-1 Kalman filtering data fusion technology, using fitness function A genetic algorithm optimization strategy is used to optimize the unit's DCS control system; among which, in the Kalman filter formula, X k|k X is the optimal estimate at time k. k|k-1 Let K be the predicted value at time k. k For Kalman gain, Z k H is the measurement value at time k. k For measurement matrix; in the fitness function of the genetic algorithm, E is the objective function value, w i e is the weighting coefficient. i For error; The control logic improvement and optimization module improves and optimizes the DCS control system logic of the unit by establishing a Petri net logic model and conducting MATLAB / Simulink simulation tests, so as to achieve changes in control logic and mode.

2. The system for improving the automatic control level of a generator set according to claim 1, characterized in that, The measurement accuracy of the temperature measuring point is ±0.1℃, the measurement accuracy of the pressure measuring point is ±0.25%FS, and the measurement accuracy of the flow measuring point is ±0.5%.

3. The system for improving the automatic control level of a generator set according to claim 1, characterized in that, Each analog input / output card has 16 channels, while a single digital input / output card supports 32 digital channels.

4. The system for improving the automatic control level of a generator set according to claim 1, characterized in that, The Ethernet communication module supports 1000Mbps high-speed data transmission, and the Profibus communication module supports a communication rate of 12Mbps.

5. The system for improving the automatic control level of a generator set according to claim 1, characterized in that, The control cabinet is equipped with a Delta DVP-ES2 power distribution unit and a Huawei S5720-36C-EI-24S-AC network switch.

6. A system for improving the automatic control level of a generator set; a method for improving the automatic control level of a generator set, characterized in that... Includes the following steps: Step 1: Install the following components: PT100 platinum resistance temperature sensor, SBWR temperature transmitter, CYB130 piezoresistive pressure sensor, 3051 pressure transmitter, LDG electromagnetic flowmeter, FX-100 flow transmitter, and their corresponding temperature, pressure, and flow measurement points to improve the flexibility and reliability of automatic control. Step 2: Expand the control system by adding 8 analog input / output cards of Xinhua Control XDPS-400e, 12 digital input / output cards of Xinhua Control XDPS-400e, 2 Ethernet communication modules of MOXA EDS-516A, and 3 Profibus communication modules of Siemens 6ES7972-0BA52-0XA0, and add 2 control cabinets of Rittal TS8837.

320. Step 3: For the newly added temperature, pressure, and flow measurement points, and their corresponding sensors and transmitters, adopt a method based on the public X... k|k =X k|k-1 +K k (Z k -H k X k|k-1 Kalman filtering data fusion technology, using fitness function The genetic algorithm optimization strategy is used to optimize the DCS control system of the unit. Step 4: In response to changes in control logic and methods, improve and optimize the DCS control system logic of the unit by establishing a Petri net logic model and conducting MATLAB / Simulink simulation tests.

7. A method for improving the automatic control level of a generator set according to claim 6, characterized in that, In step one, the installation locations of temperature measuring points include the boiler superheater headers at each stage and the turbine cylinder block; the installation locations of pressure measuring points include the main steam pipeline and the extraction steam pipeline; and the installation locations of flow measuring points include the feedwater pipeline and the condensate pipeline.

8. A method for improving the automatic control level of a generator set according to claim 6 or 7, characterized in that, In step two, when installing analog input / output cards, the output signals of temperature sensors, pressure sensors, and flow transmitters are connected to the corresponding analog input channels according to the terminal block definitions, using a three-wire or four-wire wiring method. When installing digital input / output cards, the start / stop signals and status feedback signals of the equipment are connected to the digital input channels, and the control command signals are led out from the digital output channels to the actuators.

9. A method for improving the automatic control level of a generator set according to claim 6 or 7, characterized in that, In step three, when using Kalman filter data fusion technology, the Kalman filter parameters are first initialized according to the system state equation and measurement equation. This includes setting the state estimation covariance matrix P0 as the identity matrix, setting the process noise covariance matrix Q to 0.01I based on the system dynamic characteristics, and setting the measurement noise covariance matrix R to 0.1I based on the sensor accuracy, where I is the identity matrix. When using the genetic algorithm optimization strategy, the population size is set to 50, the crossover probability to 0.8, the mutation probability to 0.05, and the maximum number of iterations to 100.

10. The method for improving the automatic control level of a generator set according to claim 6, characterized in that, In step four, when establishing the Petri net logic model, the system state is defined by the library, the event trigger is defined by the transition, and the relationship between the state and the event is defined by the arc. When conducting MATLAB / Simulink simulation tests, a simulation system is built that includes boiler model, turbine model, generator model and various auxiliary machine models. Various operating conditions are set for testing, such as the unit increasing from 50% load to 80% load and grid frequency fluctuation of ±0.5Hz.

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