Coal-fired unit self-starting intelligent scheduling and control system based on ICS platform

Abstract

The invention relates to the technical field of coal-fired unit control systems, and discloses a coal-fired unit self-starting intelligent scheduling and control system based on an ICS platform, which comprises a multi-source heterogeneous ICS control platform and an intelligent APS system, and is characterized in that the intelligent APS system is divided into a top layer module, a middle layer function group and a bottom layer subsystem; the top layer module comprises a comprehensive fusion intelligent inspection module, an intelligent early warning module and an intelligent power plant advanced application module, the middle layer function group is used for full-period automatic control and closed-loop control, and the bottom layer subsystem comprises an MCS, a DEH, an SCS and an ECS and is in signal connection with the middle layer function group. According to the coal-fired unit self-starting intelligent scheduling and control system based on the ICS platform, automatic optimization of the starting step sequence is achieved through the top layer module of the intelligent APS system, the optimal step sequence is selected, the time and errors of manual step sequence selection are reduced, the unit starting process is smoother and more efficient, and the starting time is shortened.

Description

Technical Field

[0001] This invention relates to the field of coal-fired power unit control system technology, specifically to a coal-fired power unit self-starting intelligent scheduling and control system based on the ICS platform. Background Technology

[0002] In the power industry, coal-fired power units are a crucial component of power supply, and the stability, efficiency, and intelligence of their startup process directly impact the safe operation and economic benefits of the power system. Traditional startup methods for coal-fired power units rely primarily on manual operation and experience-based judgment, which has numerous drawbacks.

[0003] From the perspective of startup efficiency, manual operation requires a series of steps, including equipment checks and parameter adjustments. The coordination between these steps is often not smooth, resulting in a longer startup time. In situations of tight power demand, the inability to quickly respond to load demands may affect the stability of the power supply.

[0004] Traditional control systems often employ a single control strategy, such as PID control, which is ill-suited to the complex and variable operating conditions during the startup of coal-fired power units. During startup, the unit's parameters undergo significant changes, and the adjustment accuracy and response speed of traditional control strategies are insufficient to ensure that the unit's parameters remain stable within a reasonable range.

[0005] Therefore, it is necessary to invent an intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a coal-fired unit self-starting intelligent scheduling and control system based on the ICS platform, including a multi-source heterogeneous ICS control platform and an intelligent APS system, wherein the intelligent APS system is divided into a top-level module, a middle-level functional group and a bottom-level subsystem;

[0008] The top-level module includes a fully integrated intelligent inspection module, an intelligent early warning module, and a smart power plant advanced application module.

[0009] The mid-level functional groups are used for full-cycle automatic control and closed-loop control;

[0010] The underlying subsystem includes MCS, DEH, SCS, and ECS, and is signal-connected to the middle-layer functional group.

[0011] Preferably, the intelligent inspection module is used to monitor the various equipment and operating parameters of the coal-fired unit in real time. It uses a parameter fluctuation coefficient calculation formula to determine the equipment operating status, the formula being:

[0012]

[0013] Where K is the parameter fluctuation coefficient, σ is the standard deviation of the parameter, and μ is the homogeneity of the parameter. When K exceeds the set threshold, it indicates that the parameter fluctuates greatly and the equipment is abnormal.

[0014] Preferably, the intelligent early warning module includes an early warning model library and an early warning processing unit;

[0015] The early warning model library is used for early warning analysis of different equipment fault types and abnormal operating conditions;

[0016] The early warning processing unit receives abnormal signals and related parameter information from the intelligent inspection module, calls the corresponding early warning model in the early warning model library for analysis, determines the type, severity, and possible development trend of the fault, and generates early warning information. The formula for determining the early warning level is as follows:

[0017] L = max(l1, l2, ..., l) m )

[0018] Where L represents the final warning level, l j Let be the warning level corresponding to the j-th warning indicator, and m be the number of warning indicators.

[0019] Preferably, the top-level module receives multi-threaded information from the intelligent inspection module, the intelligent early warning module, and other advanced smart power plant application modules, including real-time monitoring data, abnormal signals, early warning information, and control commands.

[0020] Preferably, the full-cycle automatic control function of the middle-level functional group specifically includes automatic control of the pre-startup preparation stage, the start-up stage, the stable operation stage, and the shutdown stage.

[0021] Preferably, the middle-level functional group includes a feedback acquisition module, a deviation calculation module, and a control adjustment module. The feedback acquisition module collects the output parameters of the lower-level subsystem and the actual operating parameters of the unit in real time. The deviation calculation module compares the collected actual operating parameters with the target parameters set by the top-level module to calculate the deviation value. The control adjustment module generates control commands based on the magnitude and trend of the deviation value, combined with advanced control strategies, and transmits them to the lower-level subsystem to adjust the operating state of the lower-level subsystem so that the actual operating parameters are close to or reach the target parameters, forming a closed-loop control loop.

[0022] The formula for calculating the control adjustment amount is:

[0023]

[0024] Where ΔU is the control adjustment quantity, k p k is the proportionality coefficient. i k is the integral coefficient. d ΔX is the differential coefficient, and ΔX is the deviation value.

[0025] Preferably, the interconnection between the underlying subsystem and the middle-layer functional group is achieved through a dedicated communication interface and protocol.

[0026] Preferably, the fault self-decision-making function of the intelligent APS operation system is implemented as follows:

[0027] When the intelligent early warning module issues an early warning message or the underlying subsystem reports a fault signal, the information interaction center of the top-level module transmits the relevant fault information to the fault decision unit.

[0028] The fault decision-making unit calls upon the stored fault handling knowledge base;

[0029] Based on the type and severity of the fault and the current operating status of the unit, the best handling solution is matched from the fault handling knowledge base;

[0030] The processing plan is converted into control commands and transmitted to the middle-level functional group, which then controls the lower-level subsystems to perform the corresponding operations.

[0031] During the troubleshooting process, the unit's operating status and the effectiveness of the troubleshooting are monitored in real time. If the troubleshooting effect does not meet expectations, the troubleshooting knowledge base is called back and the troubleshooting plan is adjusted until the fault is resolved or controlled within an acceptable range.

[0032] Preferably, the multi-source heterogeneous ICS control platform adopts an advanced control strategy.

[0033] Compared with existing technologies, this invention provides an intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform, which has the following advantages:

[0034] 1. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform automatically optimizes the start-up sequence through the top-level module of the intelligent APS system, selects the optimal sequence, reduces the time and error of manual selection of the sequence, makes the start-up process of the unit smoother and more efficient, and shortens the start-up time.

[0035] 2. The intelligent scheduling and control system for coal-fired power units based on the ICS platform, combined with the full-cycle automatic control function of the middle-level functional groups, controls the operation of each underlying subsystem according to preset logic and timing, ensuring that the unit load and parameters gradually and stably increase to the target value, improving the start-up quality and avoiding problems such as excessive parameter fluctuations caused by improper manual operation.

[0036] 3. The self-starting intelligent dispatch and control system for coal-fired units based on the ICS platform collects various parameters of the unit in real time through the intelligent inspection module, promptly detects equipment abnormalities, and issues warnings and activates corresponding handling plans through the intelligent early warning module. This enables early detection and timely handling of equipment failures and operational anomalies, reduces the risk of fault escalation, and improves the reliability of power supply.

[0037] 4. The intelligent scheduling and control system for coal-fired power units based on the ICS platform realizes full-cycle automatic control from pre-start preparation to shutdown. All operations are completed automatically by the system, reducing the need for manual intervention. This not only reduces the risk caused by human error, but also saves a lot of labor costs and improves efficiency.

[0038] 5. The self-starting intelligent scheduling and control system for coal-fired units based on the ICS platform can adjust the scheme in real time according to the processing effect, which improves the efficiency and accuracy of fault handling. Compared with the traditional manual fault handling method, it can eliminate faults or reduce the impact of faults in a shorter time, ensuring the safe and stable operation of the unit. Detailed Implementation

[0039] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0041] This invention provides a technical solution: a coal-fired unit self-starting intelligent scheduling and control system based on the ICS platform, including a multi-source heterogeneous ICS control platform and an intelligent APS system. The intelligent APS system is divided into a top-level module, a middle-level functional group and a bottom-level subsystem.

[0042] The top-level module includes a fully integrated intelligent inspection module, an intelligent early warning module, and an advanced smart power plant application module;

[0043] The middle-level functional groups are used for full-cycle automatic control and closed-loop control;

[0044] The underlying subsystems include MCS, DEH, SCS, and ECS, and are connected to the middle-level functional groups via signals.

[0045] The system calculates and optimizes key parameters using the following formulas to ensure accurate system operation:

[0046] The formula for evaluating the boot sequence optimization is:

[0047]

[0048] Where S is the overall score for the boot sequence, and w i p represents the weight of the i-th evaluation indicator. i Let be the score of the i-th evaluation indicator, and n be the number of evaluation indicators. This formula is used to comprehensively score different boot sequences, and the sequence with the highest score is selected as the optimal boot sequence.

[0049] The formula for calculating equipment operating status deviation is:

[0050] ΔX=X 实际 -X 目标

[0051] Where ΔX is the deviation value of the equipment operating status parameter, X 实际 X represents the actual operating status parameter value of the equipment. 目标 The target state parameter value is set for the equipment. This formula is used to calculate the deviation between the actual operating parameters of the equipment and the target parameters, providing a basis for closed-loop control.

[0052] The formula for assessing the impact of a fault is:

[0053] I = α × s + β × t

[0054] Where I represents the degree of impact of the fault, α and β are weighting coefficients, s is the impact of the fault on the unit's operational stability, and t is the potential downtime caused by the fault. This formula is used to assess the degree of impact of the fault in order to take appropriate measures.

[0055] Furthermore, the intelligent inspection module is used to monitor various equipment and operating parameters of the coal-fired unit in real time. It uses a parameter fluctuation coefficient calculation formula to determine the equipment operating status. The formula is as follows:

[0056]

[0057] Where K is the parameter fluctuation coefficient, σ is the standard deviation of the parameter, and μ is the homogeneity of the parameter. When K exceeds the set threshold, it indicates that the parameter fluctuates greatly and the equipment is abnormal.

[0058] Furthermore, the intelligent early warning module includes an early warning model library and an early warning processing unit;

[0059] The early warning model library is used for early warning analysis of different equipment fault types and abnormal operating conditions;

[0060] The early warning processing unit receives abnormal signals and related parameter information from the intelligent inspection module, calls the corresponding early warning model in the early warning model library for analysis, determines the type, severity, and possible development trend of the fault, and generates early warning information. The formula for determining the early warning level is as follows:

[0061] L = max(l1, l2, ..., l) m )

[0062] Where L represents the final warning level, l j Let be the warning level corresponding to the j-th warning indicator, and m be the number of warning indicators.

[0063] Furthermore, the top-level module receives multi-threaded information from the intelligent inspection module, intelligent early warning module, and other advanced smart power plant application modules, including real-time monitoring data, abnormal signals, early warning information, and control commands. It categorizes, filters, and prioritizes the received information, then transmits the processed information to the middle-level functional groups according to preset rules and protocols. Simultaneously, it receives operational status information and control result information from the middle-level functional groups, establishing an information interaction log to record the transmission time, content, source, and destination of all information for subsequent querying and analysis. Information priority is calculated using the following formula:

[0064] P = a × t + b × i

[0065] Where P is the information priority, a and b are weighting coefficients, t is the urgency value of the information, and i is the importance value of the information. The priority of information is calculated by this formula to ensure that important and urgent information is processed first.

[0066] Furthermore, the full-cycle automatic control function of the mid-level functional group specifically includes automatic control of the pre-start preparation stage, start-up stage, stable operation stage and shutdown stage.

[0067] During the pre-startup preparation phase, the status of each piece of equipment, such as the on / off status of valves and the operating status of pumps, is automatically detected to ensure that the equipment is in a ready-to-start state; the initialization settings of relevant parameters are automatically completed, such as setting the target parameters for startup and safety thresholds.

[0068] During the startup phase, based on the startup sequence transmitted by the top-level module, the system automatically optimizes the operation of each underlying subsystem according to the preset logic and timing, gradually increasing the unit's load and parameters until the startup target is achieved.

[0069] During the stable operation phase, the unit's operating parameters are monitored in real time, and the control parameters are automatically adjusted according to load changes and changes in external conditions to maintain the stable operation of the unit.

[0070] During the shutdown phase, the unit's load and parameters are gradually reduced according to the preset shutdown procedure, and all equipment is controlled to shut down in an orderly manner to ensure the safety and stability of the shutdown process.

[0071] Formula for calculating the load increase rate during unit startup:

[0072]

[0073] Where v is the load increase rate, P 目标 For the target load during the startup phase, P 初始 The initial load during the startup phase is given by the formula, and T is the planned startup time. The load increase rate is determined by this formula to ensure a smooth startup of the unit.

[0074] Furthermore, the mid-level functional group includes a feedback acquisition module, a deviation calculation module, and a control and regulation module. The feedback acquisition module collects the output parameters of the lower-level subsystem and the actual operating parameters of the unit in real time. The deviation calculation module compares the collected actual operating parameters with the target parameters set by the top-level module and calculates the deviation value. The control and regulation module generates control commands based on the magnitude and trend of the deviation value, combined with advanced control strategies, and transmits them to the lower-level subsystem to adjust the operating state of the lower-level subsystem so that the actual operating parameters are close to or reach the target parameters, forming a closed-loop control loop.

[0075] The formula for calculating the control adjustment amount is:

[0076]

[0077] Where ΔU is the control adjustment quantity, k p k is the proportionality coefficient. i k is the integral coefficient. d ΔX is the differential coefficient, and ΔX is the deviation value.

[0078] Furthermore, the interconnection between the lower-level subsystems and the middle-level functional groups is achieved through dedicated communication interfaces and protocols;

[0079] The MCS subsystem can receive control commands from the middle-level functional groups and adjust the analog quantities of the unit.

[0080] The DEH subsystem receives speed and load control commands from the intermediate functional group, adjusts the steam intake of the turbine to control speed and load, and feeds back the turbine's operating parameters, such as speed, power, and steam pressure, to the intermediate functional group.

[0081] The SCS subsystem receives sequential control commands from the middle-level functional group, performs start-stop control and interlock protection for auxiliary equipment of the unit such as valves, pumps, and fans, and feeds back the on / off status and abnormal operation signals of the equipment to the middle-level functional group.

[0082] The ECS subsystem receives control commands from the middle-level functional group to control the unit's electrical system, such as grid connection and disconnection of generators, and opening and closing of circuit breakers. At the same time, it feeds back the operating parameters of the electrical system, such as voltage, current, and frequency, to the middle-level functional group.

[0083] The communication quality assessment formula between each subsystem and the middle-level functional group is as follows:

[0084]

[0085] Where Q is the communication quality assessment value, and N 成功 N represents the number of data packets successfully transmitted. 总 Let D be the total number of data packets transmitted, and D be the average transmission delay. max This formula is used to evaluate communication quality to determine the maximum allowable transmission delay, ensuring the reliability and timeliness of data transmission.

[0086] Furthermore, the specific implementation process of the fault self-decision-making function of the intelligent APS operation system is as follows:

[0087] When the intelligent early warning module issues an early warning message or the underlying subsystem reports a fault signal, the information interaction center of the top-level module transmits the relevant fault information to the fault decision unit.

[0088] The fault decision unit calls the stored fault handling knowledge base, which contains handling solutions and decision rules for various fault types;

[0089] Based on the type and severity of the fault and the current operating status of the unit, the best handling solution is matched from the fault handling knowledge base;

[0090] The processing plan is converted into control commands and transmitted to the middle-level functional group. The middle-level functional group then controls the lower-level subsystems to perform corresponding operations to eliminate the fault or reduce its impact.

[0091] During the troubleshooting process, the unit's operating status and the effectiveness of the troubleshooting are monitored in real time. If the effectiveness of the troubleshooting does not meet expectations, the troubleshooting knowledge base is called back and the troubleshooting plan is adjusted until the fault is resolved or controlled within an acceptable range.

[0092] The formula for calculating the matching degree of fault handling solutions is:

[0093]

[0094] Where M represents the matching degree of the fault handling scheme, and c k δ represents the weight of the k-th matching metric. k Let q be the matching degree of the k-th matching indicator, and q be the number of matching indicators. The matching degree of different fault handling solutions is calculated using this formula, and the solution with the highest matching degree is selected.

[0095] Furthermore, the multi-source heterogeneous ICS control platform adopts advanced control strategies to replace the traditional PID control strategies, so as to ensure that the relevant actuators of analog control are in the right positions during the unit startup process.

[0096] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A coal-fired power unit self-starting intelligent dispatching and control system based on the ICS platform, comprising a multi-source heterogeneous ICS control platform and an intelligent APS system, characterized in that: The intelligent APS system is divided into a top-level module, a middle-level functional group, and a bottom-level subsystem. The top-level module includes a fully integrated intelligent inspection module, an intelligent early warning module, and a smart power plant advanced application module. The mid-level functional groups are used for full-cycle automatic control and closed-loop control; The underlying subsystem includes MCS, DEH, SCS, and ECS, and is signal-connected to the middle-layer functional group.

2. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The intelligent inspection module is used to monitor the various equipment and operating parameters of the coal-fired power unit in real time. It uses a parameter fluctuation coefficient calculation formula to determine the equipment operating status. The formula is as follows: Where K is the parameter fluctuation coefficient, σ is the standard deviation of the parameter, and μ is the homogeneity of the parameter. When K exceeds the set threshold, it indicates that the parameter fluctuates greatly and the equipment is abnormal.

3. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The intelligent early warning module includes an early warning model library and an early warning processing unit; The early warning model library is used for early warning analysis of different equipment fault types and abnormal operating conditions; The early warning processing unit receives abnormal signals and related parameter information from the intelligent inspection module, calls the corresponding early warning model in the early warning model library for analysis, determines the type, severity, and possible development trend of the fault, and generates early warning information. The formula for determining the early warning level is as follows: L=max(l1,l2,…,l m ) Where L represents the final warning level, l j Let be the warning level corresponding to the j-th warning indicator, and m be the number of warning indicators.

4. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The top-level module receives multi-threaded information from the intelligent inspection module, the intelligent early warning module, and other advanced smart power plant application modules, including real-time monitoring data, abnormal signals, early warning information, and control commands.

5. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The full-cycle automatic control function of the mid-level functional group specifically includes automatic control of the pre-start preparation stage, the start-up stage, the stable operation stage, and the shutdown stage.

6. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The mid-level functional group includes a feedback acquisition module, a deviation calculation module, and a control adjustment module. The feedback acquisition module collects the output parameters of the bottom subsystem and the actual operating parameters of the unit in real time. The deviation calculation module compares the collected actual operating parameters with the target parameters set by the top-level module to calculate the deviation value. The control adjustment module generates control commands based on the magnitude and trend of the deviation value, combined with advanced control strategies, and transmits them to the bottom subsystem to adjust the operating state of the bottom subsystem so that the actual operating parameters are close to or reach the target parameters, forming a closed-loop control loop. The formula for calculating the control adjustment amount is: Where ΔU is the control adjustment quantity, k p k is the proportionality coefficient. i k is the integral coefficient. d ΔX is the differential coefficient, and ΔX is the deviation value.

7. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The interconnection between the underlying subsystem and the middle-level functional group is achieved through dedicated communication interfaces and protocols.

8. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The specific implementation process of the fault self-decision-making function of the intelligent APS operation system is as follows: When the intelligent early warning module issues an early warning message or the underlying subsystem reports a fault signal, the information interaction center of the top-level module transmits the relevant fault information to the fault decision unit. The fault decision-making unit calls upon the stored fault handling knowledge base; Based on the type and severity of the fault and the current operating status of the unit, the best handling solution is matched from the fault handling knowledge base; The processing plan is converted into control commands and transmitted to the middle-level functional group, which then controls the lower-level subsystems to perform the corresponding operations. During the troubleshooting process, the unit's operating status and the effectiveness of the troubleshooting are monitored in real time. If the troubleshooting effect does not meet expectations, the troubleshooting knowledge base is called back and the troubleshooting plan is adjusted until the fault is resolved or controlled within an acceptable range.

9. The intelligent scheduling and control system for self-starting coal-fired power units based on the ICS platform according to claim 1, characterized in that: The multi-source heterogeneous ICS control platform adopts advanced control strategies.

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