Optimal control method and system for frequency modulation based on power opening degree nonlinear prediction

Abstract

The application belongs to the field of automatic control of hydroelectric generating set, and specifically discloses a primary frequency modulation optimization control method and system based on power opening degree nonlinear prediction, which comprises the following steps: converting a frequency deviation into a primary frequency modulation power change amount, adding the power change amount and a basic power set point of the generating set to obtain a dynamic power target; integrating a power deviation signal to obtain a power integral opening degree reference instruction; taking the dynamic power target and a water head of the generating set as inputs of a feedforward model to obtain a feedforward leading opening degree instruction; inputting an opening degree deviation value into a PID controller to generate a feedback opening degree correction instruction; and obtaining a guide vane opening degree given value based on the feedforward leading opening degree instruction and the feedback opening degree correction instruction, which is taken as a given signal of a guide vane position control loop. Through nonlinear prediction and a unique feedback structure, the application realizes high self-adaptation to the working condition change of the generating set, and significantly improves the rapidity, consistency and robustness of the primary frequency modulation response of the generating set.

Description

Technical Field

[0001] This application belongs to the field of automatic control of hydroelectric generator sets, and more specifically, relates to a primary frequency regulation optimization control method and system based on nonlinear prediction of power opening. Background Technology

[0002] The frequency regulation function of a hydroelectric generating unit is achieved by its core control device, the governor. Based on the power plant's operating strategy and the architecture of the upper-level monitoring system, the governor typically operates in two main modes: "power mode" and "opening mode." In opening mode, the governor receives and tracks an externally given guide vane opening command value. Simultaneously, its internal primary frequency regulation module operates independently. This module monitors the grid frequency in real time, and when a frequency deviation occurs, it automatically adds an adjustment amount to the external opening command value to achieve rapid support for the grid frequency.

[0003] However, in practical applications, this traditional primary frequency control method based on the guide vane opening pattern faces a significant physical bottleneck. The fundamental reason lies in the inherent nonlinearity of the turbine's hydraulic characteristics, which significantly shifts with changes in a key external condition—the operating head (i.e., the difference between the upstream water level and the downstream tailrace level). Specifically, there is a complex multivariate coupling relationship between the turbine's output power, guide vane opening, and operating head. This means that the same change in guide vane opening will result in entirely different power changes under different operating heads.

[0004] Traditional single-stage frequency control for guide vane opening typically employs a PID controller that takes the frequency deviation as input, with its output directly affecting the guide vane opening. The underlying logic of this control method assumes a fixed, linear relationship between the frequency deviation and the desired opening adjustment. However, due to the aforementioned head variations, this assumption is invalid over a wide operating range, leading to a series of serious technical problems:

[0005] Degraded performance: Parameters optimized for high head conditions may exhibit slow response and insufficient regulation at low head conditions, failing to meet the frequency regulation requirements of the power grid; conversely, parameters optimized for low head conditions may be overly sensitive at high head conditions, leading to overshoot or even oscillation, which may endanger the stability of the unit and the power grid.

[0006] To cope with changes in water head, existing technologies often employ methods such as "parameter segmentation" or "gain scheduling," which involves pre-setting multiple sets of PID parameters and switching them according to the water head range. This approach increases the complexity of debugging, and the instantaneous switching of parameters may cause abrupt changes in the control variable, introducing unnecessary disturbances.

[0007] Therefore, there is an urgent need for a completely new control method that can overcome the influence of the nonlinear characteristics of the turbine changing with the operating conditions within the framework of the opening mode, and achieve a truly adaptive primary frequency regulation control. Summary of the Invention

[0008] To address the shortcomings of existing technologies, the purpose of this application is to provide a primary frequency regulation optimization control method and system based on nonlinear prediction of power opening, aiming to solve the problem that traditional primary frequency regulation control methods based on opening mode usually use PID controllers with frequency deviation as input, whose output directly affects the guide vane opening. Due to the neglect of the influence of water head changes, the frequency regulation performance of the power grid is poor.

[0009] The first aspect of this application relates to a primary frequency modulation optimization control method based on nonlinear prediction of power opening, specifically including the following steps:

[0010] Step S1: Convert the frequency deviation between the grid frequency and the reference frequency into the primary frequency regulation power change, add the power change to the unit's basic power setpoint, and obtain the dynamic power target;

[0011] Step S2: Integrate the power deviation signal between the dynamic power target in step S1 and the feedback signal of the actual output power of the unit to obtain the power integral opening reference command.

[0012] Step S3: Using the dynamic power target and the unit head as inputs to the feedforward model, the feedforward dominant opening command is obtained through table lookup interpolation; wherein, the feedforward model is a model describing the relationship between turbine head, output power and guide vane opening.

[0013] Step S4: Input the opening deviation value between the feedback opening correction command and the power integral opening reference command to the PID controller to generate the feedback opening correction command;

[0014] Step S5: Add the feedforward main opening command and the feedback opening correction command to obtain the guide vane opening setpoint value, which is used as the setpoint signal for the guide vane position control loop inside the governor.

[0015] In some implementations, the feedforward model is obtained as follows:

[0016] Based on the comprehensive characteristic curve of the turbine model, a series of data points containing information on head, power and opening degree are extracted from the two-dimensional curve graph.

[0017] The extracted data points are organized and interpolated to generate regular grid data;

[0018] The regular grid data is plotted as a 3D surface to complete the construction of the feedforward model.

[0019] In some implementations, step S4 specifically includes the following steps:

[0020] Step S4.1: Subtract the feedback opening correction command from the power integral opening reference command to obtain the opening deviation value;

[0021] Step S4.2: After passing through the dead zone and limiting circuit, the opening deviation value is multiplied by the permanent slip coefficient, and then passed through the PID circuit to obtain the feedback opening correction command.

[0022] In some implementations, step S1 specifically includes the following steps:

[0023] Step S11: The frequency deviation is obtained by subtracting the grid frequency from the reference frequency. After the frequency deviation is processed by the dead zone and limiting circuit, it is multiplied by a gain coefficient that represents the unit's drooping characteristics to obtain the change in primary frequency regulation power.

[0024] Step S12: Add the change in primary frequency regulation power to the unit's base power setpoint to obtain the dynamic power target.

[0025] In some implementations, step S2 specifically includes the following steps:

[0026] Step S2.1: Subtract the dynamic power target from the actual output power feedback signal of the unit to obtain the power deviation signal;

[0027] Step S2.2: After the power deviation signal passes through the dead zone, it is multiplied by an integral gain coefficient and then passed through the integral stage to generate a power integral opening reference command.

[0028] The second aspect of this application relates to a primary frequency modulation optimization control system based on nonlinear prediction of power opening, comprising: a dynamic power target acquisition module, an opening reference command acquisition module, a dominant opening command acquisition module, an opening correction command acquisition module, and an opening setpoint acquisition module;

[0029] The dynamic power target acquisition module is used to convert the frequency deviation between the grid frequency and the reference frequency into the primary frequency regulation power change, and add the power change to the unit's basic power setpoint to obtain the dynamic power target;

[0030] The opening reference command acquisition module is used to integrate the power deviation signal between the feedback signal of the dynamic power target and the actual output power of the unit to obtain the power integral opening reference command;

[0031] The dominant opening command acquisition module is used to take the dynamic power target and the unit head as inputs to the feedforward model, and obtain the feedforward dominant opening command through table lookup interpolation; wherein, the feedforward model is a model describing the relationship between turbine head, output power and guide vane opening;

[0032] The opening correction command acquisition module is used to input the opening deviation value between the feedback opening correction command and the power integral opening reference command to the PID controller to generate the feedback opening correction command;

[0033] The opening setpoint acquisition module is used to add the feedforward main opening command and the feedback opening correction command to obtain the guide vane opening setpoint, which serves as the given signal for the guide vane position control loop inside the governor.

[0034] In some implementations, the dominant opening instruction acquisition module includes a feedforward model construction unit, which includes a data extraction subunit and a 3D visualization processing subunit.

[0035] The data extraction subunit is used to obtain a series of data points containing head, power and opening information from the two-dimensional curve graph based on the comprehensive characteristic curve of the turbine model.

[0036] The 3D visualization processing subunit is used to organize and interpolate the extracted data points to generate regular grid data; the regular grid data is then plotted into a 3D surface map to complete the construction of the feedforward model.

[0037] In some implementations, the opening correction instruction acquisition module includes: a subtractor and a PID controller unit;

[0038] The subtractor is used to subtract the feedback opening correction command from the power integral opening reference command to obtain the opening deviation value;

[0039] The PID controller unit is used to multiply the opening deviation value by the permanent slip coefficient after passing through the dead zone and limiting stage, and then obtain the feedback opening correction command through the PID stage.

[0040] In some implementations, the dynamic power target acquisition module includes a power change calculation unit and an adder;

[0041] The power change calculation unit is used to obtain the frequency deviation by subtracting the grid frequency from the reference frequency. After the frequency deviation is processed by the dead zone and limiting circuit, it is multiplied by a gain coefficient that represents the unit's drooping characteristics to obtain the primary frequency regulation power change.

[0042] The adder is used to add the change in primary frequency regulation power to the unit's base power setpoint to obtain the dynamic power target.

[0043] In some implementations, the opening reference command acquisition module includes: a power deviation calculation unit and an opening reference command calculation unit;

[0044] The power deviation calculation unit is used to calculate the difference between the dynamic power target and the actual output power feedback signal of the unit to obtain the power deviation signal.

[0045] The reference command calculation unit is used to multiply the power deviation signal by an integral gain coefficient after passing through the dead zone, and then pass it through the integration stage to generate a power integral opening reference command.

[0046] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art:

[0047] This application provides a primary frequency regulation optimization control method and system based on nonlinear prediction of power opening. The dominant opening command acquisition module undertakes the nonlinear scheduling task related to water head, fundamentally solving the problem of control performance varying with water head. This frees the feedback PID control unit from complex nonlinear compensation tasks, and its parameters are no longer sensitive to water head changes. Since the role of PID control is weakened to fine-tuning, its parameters can be set within a small, insensitive range, eliminating the need for segmented tuning based on water head. This greatly simplifies unit commissioning and maintenance, and improves system reliability.

[0048] This application provides a primary frequency regulation optimization control method and system based on nonlinear prediction of power opening degree. In the feedforward control, a predictive baseline value close to the final adjustment value is provided by the three-dimensional characteristic prediction curve related to power, head, and opening degree, ensuring rapid response. At the same time, PID feedback commands correct the dynamic process in real time, ensuring the smoothness and accuracy of the regulation process. This application clearly divides the control task into two parts: "feedforward prediction-led" and "feedback correction," with clear functional division. The feedforward is responsible for static adaptability, and the feedback is responsible for dynamic stability. The structure is clear, easy to understand, and easy to implement. Attached Figure Description

[0049] Figure 1 This is a flowchart of a primary frequency modulation optimization control method based on nonlinear prediction of power opening provided in an embodiment of this application.

[0050] Figure 2 It is a three-dimensional characteristic surface of the turbine head, power and opening degree provided in the embodiments of this application.

[0051] Figure 3 This is a block diagram of primary frequency modulation optimization control based on nonlinear prediction of power opening provided in the embodiments of this application.

[0052] Figure 4(a) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 60% rated power and rated head with a -0.1Hz disturbance.

[0053] Figure 4(b) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 60% rated power and rated head with a +0.1Hz disturbance.

[0054] Figure 5(a) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 60% rated power and 70m low head with a -0.1Hz disturbance.

[0055] Figure 5(b) shows the simulation adaptability verification of the traditional opening mode and the power opening-based nonlinear predictive control mode under the condition of 60% rated power and 70m low head with a +0.1Hz disturbance.

[0056] Figure 6(a) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 60% rated power and 100m high head with a -0.1Hz disturbance.

[0057] Figure 6(b) shows the simulation adaptability verification of the traditional opening mode and the power opening-based nonlinear predictive control mode under the condition of 60% rated power and 100m high head with a +0.1Hz disturbance.

[0058] Figure 7(a) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 30% rated power and rated head with a -0.1Hz disturbance.

[0059] Figure 7(b) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 30% rated power and rated head with a +0.1Hz disturbance.

[0060] Figure 8(a) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 80% rated power and rated head with a -0.1Hz disturbance.

[0061] Figure 8(b) shows the simulation adaptability verification of the traditional opening mode and the power opening nonlinear predictive control mode under the condition of 80% rated power and rated head with a +0.1Hz disturbance. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0063] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. In this application, the symbol " / " indicates that the related objects are in an "or" relationship, for example, A / B means A or B.

[0064] In this application, the terms “first” and “second” are used to distinguish different objects, rather than to describe a specific order of objects.

[0065] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0066] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more.

[0067] The embodiments of this application are described below with reference to the accompanying drawings.

[0068] like Figure 1 As shown, this application provides a primary frequency modulation optimization control method based on nonlinear prediction of power opening, including the following steps:

[0069] Step S1: Calculate the dynamic power target: Monitor the grid frequency in real time and calculate its deviation from the reference frequency; according to the unit's preset droop coefficient, convert the frequency deviation into the power change in the primary frequency regulation response, and add the power change to the unit's basic power setpoint to form a dynamic power target;

[0070] Step S2: Generate opening reference command: Combine the dynamic power target obtained in step S1 with the feedback signal of the actual output power of the unit. The power deviation signal is obtained by subtraction. Then the power deviation signal The data is fed into an integrator for processing, generating a power integral opening reference command used to eliminate steady-state power errors. ;

[0071] Step S3: Generate feedforward dominant command: Based on the comprehensive characteristic curve of the turbine model, extract a series of data points containing head, power and opening information from the two-dimensional curve graph. Organize and interpolate the extracted data points to generate regular grid data, and then draw a three-dimensional surface graph. Use the dynamic power target obtained in step S1 and the real-time monitored unit head as input to the feedforward model. Through table lookup and interpolation, directly calculate the basic guide vane opening required to achieve the power target, which serves as the feedforward dominant opening command. This command undertakes the main regulation task.

[0072] Step S4: Generate feedback correction command: Take the opening deviation value as input and send it to a PID controller for processing to generate a feedback opening correction command for fine correction of the dynamic process.

[0073] Step S5: Synthesize the final control command: Algebraically superimpose the feedforward main opening command obtained in step S3 and the feedback opening correction command obtained in step S4 to form the final, comprehensive guide vane opening setpoint, which is then used as the setpoint signal for the guide vane position control loop inside the governor.

[0074] Example 1

[0075] This application provides a primary frequency modulation optimization control method based on power opening nonlinear prediction, specifically including the following steps:

[0076] Step S1, Formation of Dynamic Power Target: This step aims to generate a dynamically changing power target signal based on the real-time frequency deviation and the baseline power setting, which will serve as a reference for subsequent system control. Specifically, it includes the following steps:

[0077] Step S11: Calculation of primary frequency regulation power change: Obtain real-time grid frequency deviation signal After being processed by dead-time and limiting stages, the signal is multiplied by a gain coefficient 1 / 3, which represents the droop characteristics of the unit. The power change in the first frequency modulation response is obtained. ;

[0078] Step S12: Dynamic power target synthesis: The primary frequency modulation power change obtained in step S11 is used to synthesize the power target. With respect to the externally given unit base power setpoint signal The signals are superimposed in an adder to form a dynamic power target signal. ;Right now ;

[0079] Step S2, Generation of Power Integral Opening Reference Command: This step aims to generate an opening reference command to eliminate the steady-state power error of the system by integrating the power deviation. Specifically, it includes:

[0080] Step S21: Power Deviation Signal Formation: The dynamic power target signal formed in step S1 is used to generate the power deviation signal. Feedback signal of the actual output power of the unit obtained through the measurement process. The power deviation signal is obtained by subtracting from the subtractor. ;Right now .

[0081] Step S22: Integration Processing: Integrate the power deviation signal obtained in step S21. After passing through the dead zone, it is multiplied by an integral gain coefficient. The data is then fed into an integration stage for processing, ultimately generating a power integral opening reference command. This instruction ensures that the actual power accurately tracks the dynamic power target when the system reaches a steady state.

[0082] Step S3, Generation of Feedforward Dominant Opening Command: This step, as the core of this application, aims to proactively predict and generate feedforward commands that undertake the main regulation task based on dynamic power targets and real-time head. To overcome the effects of nonlinearity and changes in operating conditions of the water turbine, the following steps are specifically included:

[0083] Step S31: Model Input Acquisition: Obtain the dynamic power target signal formed in step S1. and real-time monitoring of unit operating head signals H , as input to the feedforward model;

[0084] Step S32: Feedforward lookup and interpolation: Using a pre-established table describing the turbine head ( H ), output power ( P ) and guide vane opening ( y Three-dimensional characteristic prediction curves of the static relationship between (e.g.) Figure 2 The "turbine head / power / opening degree relationship curve" shown is based on the input signal obtained in step S31. and H By looking up tables and performing interpolation calculations, the basic guide vane opening required to achieve the power target is directly calculated and used as the feedforward dominant opening command. ;

[0085] Step S4, Generation of Feedback Correction Opening Command: This step aims to generate a feedback command for fine correction and to provide system damping based on the dynamic process of the opening deviation. Specifically, it includes the following steps:

[0086] Step S41: PID controller main input formation: Obtain feedback opening correction command and power integral opening command. The difference is used as the input signal for the PID controller;

[0087] Step S42: Generation of feedback command: The input signal of the PID controller, after passing through the dead zone and limiting circuit, is multiplied by the permanent slip coefficient. After further processing by the PID controller, the feedback opening correction command can be obtained. ;

[0088] Step S5, Coordinated Synthesis of Final Control Commands: This step organically combines the commands generated by the various channels mentioned above to form the final control signal driving the actuator. Specifically, it includes the following steps:

[0089] Step S51: Command Overlay: Overlay the feedforward dominant opening command generated in step S3. and the feedback correction opening command generated in step S4 Algebraic summation is performed in the final adder;

[0090] Step S52: Final command output: The output of the adder is the final, integrated guide vane opening setpoint. ,Right now The instruction The position servo circuit is sent to the speed control system as its setpoint, thereby enabling adaptive, fast and precise primary frequency control of the hydropower unit.

[0091] To further verify the effectiveness and advancement of the control method provided in this application, a simulation analysis platform was built based on the nonlinear model of a 200MW mixed-flow hydropower unit in a power station. On the platform, comparative experiments were conducted on the primary frequency regulation performance of the traditional opening-mode control method and the method of this application under different head and power conditions. The primary frequency regulation performance indicators used in this experiment are described below.

[0092] Explanation of primary frequency modulation performance evaluation indicators:

[0093] To objectively and quantitatively evaluate the performance of different control methods, this simulation adopts the core performance indicators for primary frequency regulation as specified in the grid connection technology guidelines commonly used in the power industry, as follows:

[0094] Lag time (s): refers to the time elapsed from the moment the grid frequency deviation exceeds the set dead zone until the unit's active power begins to change effectively (i.e., move towards the theoretical regulation direction). This indicator mainly reflects the inherent delay in signal processing, command issuance, and the initial response of the hydraulic servo system and water system of the control system. It measures the immediacy of the unit's response and is a key factor in evaluating whether primary frequency regulation can start up quickly; the shorter the time, the better the performance.

[0095] Response time (s): This refers to the time elapsed from when the grid frequency deviation exceeds the dead zone until the unit's active power output reaches 90% of the theoretical target power change. This indicator measures the speed of the unit's response and is a key factor in evaluating the timeliness of primary frequency regulation. The shorter the time, the better the performance; generally, a response time of less than 15 seconds is considered acceptable.

[0096] Power deviation (%): Power deviation refers to the relative deviation between the response power and the theoretical target power. The calculation formula is: (response power - target power) / target power × 100%. This indicator measures the accuracy of the unit's response. According to technical guidelines, the power deviation is usually required to be within ±25%. Exceeding this range is considered unqualified.

[0097] Integral power ratio: This refers to the ratio of the integral power (power integrated over time) actually contributed by the unit to the integral power that should theoretically be contributed within a specific time period after a frequency disturbance occurs (60 seconds in this frequency regulation experiment). This indicator comprehensively measures the speed and accuracy of the unit's response and fully reflects the unit's total energy support capacity during the frequency regulation process. The closer the ratio is to 1, the more sufficient and ideal the frequency regulation contribution is.

[0098] The following simulation results will be used to analyze the frequency modulation performance of the two control methods under different operating conditions.

[0099] A primary frequency regulation test was conducted under the baseline operating condition of 60% rated power, rated head (84.4m), and a frequency difference of -0.1Hz. This operating point is typically located in the high-efficiency range of the turbine, representing a typical high-efficiency operating range for power plants. Optimizing the parameters of the two control modes under this baseline condition ensures the fairness of the comparison and provides a representative and universal performance benchmark for subsequent disturbance verification. Furthermore, since the PID control parameters have different effects on the primary frequency regulation dynamic response process under different control methods, to maintain the objectivity of the comparison, the baseline operating condition control parameters for each control method were tuned with a rise time of 7 seconds from the start of the frequency difference exceeding the primary frequency regulation dead zone to the active power reaching 90% steady-state value. The simulation conditions and results are as follows:

[0100] A. Verification of adaptability to head changes

[0101] (1) The unit operates at 60% rated power and rated head, and is subjected to The simulation results for a 0.1Hz grid frequency step disturbance are shown in Figure 4(a) and Figure 4(b).

[0102] (2) The unit operates at 60% rated power and 70m low head, and is subjected to The simulation results for a 0.1Hz grid frequency step disturbance are shown in Figure 5(a) and Figure 5(b).

[0103] (3) The unit operates at 60% rated power and 100m high head, and is subjected to The simulation results for a 0.1Hz grid frequency step disturbance are shown in Figure 6(a) and Figure 6(b).

[0104] Based on the data above, the simulation results clearly reveal:

[0105] Traditional frequency regulation performance in the traditional opening-delay mode heavily relies on the operating head. Its fixed PID parameters cannot adapt to changes in turbine characteristics, resulting in performance issues such as "severely insufficient response at low heads and severe overshoot at high heads" when the head deviates from the design point. This makes it almost impossible to meet grid connection requirements in power plants with a wide head range. The nonlinear predictive control mode based on power opening in this application, through its core feedforward control unit, can actively and in real-time adaptively compensate for control commands based on the real-time head. Regardless of whether the head is low, medium, or high, the accuracy and stability of its primary frequency regulation response remain at an extremely high level, with highly consistent performance indicators.

[0106] B. Power Level Adaptability Verification

[0107] (1) The unit operates at 30% rated power and rated head, and is subjected to The simulation results for a 0.1Hz grid frequency step disturbance are shown in Figures 7(a) and 7(b).

[0108] (2) The unit operates at 80% rated power and 84.4m rated head, and is subjected to The simulation results for a 0.1Hz grid frequency step disturbance are shown in Figures 8(a) and 8(b).

[0109] In summary, the simulation results clearly reveal that:

[0110] Low-power region: Traditional opening mode exhibits significant over-adjustment, with power deviations reaching as high as 40.36% and 43.28% under both frequency rise and fall disturbances. This indicates that the PID parameters optimized for medium load (60%) become too aggressive in the low-load region, leading to severe overshoot and a significant excess of integral charge. The nonlinear predictive control mode based on power opening in this application maintains accurate and stable response even under significantly reduced load conditions; the power deviation is strictly controlled within a very small range of -0.76% and -0.64%, and the integral charge ratio remains at an ideal level of 0.923 and 0.93.

[0111] In the high-power region, traditional operating modes exhibit inconsistent performance, exhibiting insufficient regulation capacity or slow response. Under frequency-increasing disturbances, the response power deviation remains within acceptable limits, but the unit power consistently fails to reach 90% of the target value, resulting in substandard response speed. Under frequency-decreasing disturbances, the response time is even longer, reaching 20.8 seconds, far exceeding conventional requirements. This invention, based on a nonlinear predictive control mode for power operation, demonstrates a significantly better response power deviation than the traditional mode. More importantly, while the response time increases due to proximity to the high-load region, it remains within a reasonable range and is significantly faster than the traditional mode, ensuring timely frequency regulation.

[0112] In summary, through the two adaptive verifications and comparative simulation tests covering key operational dimensions, it can be concluded that the primary frequency regulation performance of the traditional opening adjustment mode is heavily dependent on specific operating conditions. When the head and power levels deviate from their parameter setpoints, the performance will significantly decrease. In contrast, this application, based on the nonlinear prediction method of power opening, demonstrates highly consistent and excellent frequency regulation performance under all test conditions, thanks to its strong adaptive capability to changes in operating conditions. It essentially surpasses the existing traditional opening control mode and has high engineering application value.

[0113] Example 2

[0114] The second aspect of this application relates to a primary frequency modulation optimization control system based on nonlinear prediction of power opening, comprising: a dynamic power target acquisition module, an opening reference command acquisition module, a dominant opening command acquisition module, an opening correction command acquisition module, and an opening setpoint acquisition module;

[0115] The dynamic power target acquisition module is used to convert the frequency deviation between the grid frequency and the reference frequency into the primary frequency regulation power change, and add the power change to the unit's basic power setpoint to obtain the dynamic power target;

[0116] The opening reference command acquisition module is used to integrate the power deviation signal between the feedback signal of the dynamic power target and the actual output power of the unit to obtain the power integral opening reference command;

[0117] The dominant opening command acquisition module is used to take the dynamic power target and the unit head as inputs to the feedforward model, and obtain the feedforward dominant opening command through table lookup interpolation; wherein, the feedforward model is a model describing the relationship between turbine head, output power and guide vane opening;

[0118] The opening correction command acquisition module is used to input the opening deviation value between the feedback opening correction command and the power integral opening reference command to the PID controller to generate the feedback opening correction command;

[0119] The opening setpoint acquisition module is used to add the feedforward main opening command and the feedback opening correction command to obtain the guide vane opening setpoint, which serves as the given signal for the guide vane position control loop inside the governor.

[0120] In some implementations, the dominant opening instruction acquisition module includes a feedforward model construction unit, which includes a data extraction subunit and a 3D visualization processing subunit.

[0121] The data extraction subunit is used to obtain a series of data points containing head, power and opening information from the two-dimensional curve graph based on the comprehensive characteristic curve of the turbine model.

[0122] The 3D visualization processing subunit is used to organize and interpolate the extracted data points to generate regular grid data; the regular grid data is then plotted into a 3D surface map to complete the construction of the feedforward model.

[0123] In some implementations, the opening correction instruction acquisition module includes: a subtractor and a PID controller unit;

[0124] The subtractor is used to subtract the feedback opening correction command from the power integral opening reference command to obtain the opening deviation value;

[0125] The PID controller unit is used to multiply the opening deviation value by the permanent slip coefficient after passing through the dead zone and limiting stage, and then obtain the feedback opening correction command through the PID stage.

[0126] In some implementations, the dynamic power target acquisition module includes a power change calculation unit and an adder;

[0127] The power change calculation unit is used to obtain the frequency deviation by subtracting the grid frequency from the reference frequency. After the frequency deviation is processed by the dead zone and limiting circuit, it is multiplied by a gain coefficient that represents the unit's drooping characteristics to obtain the primary frequency regulation power change.

[0128] The adder is used to add the change in primary frequency regulation power to the unit's base power setpoint to obtain the dynamic power target.

[0129] In some implementations, the opening reference command acquisition module includes: a power deviation calculation unit and an opening reference command calculation unit;

[0130] The power deviation calculation unit is used to calculate the difference between the dynamic power target and the actual output power feedback signal of the unit to obtain the power deviation signal.

[0131] The reference command calculation unit is used to multiply the power deviation signal by an integral gain coefficient after passing through the dead zone, and then pass it through the integration stage to generate a power integral opening reference command.

[0132] In summary, this application has the following advantages compared to the prior art:

[0133] The feedforward control unit undertakes the nonlinear scheduling task related to water head, fundamentally solving the problem of control performance changing with water head. This frees the feedback PID control unit from the complex nonlinear compensation task, and its parameters are no longer sensitive to changes in water head.

[0134] Since the role of PID control is reduced to fine-tuning, its parameters can be set within a small, insensitive range, eliminating the need for segmented tuning based on head. This greatly simplifies system debugging and maintenance, and improves system reliability.

[0135] In feedforward control, predictive baseline values ​​close to the final adjustment amount are provided by the three-dimensional characteristic prediction curves related to power, head, and opening degree, ensuring rapid response; at the same time, PID feedback commands correct the dynamic process in real time, ensuring the smoothness and accuracy of the adjustment process.

[0136] This application clearly divides the control task into two parts: "feedforward prediction-led" and "feedback correction". The functional division is clear: the feedforward is responsible for static adaptability, and the feedback is responsible for dynamic stability. The structure is clear and easy to understand and implement.

[0137] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A primary frequency modulation optimization control method based on nonlinear prediction of power opening, characterized in that, Includes the following steps: Step S1: Convert the frequency deviation between the grid frequency and the reference frequency into the primary frequency regulation power change, add the power change to the unit's basic power setpoint, and obtain the dynamic power target; Step S2: Integrate the power deviation signal between the feedback signal of the dynamic power target and the actual output power of the unit to obtain the power integral opening reference command; Step S3: Using the dynamic power target and the unit head as inputs to the feedforward model, the feedforward dominant opening command is obtained through table lookup interpolation; wherein, the feedforward model is a model describing the relationship between turbine head, output power and guide vane opening. Step S4: Input the opening deviation value between the feedback opening correction command and the power integral opening reference command to the PID controller to generate the feedback opening correction command; Step S5: Add the feedforward main opening command and the feedback opening correction command to obtain the guide vane opening setpoint value, which is used as the setpoint signal for the guide vane position control loop inside the governor. Step S4 specifically includes the following steps: Step S4.1: Subtract the feedback opening correction command from the power integral opening reference command to obtain the opening deviation value; Step S4.2: After passing through the dead zone and limiting circuit, the opening deviation value is multiplied by the permanent slip coefficient, and then passed through the PID circuit to obtain the feedback opening correction command.

2. The primary frequency modulation optimization control method according to claim 1, characterized in that, The method for obtaining the feedforward model is as follows: Based on the comprehensive characteristic curve of the turbine model, a series of data points containing information on head, power and opening degree are extracted from the curve graph. The extracted data points are organized and interpolated to generate regular grid data; The regular grid data is plotted as a 3D surface to complete the construction of the feedforward model.

3. The primary frequency modulation optimization control method according to claim 1, characterized in that, Step S1 specifically includes the following steps: Step S11: The frequency deviation is obtained by subtracting the grid frequency from the reference frequency. After the frequency deviation is processed by the dead zone and limiting circuit, it is multiplied by a gain coefficient that represents the unit's drooping characteristics to obtain the change in primary frequency regulation power. Step S12: Add the change in primary frequency regulation power to the unit's base power setpoint to obtain the dynamic power target.

4. The primary frequency modulation optimization control method according to claim 1 or 3, characterized in that, Step S2 specifically includes the following steps: Step S2.1: Subtract the dynamic power target from the actual output power feedback signal of the unit to obtain the power deviation signal; Step S2.2: After the power deviation signal passes through the dead zone, it is multiplied by an integral gain coefficient and then passed through the integral stage to generate a power integral opening reference command.

5. A primary frequency modulation optimization control system based on nonlinear prediction of power opening, characterized in that, include: The module includes a dynamic power target acquisition module, an opening reference command acquisition module, a dominant opening command acquisition module, an opening correction command acquisition module, and an opening setpoint acquisition module. The dynamic power target acquisition module is used to convert the frequency deviation between the grid frequency and the reference frequency into the primary frequency regulation power change, and add the power change to the unit's basic power setpoint to obtain the dynamic power target; The opening reference command acquisition module is used to integrate the power deviation signal between the feedback signal of the dynamic power target and the actual output power of the unit to obtain the power integral opening reference command; The dominant opening command acquisition module is used to take the dynamic power target and the unit head as inputs to the feedforward model, and obtain the feedforward dominant opening command through table lookup interpolation; wherein, the feedforward model is a model describing the relationship between turbine head, output power and guide vane opening; The opening correction command acquisition module is used to input the opening deviation value between the feedback opening correction command and the power integral opening reference command to the PID controller to generate the feedback opening correction command; The opening setpoint acquisition module is used to add the feedforward main opening command and the feedback opening correction command to obtain the guide vane opening setpoint, which serves as the given signal for the guide vane position control loop inside the governor. The opening correction instruction acquisition module includes a subtractor and a PID controller unit. The subtractor is used to subtract the feedback opening correction command from the power integral opening reference command to obtain the opening deviation value; The PID controller unit is used to multiply the opening deviation value by the permanent slip coefficient after passing through the dead zone and limiting stage, and then obtain the feedback opening correction command through the PID stage.

6. The primary frequency modulation optimization control system according to claim 5, characterized in that, The dominant opening instruction acquisition module includes a feedforward model construction unit, which includes a data extraction subunit and a 3D visualization processing subunit. The data extraction subunit is used to obtain a series of data points containing head, power and opening information from the two-dimensional curve graph based on the comprehensive characteristic curve of the turbine model. The 3D visualization processing subunit is used to organize and interpolate the extracted data points to generate regular grid data; the regular grid data is then plotted into a 3D surface map to complete the construction of the feedforward model.

7. The primary frequency modulation optimization control system according to claim 5, characterized in that, The dynamic power target acquisition module includes a power change calculation unit and an adder; The power change calculation unit is used to obtain the frequency deviation by subtracting the grid frequency from the reference frequency. After the frequency deviation is processed by the dead zone and limiting circuit, it is multiplied by a gain coefficient that represents the unit's drooping characteristics to obtain the primary frequency regulation power change. The adder is used to add the change in primary frequency regulation power to the unit's base power setpoint to obtain the dynamic power target.

8. The primary frequency modulation optimization control system according to claim 5 or 7, characterized in that, The opening reference command acquisition module includes: a power deviation calculation unit and an opening reference command calculation unit; The power deviation calculation unit is used to calculate the difference between the dynamic power target and the actual output power feedback signal of the unit to obtain the power deviation signal. The reference command calculation unit is used to multiply the power deviation signal by an integral gain coefficient after passing through the dead zone, and then pass it through the integration stage to generate a power integral opening reference command.

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