Source-grid collaborative primary frequency modulation optimization method and system based on load demand

Abstract

The application relates to the technical field of power grid system frequency modulation, and specifically discloses a source-grid collaborative primary frequency modulation optimization method and system based on load demand, which comprises the following steps: acquiring key parameter information of a power grid and a unit; determining index parameter information for evaluating the frequency modulation performance of the unit according to the key parameter information; judging the index parameter information and quantifying the index parameter information based on a coding analysis method; determining weak index parameters of the unit in the frequency modulation process; determining the deviation value of the actual integral electric quantity from the theoretical integral electric quantity according to the weak index parameters; superimposing the deviation value to the frequency modulation compensation quantity of the unit; acquiring the frequency difference peak value in the closed-loop adjustment process and the frequency modulation duration; if the frequency difference peak value is smaller than a preset frequency difference threshold value and the frequency modulation duration is larger than a preset duration threshold value, compensating the small frequency difference response and the post-response after frequency modulation, and improving the frequency modulation response speed and performance of the unit and effectively improving the frequency stability of the power grid.

Description

Technical Field

[0001] This application relates to the field of frequency regulation technology for power grid systems, and in particular to a source-grid coordinated primary frequency regulation optimization method and system based on load demand. Background Technology

[0002] Traditional frequency regulation control schemes for thermal power units mainly rely on the adjustment relationship between the unit's speed signal and the electrical frequency signal. However, this frequency regulation control scheme usually suffers from frequency regulation response lag. That is, when the frequency changes, the unit cannot respond immediately, thus affecting the rapid stabilization of the grid frequency. Secondly, under small frequency difference conditions, the regulation effect of traditional frequency regulation methods is not obvious. Especially when the grid frequency fluctuation is small or changes slowly, the unit's response is insufficient, resulting in the inability to effectively maintain frequency stability.

[0003] One of the key technologies for grid-source frequency regulation is achieving coordination and optimization between the generation and load sides. The generation side participates in frequency regulation through power electronic devices and energy storage systems, while the load side regulates the load through intelligent control and demand response technologies. In practical applications, it has been found that integral power is one of the main factors affecting the frequency regulation performance of generating units. The key challenges include how to achieve grid-source frequency regulation and automatically analyze integral power indicators from numerous metrics, and how to adjust and address insufficient response during small frequency differences and insufficient response after long-term frequency regulation when integral power is the most prominent influencing factor. This would prevent over-regulation or reverse regulation, improve the speed and accuracy of frequency regulation response, and effectively enhance the frequency stability of the power grid. Summary of the Invention

[0004] This application aims to solve at least one of the problems existing in the prior art mentioned above. Based on this, it proposes a source-grid coordinated primary frequency regulation optimization method and system based on load demand. This method enables automated analysis of the frequency regulation performance of generating units, while simultaneously adjusting the frequency response capabilities of the generation and load ends, accurately adjusting the frequency regulation amplitude of the generating units, avoiding over-regulation or reverse regulation, and improving the speed and accuracy of frequency regulation response, thereby effectively enhancing the frequency stability of the power grid.

[0005] Firstly, this application provides a source-grid coordinated primary frequency regulation optimization method based on load demand, including:

[0006] Acquire key parameter information of the power grid and generating units, including power grid frequency data, power grid power, generator output power, and frequency regulation commands;

[0007] Based on the key parameter information, the index parameter information for evaluating the frequency regulation performance of the unit is determined. The index parameter information includes at least response lag time, integral power, and regulation reverse.

[0008] The indicator parameter information is judged and quantified based on the coding analysis method to determine the weak indicator parameters of the unit during frequency regulation.

[0009] Based on the weak index parameters, the deviation between the actual and theoretical integral power is determined by the integral power closed-loop optimization module on the CCS system side, and the deviation is added to the frequency regulation compensation of the unit to perform closed-loop adjustment of the unit's output power.

[0010] The peak frequency difference and the duration of frequency modulation are obtained during the closed-loop adjustment process. It is then determined whether the peak frequency difference is less than a preset frequency difference threshold and whether the duration of frequency modulation is greater than a preset duration threshold.

[0011] If so, the frequency modulation compensation module compensates for the small frequency difference response and the later response after frequency modulation.

[0012] In some examples, the determination of indicator parameters for evaluating the frequency regulation performance of the generating unit based on the key parameter information includes at least response lag time, integral power, and regulation reversal, including:

[0013] Based on the grid frequency data and the frequency regulation command, the response lag time is determined, wherein the response lag time is used to characterize the delay between the time when the generator set's output power begins to respond to the frequency regulation command and the time when the frequency regulation command is issued.

[0014] Based on the grid power and the generator set output power, determine the integral energy, and

[0015] The adjustment reverse direction is determined based on the frequency modulation command and the direction of power increase or decrease.

[0016] In some examples, the integral energy is determined based on the grid power and the generator output power, and the adjustment reverse is determined based on the frequency regulation command and the direction of power increase or decrease, including:

[0017] Points of electricity The calculation expression is:

[0018] ,

[0019] in, For real-time power, The initial power locked when the frequency modulation operation crosses the dead zone is given, and the integration start time is the frequency dead zone time. The product coefficient;

[0020] The expression for adjusting the inverse is:

[0021] ,

[0022] in, and These represent the increments of the frequency modulation command and the actual power change, respectively. If the two changes are in opposite directions, the adjustment is 1 for the reverse direction; otherwise, it is 0.

[0023] In some examples, the process of determining the indicator parameter information and quantifying it based on a coding analysis method to identify the weak indicator parameters of the unit during frequency regulation includes:

[0024] The response lag time, the integral energy, and the adjustment reversal are encoded, wherein each indicator in the indicator parameter information is encoded as 0 if it meets the standard and 1 if it does not. The integral energy is less than 50 and does not meet the standard, the response lag time is greater than 2 and does not meet the standard, and the adjustment reversal indicator does not meet the standard when the integral energy is negative.

[0025] The encoded value corresponding to the frequency modulation result is determined based on the binary method for the encoded index parameter information;

[0026] The response lag time, the integral charge, and the encoding value of the adjustment reversal are correlated to determine the numerical parameters used for quantization;

[0027] Based on the numerical parameters, the pass rates of each assessment indicator are statistically correlated, and the relationships between the assessment indicators are analyzed to determine the frequency regulation status information of the weak links in the frequency regulation process of the unit.

[0028] In some examples, the correlation between the response lag time, the integral charge, and the coded value of the adjustment reversal to determine the numerical parameters used for quantization includes:

[0029] The response lag time, the integral power, and the encoding value of the reversal of the adjustment are correlated in binary. There are five categories of numerical encoding results, namely [0,1,3,5,7]. The value 0 represents that all three indicators are qualified, the value 1 represents that the integral power is not qualified, the value 3 represents that the integral contribution rate is qualified but the response lag time indicator is not qualified, the value 5 represents that the frequency adjustment action is reversed but the response lag time indicator is qualified, and the value 7 represents that all three indicators are not qualified. The numerical parameters used for quantification are determined.

[0030] In some examples, the step of determining the deviation between the actual and theoretical integral power based on the weak index parameters using the integrated power closed-loop optimization module on the CCS system side, and then adding the deviation to the unit's frequency regulation compensation to perform closed-loop adjustment of the unit's output power, includes:

[0031] The expression for calculating the theoretical value of the integrated energy is:

[0032] ,

[0033] in, ,

[0034] In the formula, This is the difference between the actual frequency and the rated frequency. Where is the rated power of the unit, and K is the product coefficient.

[0035] In some examples, if so, compensation is performed based on the frequency modulation compensation module for the small frequency difference response and the later response after frequency modulation, including:

[0036] The formula for calculating the power increment of the small frequency difference response compensation is:

[0037] ,

[0038] in, To compensate for the power increment, This is the gain coefficient for small frequency difference compensation. This is the difference between the actual frequency and the rated frequency.

[0039] The formula for calculating the power increment of the later response compensation is:

[0040] ,

[0041] in, To compensate for the power increment in the later stage, This is the gain coefficient for later compensation. For frequency modulation duration, The time exceeding the preset frequency difference threshold within the frequency modulation duration.

[0042] Compared with the prior art, the technical solution provided in the first aspect of this application includes at least the following beneficial effects or advantages:

[0043] By collecting grid frequency data, grid power, generator output power, and frequency regulation command information at the generation end, the response lag time, integral power, and regulation reversal index for evaluating the unit's frequency regulation performance are calculated. These three indicators are quantified using a binary coding analysis method. Electronic equipment enables automated statistical analysis of the frequency of different coded values ​​and correlation analysis of indicator codes, identifying the integral power index affecting the unit's frequency regulation performance. By adding an integral power closed-loop optimization module at the load end, the unit's frequency regulation compensation is calculated and adjusted in real time, gradually reducing the deviation between actual and theoretical power.

[0044] The frequency regulation index compensation increment is composed of small frequency difference response compensation and later response compensation. The frequency regulation index compensation increment is added to the CCS system side and accumulated with the original unit frequency regulation compensation. At the same time, the compensation increment is superimposed on the frequency feedback signal to the DEH system side to improve the frequency regulation amplitude under small frequency difference and the response strength after long-term frequency regulation, thereby enhancing the overall frequency regulation performance of the unit. Through this compensation mechanism, the frequency regulation index compensation module ensures that the generator unit can operate effectively under both small frequency difference and long-term frequency regulation response scenarios, avoiding insufficient frequency regulation caused by small frequency difference, and improving the frequency regulation response speed and performance of the unit. The effect is particularly significant when the grid frequency changes smoothly but needs continuous adjustment, thereby avoiding over-adjustment or reverse adjustment, while improving the speed and accuracy of frequency regulation response and effectively improving the frequency stability of the grid.

[0045] Secondly, this application provides a source-grid coordinated primary frequency regulation optimization system based on load demand, comprising:

[0046] The acquisition module is configured to acquire key parameter information of the power grid and generating units, including power grid frequency data, power grid power, generator set output power, and frequency regulation commands.

[0047] The indicator parameter confirmation module is configured to determine the indicator parameter information for evaluating the frequency regulation performance of the unit based on the key parameter information. The indicator parameter information includes at least response lag time, integral power, and regulation reverse.

[0048] The quantization coding module is configured to determine the indicator parameter information and quantify the indicator parameter information based on the coding analysis method to identify the weak indicator parameters of the unit during frequency regulation.

[0049] The integral power optimization module is configured to determine the deviation between the actual and theoretical integral power based on the weak index parameters and the integral power closed-loop optimization module on the CCS system side, and to add the deviation value to the frequency regulation compensation of the unit to perform closed-loop adjustment of the unit's output power.

[0050] The judgment module is configured to acquire the peak frequency difference and the frequency modulation duration during the closed-loop adjustment process, and to determine whether the peak frequency difference is less than a preset frequency difference threshold and whether the frequency modulation duration is greater than a preset duration threshold.

[0051] The frequency modulation compensation module is configured to compensate for the small frequency difference response and the later response after frequency modulation based on the judgment result of the judgment module.

[0052] Thirdly, this application also provides an electronic device, comprising:

[0053] At least one processor; and

[0054] A memory communicatively connected to the at least one processor; wherein,

[0055] The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the steps of the source-network coordinated primary frequency regulation optimization method based on load demand provided in the first aspect above.

[0056] Fourthly, this application also provides a computer-readable storage medium having stored thereon computer program instructions, which, when executed by a processor, implement the steps of the source-network coordinated primary frequency modulation optimization method based on load demand provided in the first aspect.

[0057] It is understood that the beneficial effects of the technical solutions provided in the second, third and fourth aspects above can be found in the relevant descriptions in the first aspect above, and will not be repeated here.

[0058] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0059] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a flowchart illustrating a source-network coordinated primary frequency modulation optimization method according to an embodiment of this application;

[0061] Figure 2 This is a control flowchart of a prior art primary frequency modulation method according to an embodiment of this application;

[0062] Figure 3 This is a control flow diagram of CCS system-side optimization according to an embodiment of this application;

[0063] Figure 4 This is a schematic diagram of a source-network coordinated primary frequency modulation optimization method according to an embodiment of this application;

[0064] Figure 5 This is a simulation result diagram of closed-loop optimization of frequency modulation index based on source-network coordinated primary frequency modulation optimization method according to an embodiment of this application;

[0065] Figure 6This is a block diagram of a source-grid coordinated primary frequency regulation optimization system based on load demand, as shown in the embodiments of this application.

[0066] Figure 7 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0067] The embodiments of this application are described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. It should be understood that the specific embodiments described herein are merely for explaining this application and are not intended to limit this application.

[0068] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0069] Please see Figures 1 to 5 This embodiment provides a source-grid coordinated primary frequency regulation optimization method based on load demand, including:

[0070] Step S100: Obtain key parameter information of the power grid and generating units, including power grid frequency data, power grid power, generator output power, and frequency regulation command;

[0071] In this step, grid frequency data, grid power, generator output power, and frequency regulation command data can be collected based on corresponding hardware. For example, a high-precision frequency transmitter can be used to collect grid frequency data; a power transmitter can be used to collect grid power and generator output power; and a power dispatching system interface can be used to collect frequency regulation commands and key indicators in the frequency regulation process, providing basic data support for subsequent frequency regulation performance analysis and optimization.

[0072] It should be noted that traditional power system design primarily relies on the inertia and rotational mass of fossil fuel generators (such as coal-fired and natural gas units) to provide frequency regulation support. However, with the increasing proportion of renewable energy sources such as wind and solar power, the traditional inertial response capability is limited. Renewable energy typically relies on power electronic devices (such as inverters) to connect to the grid. These devices do not possess the same rotational inertia as synchronous generators, and therefore cannot directly contribute frequency regulation capabilities like traditional generators. Simultaneously, with the opening of the electricity market, grid operation has become more complex, and the risks of frequency fluctuations and power supply instability are constantly increasing. The output of wind and solar power generation exhibits significant volatility, influenced by meteorological conditions; changes in wind speed and sunlight directly lead to fluctuations in power generation. This volatility, to some extent, exacerbates grid frequency fluctuations, making grid frequency regulation more difficult. Furthermore, load demand within the grid is also dynamically changing, especially in areas with high industrial loads, where load fluctuations are significant, placing higher demands on grid frequency regulation.

[0073] In related technologies, primary frequency regulation control schemes mainly rely on the adjustment relationship between the unit's speed signal and the electrical frequency signal. However, this approach has revealed a series of limitations in modern power grids. First, traditional frequency regulation control schemes typically suffer from frequency regulation response lag; that is, when the frequency changes, the unit cannot respond immediately, thus affecting the rapid stabilization of the grid frequency. Second, under small frequency differences, the regulation effect of traditional frequency regulation methods is not significant, especially when the grid frequency fluctuations are small or change slowly, resulting in insufficient unit response and an inability to effectively maintain frequency stability. Third, during traditional frequency regulation, unit regulation sometimes exhibits reverse regulation; that is, under certain conditions, the frequency regulation response exacerbates frequency fluctuations, mainly due to the dynamic characteristics of the system and the lag in the unit control strategy. Finally, the compliance rate of frequency regulation targets is low, especially when load fluctuations are large or the proportion of renewable energy is high. Traditional frequency regulation control methods often fail to meet the accuracy requirements of grid frequency regulation, leading to grid frequency instability and even the risk of power outages.

[0074] Traditional frequency regulation methods mainly rely on the regulation capabilities of the generation end. However, with the increasing proportion of renewable energy, the insufficient regulation capabilities of the generation end have become a bottleneck restricting the stability of the power grid frequency. One of the key technologies for source-grid coordinated frequency regulation is how to achieve coordination and optimization between the generation end and the load end. The generation end participates in frequency regulation through power electronic devices and energy storage systems, while the load end regulates the load through intelligent control and demand response technologies.

[0075] To achieve coordinated frequency regulation between the power generation and grid, an optimization method that simultaneously considers the regulation capabilities of both the generation and load sides is needed. In this process, frequency regulation accuracy, response speed, and stability are key technical challenges that need to be addressed. Considering the characteristics of frequency fluctuations in the power grid, how to design efficient control strategies and avoid over-regulation and frequency regulation lag in practical applications is crucial. Therefore, this implementation provides a novel coordinated primary frequency regulation optimization method between the power generation and grid. This method should be able to simultaneously regulate the frequency response capabilities of both the generation and load sides, accurately adjust the frequency regulation amplitude of the units, avoid over-regulation or reverse regulation, and improve the speed and accuracy of the frequency regulation response.

[0076] Step S200: Based on the key parameter information, determine the index parameter information for evaluating the frequency regulation performance of the unit. The index parameter information includes at least response lag time, integral power, and regulation reverse.

[0077] In this step, after collecting key parameter information, the response lag time is determined based on the grid frequency data and frequency regulation command. The response lag time is used to characterize the delay between the time when the generator set's output power begins to respond to the frequency regulation command and the time when the frequency regulation command is issued. The integral power is determined based on the grid power and the generator set's output power, and the regulation reverse direction is determined based on the frequency regulation command and the direction of power increase or decrease.

[0078] In some embodiments, the power grid is t Frequency difference at time The calculation formula is as follows:

[0079]

[0080] in, In time The actual frequency measured at any given time, The rated frequency of the power grid is 50Hz.

[0081] Response lag time The calculation formula is as follows:

[0082]

[0083] in, The moment when the generator set's output power begins to change significantly. The response lag time is determined by calculating the time delay between the generator set's output power starting to respond to the frequency regulation command and the time the frequency regulation command is issued, which is the moment when the frequency regulation command is issued.

[0084] Points of electricity The calculation expression is:

[0085] ,

[0086] in, For real-time power, The initial power locked when the frequency modulation operation crosses the dead zone is given, and the integration start time is the frequency dead zone time. The product coefficient;

[0087] The reversal adjustment is determined by judging whether the direction of power increase or decrease is opposite to the frequency modulation command. The calculation formula is as follows:

[0088]

[0089] in, and These are the increments of the frequency modulation command and the actual power change, respectively. If the two changes are in opposite directions, the adjustment is 1 for the reverse direction; otherwise, it is 0.

[0090] Step S300: Determine the indicator parameter information and quantify the indicator parameter information based on the coding analysis method to identify the weak indicator parameters of the unit during frequency regulation;

[0091] In this step, to automate the processing of various parameters of the indicator information, each indicator is first judged according to preset qualification standards. For example, the power contribution rate refers to the ratio of the integral power of the actual operation of a frequency regulation to the integral power of the theoretical operation. A power contribution rate of not less than 75% is considered to meet the standard.

[0092]

[0093] In the formula, the actual integrated energy is Theoretical value of integrated electricity consumption ;

[0094] For a response lag time of no more than 3 seconds, it is considered to meet the standard. For the reverse adjustment indicator, that is, when the integral energy is negative, the adjustment is reversed, and the indicator is not met.

[0095] In some embodiments, in order to achieve automated and accurate processing of various parameters in electronic devices, response lag time, integral power, and adjustment reversal are encoded. Specifically, the encoded index parameter information is used to determine the encoded value corresponding to the frequency regulation result based on a binary method. The encoded values ​​of response lag time, integral power, and adjustment reversal are correlated to determine the numerical parameters used for quantification. Based on the numerical parameters, the pass rate of each assessment indicator after correlation is statistically analyzed, and the relationship between the assessment indicators is analyzed to determine the frequency regulation status information of the weak links in the unit during the frequency regulation process.

[0096] Optionally, the numerical parameters used for quantization are determined by associating the coded values ​​of response lag time, integral power, and reverse regulation. This includes: associating the coded values ​​of response lag time, integral power, and reverse regulation in binary. Since the power contribution index must not meet the standard when the frequency regulation reverses, there are 5 categories of numerical coding results, namely [0, 1, 3, 5, 7]. A value of 0 represents that all three indicators are qualified, a value of 1 represents that the integral power does not meet the standard, a value of 3 represents that the integral contribution rate is qualified but the response lag time indicator is unqualified, a value of 5 represents that the frequency regulation reverses but the response lag time indicator is qualified, and a value of 7 represents that all three indicators are unqualified. The numerical parameters used for quantization are determined as shown in Table (1).

[0097]

[0098] For example, using the monthly frequency regulation assessment results of the generating units as the data source, the pass rate of each assessment indicator is statistically analyzed, and the relationship between the assessment indicators is analyzed. The proportion of non-compliance of the three major assessment indicators and their combinations is statistically analyzed. The indicator with the highest proportion of non-compliance is the contribution rate of the integral electricity, which has the highest proportion of non-compliance, reaching 75% of the number of non-compliances.

[0099]

[0100] Step S400: Based on the weak index parameters, determine the deviation between the actual and theoretical integral power based on the integral power closed-loop optimization module on the CCS system side, and add the deviation value to the frequency regulation compensation of the unit to perform closed-loop adjustment of the unit's output power;

[0101] In this step, the weak performance parameter refers to situations where the integral power output is substandard. Furthermore, in practical applications, substandard integral power output contribution rates have been found to be particularly prominent, especially during frequency regulation when the unit fails to adjust according to the theoretical power output. Therefore, for frequency regulation optimization schemes addressing substandard integral power output, please refer to [reference needed]. Figure 3 and Figure 4 An integral power closed-loop optimization module is added to the CCS system side. This module calculates the actual value of integral power in real time during frequency regulation and compares it with the theoretical value to calculate the deviation. Closed-loop control is achieved through a PI controller, and the integral power deviation is added to the frequency regulation compensation of the unit. In this way, the deviation between the actual power and the theoretical power will gradually decrease during frequency regulation, making the frequency regulation process more accurate and improving the frequency regulation capability of the unit.

[0102] For example, the integrated power consumption closed-loop optimization module is integrated into the CCS system side, which calculates the integrated power consumption in real time throughout the frequency modulation process and outputs the actual value of the integrated power consumption. Theoretical value of integrated energy The deviation is added to the unit's frequency regulation compensation, forming a closed-loop control.

[0103] Specifically, in the existing traditional frequency regulation scheme, the CCS system calculates the frequency feedback signal by using the frequency difference function and the rated frequency. The frequency feedback signal is used as the frequency regulation compensation amount of the unit. This control signal is then transmitted to the subsequent regulation module to generate frequency regulation commands, ensuring that the unit output meets the load requirements.

[0104] The integral power closed-loop optimization module calculates the real-time deviation between the actual and theoretical integral power values ​​and introduces a PI controller to achieve closed-loop control. The output signal of the PI controller and the frequency feedback signal are superimposed on the frequency regulation compensation of the unit, so that the actual power gradually approaches the theoretical power.

[0105] The formula for calculating the actual value of the credited energy is as follows:

[0106]

[0107] in, For real-time power, The initial power locked when the frequency modulation operation crosses the dead zone is given, and the integration start time is the frequency dead zone time. The product coefficient is used as the formula for calculating the theoretical value of the integrated charge, as shown below:

[0108] ,

[0109] in,

[0110] In the formula, This is the difference between the actual frequency and the rated frequency. Where is the rated power of the unit, and K is the product coefficient.

[0111] To ensure that the power contribution of the generator set meets the grid standards, the integral energy closed-loop optimization module compares the deviation between the actual integral energy and the theoretical integral energy in real time. The calculation formula is as follows:

[0112]

[0113] It should be noted that when the deviation between the actual integrated energy and the theoretical integrated energy... When the value is negative, it indicates that the current output power of the unit is lower than the theoretical value, and the system needs to increase the frequency regulation power of the unit. When the value is positive, it indicates that the unit's output power is higher than the theoretical value, and the system needs to reduce the frequency regulation power. The module will adjust the deviation accordingly. A PI controller is introduced to obtain the output signal. The output signal and the frequency feedback signal are superimposed on the unit's frequency regulation compensation. The unit's output power is continuously adjusted through closed-loop control so that the actual integral power is consistent with the theoretical integral power, thereby meeting the grid's frequency regulation requirements.

[0114] Of course, if the weak parameter is response lag time, and the response lag time is too long, the optimization solution can be to replace the original mechanical hydraulic control valve with a high-frequency response electro-hydraulic servo valve (such as a MOOG valve). This type of servo valve can significantly shorten the valve's full stroke action time, and its response frequency needs to reach above 100Hz to support rapid adjustment. The MOOG electro-hydraulic servo valve can quickly respond to frequency modulation requirements by converting low-power electrical signals into high-power hydraulic energy output, thus completing the displacement, speed, and acceleration control of the actuator.

[0115] By shortening the sampling period of the control system from 1 second to 10 ms and employing a high-precision fiber optic frequency measurement device to capture frequency changes in real time, and by installing a fast-release valve at the inlet of the turbine's high-pressure cylinder, the boiler's heat storage capacity is utilized to rapidly release stored energy at the initial stage of frequency deviation, providing instantaneous power support. This method can effectively alleviate the power shortage problem caused by response lag, especially under frequency regulation requirements with small frequency differences and short durations, enabling rapid response and providing necessary power support.

[0116] Similarly, if the weak indicator parameter is the reverse of frequency regulation, it can be optimized and adjusted based on existing technologies. For example, by combining the characteristics of the unit with the frequency regulation mechanism, closed-loop management optimization can be carried out from system diagnosis to optimization implementation. Specifically, existing technologies can be referenced and reasonable designs can be made according to actual needs.

[0117] Step S500: Obtain the peak frequency difference and the frequency modulation duration during the closed-loop adjustment process, and determine whether the peak frequency difference is less than a preset frequency difference threshold and whether the frequency modulation duration is greater than a preset duration threshold;

[0118] In this step, although the deviation of the integrated power has been effectively improved in the previous steps, time series analysis of frequency difference and power output data reveals that there are still problems of insufficient response to small frequency differences and insufficient response in the later stage after long-term frequency modulation during the frequency modulation process.

[0119] Currently, small frequency fluctuations occur far more frequently than large frequency fluctuations in the grid frequency, meaning that the maximum frequency difference in most effective primary frequency regulation tests is less than 0.06Hz. For frequency regulation requirements with small frequency difference amplitudes and short durations, conventional control schemes result in minimal changes to the turbine's integrated valve position, and load changes are even masked by the unit's own power fluctuations, leading to substandard frequency regulation performance or even reverse regulation.

[0120] To address these issues, this step proposes a solution for a frequency regulation index compensation module. The solution includes small frequency difference response compensation and post-frequency regulation response compensation after a long period of frequency regulation. Small frequency difference response compensation: When the peak frequency difference is lower than a predetermined threshold, the compensation mechanism is activated. The compensation module automatically adjusts the frequency regulation amplitude of the unit based on the absolute value of the current frequency difference and the duration of frequency regulation, ensuring that the unit can still generate sufficient power regulation under small frequency difference conditions.

[0121] Step S600: If so, compensate for the small frequency difference response and the later response after frequency modulation based on the frequency modulation compensation module.

[0122] In this step, the goal of small frequency difference response compensation is to enhance the unit's response when the grid frequency difference is small, so as to ensure that the unit can still provide sufficient power adjustment when the frequency difference is lower than the predetermined threshold. Usually, the insufficient response under small frequency difference is because the frequency regulation system does not make large adjustments under small frequency difference by default. By increasing the compensation amount, the frequency regulation sensitivity under small frequency difference can be significantly improved.

[0123] When frequency difference The absolute value is lower than the predetermined threshold When this occurs, small frequency difference response compensation is triggered, and the calculation formula for the compensation increment is as follows:

[0124]

[0125] in, To compensate for the power increment, This is the gain coefficient for small frequency difference compensation. This is the difference between the actual frequency and the rated frequency.

[0126] For post-frequency regulation response compensation: By introducing a compensation mechanism, the unit's response capability after long-term frequency regulation is increased, ensuring continuous frequency regulation capability and improving the unit's stability and reliability.

[0127] The post-response compensation is mainly based on the changes in frequency modulation duration and frequency difference. After the frequency modulation process has lasted for a period of time, the compensation power is appropriately increased so that the unit's response capability can be restored to a higher level.

[0128] Assuming the frequency modulation duration is When the time exceeds the threshold When this occurs, post-response compensation is activated, and the compensation increment is calculated using the following formula:

[0129] ,

[0130] in, To compensate for the power increment in the later stage, This is the gain coefficient for later compensation. For frequency modulation duration, The time exceeding the preset frequency difference threshold within the frequency modulation duration.

[0131] For example, Figure 2 For existing traditional frequency regulation schemes, add an integral power closed-loop optimization module and a frequency regulation compensation module (such as...) to the CCS system side of the traditional scheme. Figure 3 As shown), the integral power closed-loop optimization module calculates the integral power compensation; the frequency modulation compensation module includes small frequency difference response compensation and later response compensation; then, a frequency modulation compensation module is added on the DEH system side to obtain the source-network coordinated primary frequency modulation optimization scheme (as shown). Figure 4 (As shown).

[0132] In some examples, to verify the feasibility of the methods and steps in the above embodiments, the effectiveness of the designed primary frequency regulation optimization scheme is verified using a step setpoint disturbance. The initial load of the unit is 180.7MW, the disturbance frequency is 0.095Hz, the duration is 70s, and the speed inequality rate of the speed regulation system is 4%. The primary frequency regulation response is simulated using both the traditional scheme and the designed primary frequency regulation optimization scheme. The simulation results are as follows: Figure 5 As shown.

[0133] from Figure 5 As can be seen, in the initial stage of frequency regulation, there is a significant difference between the actual load of the unit and the ideal curve. At this time, the frequency regulation index closed-loop optimization module enhances the power control parameters. As the frequency regulation process continues, the actual load gradually approaches the ideal curve, and the difference gradually decreases. Through comparison, it can be found that after adopting a primary frequency regulation optimization scheme to adaptively adjust the control parameters, the frequency regulation response speed is effectively improved.

[0134] It should be noted that the above method involves collecting grid frequency data, grid power, generator output power, and frequency regulation command information at the generation end. Response lag time, integral power, and regulation reversal index, which evaluate the unit's frequency regulation performance, are calculated separately. These three indicators are quantified using binary coding analysis. Electronic equipment enables automated statistical analysis of the frequency of different coded values ​​and correlation analysis of indicator codes. This identifies the integral power index affecting the unit's frequency regulation performance. By adding an integral power closed-loop optimization module at the load end, the unit's frequency regulation compensation is calculated and adjusted in real time, gradually reducing the deviation between actual and theoretical power.

[0135] The frequency regulation index compensation increment is composed of small frequency difference response compensation and later response compensation. The frequency regulation index compensation increment is added to the CCS system side and accumulated with the original unit frequency regulation compensation. At the same time, the compensation increment is superimposed on the frequency feedback signal to the DEH system side to improve the frequency regulation amplitude under small frequency difference and the response strength after long-term frequency regulation, thereby enhancing the overall frequency regulation performance of the unit. Through this compensation mechanism, the frequency regulation index compensation module ensures that the generator unit can operate effectively under both small frequency difference and long-term frequency regulation response scenarios, avoiding insufficient frequency regulation caused by small frequency difference, and improving the frequency regulation response speed and performance of the unit. The effect is particularly significant when the grid frequency changes smoothly but needs continuous adjustment, thereby avoiding over-adjustment or reverse adjustment, while improving the speed and accuracy of frequency regulation response and effectively improving the frequency stability of the grid.

[0136] Please see Figure 6 , Figure 6 This diagram illustrates a block diagram of a load demand-based source-grid coordinated primary frequency regulation optimization system 200, which includes:

[0137] The acquisition module 210 is configured to acquire key parameter information of the power grid and the generating unit, including power grid frequency data, power grid power, generator set output power and frequency regulation command;

[0138] The indicator parameter confirmation module 220 is configured to determine the indicator parameter information for evaluating the frequency regulation performance of the unit based on the key parameter information. The indicator parameter information includes at least response lag time, integral power, and regulation reverse.

[0139] The quantization coding module 230 is configured to determine the indicator parameter information and quantify the indicator parameter information based on the coding analysis method to identify the weak indicator parameters of the unit during frequency regulation.

[0140] The integral power optimization module 240 is configured to determine the deviation between the actual and theoretical integral power based on the weak index parameters and the integral power closed-loop optimization module on the CCS system side, and to add the deviation value to the frequency regulation compensation of the unit to perform closed-loop adjustment of the unit's output power.

[0141] The judgment module 250 is configured to acquire the peak frequency difference and the frequency modulation duration during the closed-loop adjustment process, and to determine whether the peak frequency difference is less than a preset frequency difference threshold and whether the frequency modulation duration is greater than a preset duration threshold.

[0142] The frequency modulation compensation module 260 is configured to compensate for the small frequency difference response and the later response after frequency modulation based on the judgment result of the judgment module.

[0143] It is understood that, in this embodiment, the source-grid coordinated primary frequency regulation optimization system 200 based on load demand operates as described above during implementation. Figure 1 The technical effects achievable by the source-grid coordinated primary frequency regulation optimization method based on load demand in the corresponding embodiment can be found in the above description. Figure 1 The technical effects achieved in the corresponding embodiments will not be elaborated upon here.

[0144] Please see Figure 7 , Figure 7 This is a structural block diagram of an electronic device provided in an embodiment of this application. The server 500 of this electronic device includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501, such as a program for a source-network coordinated primary frequency modulation optimization method based on load demand. When the processor 501 executes the computer program 503, it implements the steps of the source-network coordinated primary frequency modulation optimization method based on load demand in the above embodiments, for example... Figure 1 Steps S100 to S600 in the corresponding embodiment. Alternatively, the processor 501 executes the computer program 503 to implement the above. Figure 6 The functions of each module in the corresponding embodiments, for example, Figure 6 For details on the functions of the modules shown (e.g., module 210), please refer to [link / reference]. Figure 6 The relevant descriptions in the corresponding embodiments are not repeated here.

[0145] For example, computer program 503 can be divided into one or more units, one or more units are stored in memory 502 and executed by processor 501 to complete the technical solution provided in the above embodiments. One or more units can be a series of computer program instruction segments capable of performing a specific function, which are used to describe the execution process of computer program 503 in server 500.

[0146] The electronic device may include, but is not limited to, a processor 501 and a memory 502. Those skilled in the art will understand that... Figure 7 This is merely an example of server 500 in an electronic device and does not constitute a limitation on server 500. It may include more or fewer components than shown, or combine certain components, or different components. For example, a turntable terminal device may also include input / output terminal devices, network access terminal devices, buses, etc.

[0147] The processor 501 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0148] The memory 502 can be an internal storage unit of the server 500, such as the server 500's hard drive or memory. The memory 502 can also be an external storage terminal device of the server 500, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the server 500. Furthermore, the memory 502 can include both internal storage units and external storage terminal devices of the server 500. The memory 502 is used to store computer programs and other programs and data required by the turntable terminal device. The memory 502 can also be used to temporarily store data that has been output or will be output.

[0149] In some embodiments, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of the source-network coordinated primary frequency regulation optimization method based on load demand as described in the above embodiments.

[0150] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0151] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be non-volatile or volatile. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0152] The terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects and not to describe a particular order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, it may include a series of steps or units, or optionally, steps or units not listed, or other steps or units inherent to these processes, methods, products, or devices.

[0153] The accompanying drawings show only the portions relevant to this application, not all of them. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations may be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process may correspond to a method, function, procedure, subroutine, subprogram, etc.

[0154] The terms “component,” “module,” “system,” “unit,” etc., used in this specification are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a unit can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, a thread of execution, a program, and / or distributed between two or more computers. Furthermore, these units can be executed from various computer-readable media on which various data structures are stored. Units can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from a second unit interacting with another unit between a local system, a distributed system, and / or a network; for example, the Internet interacting with other systems via signals).

[0155] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0156] Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The reference to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily indicate the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0157] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

[0158] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

Claims

1. A source-grid coordinated primary frequency regulation optimization method based on load demand, characterized in that, include: Acquire key parameter information of the power grid and generating units, including power grid frequency data, power grid power, generator output power, and frequency regulation commands; Based on the key parameter information, the index parameter information for evaluating the frequency regulation performance of the unit is determined. The index parameter information includes at least response lag time, integral power, and regulation reverse. The indicator parameter information is judged and quantified based on the coding analysis method to determine the weak indicator parameters of the unit during frequency regulation. This includes coding the response lag time, the integral power, and the regulation reversal. In the indicator parameter information, each indicator is coded as 0 if it meets the standard and 1 if it does not. The integral power is less than 50 and it does not meet the standard. The response lag time is greater than 2 and it does not meet the standard. The regulation reversal indicator does not meet the standard when the integral power is negative. The encoded value corresponding to the frequency modulation result is determined based on the binary method for the encoded index parameter information; The response lag time, the integral power, and the encoding value of the adjustment reversal are correlated to determine the numerical parameters used for quantization. The response lag time, the integral power, and the encoding value of the adjustment reversal are correlated in binary. There are five categories of numerical encoding results, namely [0,1,3,5,7]. The value 0 represents that all three indicators are qualified, the value 1 represents that the integral power is not qualified, the value 3 represents that the integral contribution rate is qualified but the response lag time indicator is not qualified, the value 5 represents that the frequency modulation action is reversed but the response lag time indicator is qualified, and the value 7 represents that all three indicators are not qualified. The numerical parameters used for quantization are determined. Based on the numerical parameters, the pass rates of each assessment indicator after statistical correlation are calculated and the relationship between the assessment indicators is analyzed to determine the frequency regulation status information of the weak links in the frequency regulation process of the unit. Based on the aforementioned weak index parameters, the deviation between the actual and theoretical integral power is determined by the integral power closed-loop optimization module on the CCS system side, and the deviation is added to the frequency regulation compensation of the unit to perform closed-loop adjustment of the unit's output power. The peak frequency difference and the duration of frequency modulation are obtained during the closed-loop adjustment process. It is then determined whether the peak frequency difference is less than a preset frequency difference threshold and whether the duration of frequency modulation is greater than a preset duration threshold. If so, the frequency modulation compensation module compensates for the small frequency difference response and the later response after frequency modulation.

2. The source-grid coordinated primary frequency regulation optimization method based on load demand as described in claim 1, characterized in that, The step of determining the index parameters for evaluating the frequency regulation performance of the generating unit based on the key parameter information includes at least response lag time, integral power, and regulation reverse, including: Based on the power grid frequency data and the frequency regulation command, the response lag time is determined, wherein the response lag time is used to characterize the delay between the time when the generator set's output power begins to respond to the frequency regulation command and the time when the frequency regulation command is issued. Based on the grid power and the generator set output power, determine the integral energy, and The adjustment reverse direction is determined based on the frequency modulation command and the direction of power increase or decrease.

3. The source-grid coordinated primary frequency regulation optimization method based on load demand according to claim 1, characterized in that, The integral power is determined based on the grid power and the generator output power, and the adjustment reverse direction is determined based on the frequency regulation command and the direction of power increase / decrease, including: Points of electricity The calculation expression is: ， in, For real-time power, The initial power locked when the frequency modulation operation crosses the dead zone is given, and the integration start time is the frequency dead zone time. The product coefficient; The expression for adjusting the inverse is: ， in, and These represent the increments of the frequency modulation command and the actual power change, respectively. If the two changes are in opposite directions, the adjustment is 1 for the reverse direction; otherwise, it is 0.

4. The source-grid coordinated primary frequency regulation optimization method based on load demand as described in claim 1, characterized in that, The step involves determining the deviation between the actual and theoretical integral power based on the weak index parameters and the integral power closed-loop optimization module on the CCS system side, and then adding the deviation to the unit's frequency regulation compensation to perform closed-loop adjustment of the unit's output power, including: The expression for calculating the theoretical value of the integrated energy is: ， in, , In the formula, This is the difference between the actual frequency and the rated frequency. Where is the rated power of the unit, and K is the product coefficient.

5. The source-grid coordinated primary frequency regulation optimization method based on load demand according to claim 1, characterized in that, If so, the compensation for the small frequency difference response and the later response after frequency modulation is performed based on the frequency modulation compensation module, including: The formula for calculating the power increment of the small frequency difference response compensation is: ， in, To compensate for the power increment, This is the gain coefficient for small frequency difference compensation. This is the difference between the actual frequency and the rated frequency. The formula for calculating the power increment of the later response compensation is: ， in, To compensate for the power increment in the later stage, This is the gain coefficient for later compensation. For frequency modulation duration, The time exceeding the preset frequency difference threshold within the frequency modulation duration.

6. A source-grid coordinated primary frequency regulation optimization system based on load demand, characterized in that, The system is applied to the source-grid coordinated primary frequency regulation optimization method based on load demand as described in any one of claims 1-5, including: The acquisition module is configured to acquire key parameter information of the power grid and generating units, including power grid frequency data, power grid power, generator set output power, and frequency regulation commands. The indicator parameter confirmation module is configured to determine the indicator parameter information for evaluating the frequency regulation performance of the unit based on the key parameter information. The indicator parameter information includes at least response lag time, integral power, and regulation reverse. The quantization coding module is configured to determine the indicator parameter information and quantify the indicator parameter information based on the coding analysis method to identify the weak indicator parameters of the unit during frequency regulation. The integral power optimization module is configured to determine the deviation between the actual and theoretical integral power based on the weak index parameters and the integral power closed-loop optimization module on the CCS system side, and to add the deviation value to the frequency regulation compensation of the unit to perform closed-loop adjustment of the unit's output power. The judgment module is configured to acquire the peak frequency difference and the frequency modulation duration during the closed-loop adjustment process, and to determine whether the peak frequency difference is less than a preset frequency difference threshold and whether the frequency modulation duration is greater than a preset duration threshold. The frequency modulation compensation module is configured to compensate for the small frequency difference response and the later response after frequency modulation based on the judgment result of the judgment module.

7. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the steps of the source-grid coordinated primary frequency regulation optimization method based on load demand, as described in any one of claims 1-5.

8. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the steps of any one of the source-network coordinated primary frequency regulation optimization methods based on load demand, as described in any one of claims 1-5.

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