Frequency optimization control method and system for network construction type wind power grid-connected system

Abstract

The invention relates to the technical field of power grid management, and particularly discloses a frequency optimization control method and system for a grid-forming type wind power grid-connected system, and the method comprises the steps: monitoring the real-time power grid state and real-time node frequency distribution data of the grid-forming type wind power grid-connected system; recording a power grid disturbance quantity in a preset monitoring period; inputting the real-time power grid state, the real-time power grid frequency and the power grid disturbance quantity in the preset monitoring period of the network-forming type wind power grid-connected system into the self-adaptive frequency optimization control model to obtain a frequency optimization control scheme; the overall performance of the grid-forming type wind power grid-connected system can be improved, the grid-forming type wind power grid-connected system can better adapt to changes and interferences of a power grid, and safe and stable operation of a power system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid management, and in particular to a frequency optimization control method and system for a grid-connected wind power system. Background Art

[0002] At present, with the increasing global demand for renewable energy, wind power generation has been widely developed as a clean and renewable energy form. However, the intermittent and volatile nature of wind power has brought challenges to the stable operation of the power system, especially in terms of frequency control. Traditional wind power grid-connected systems usually adopt a grid-following control strategy, which mainly responds by adjusting the output power when the grid frequency changes, but this method may cause the system frequency stability to decrease when dealing with large-scale wind power access. The grid-connected wind power grid-connected system can actively participate in the frequency regulation of the system and improve the stability of the power system by simulating the characteristics of synchronous generators. The existing frequency optimization control method of the grid-connected wind power grid-connected system simulates the characteristics of synchronous generators and adopts virtual inertia control, primary frequency regulation control, coordinated control and advanced control algorithms to provide reliable technical support for large-scale wind power access. In the power system, frequency is a key parameter that reflects the balance between power generation and load in the system. Maintaining the stability of frequency is crucial for the safe and reliable operation of the power system. Therefore, it is of great practical significance to optimize the frequency control of the grid-connected wind power grid-connected system.

[0003] However, the existing grid-connected wind power systems are not robust enough to changes in system parameters and external interference. When system parameters change or are subject to external interference, the frequency control effect may be greatly affected, making it difficult to ensure the stable operation of the system. There may be adaptability issues when dealing with large-scale wind power access. With the continuous increase in wind power installed capacity, the dynamic characteristics of the system change, and the existing frequency control methods may not be able to effectively cope with such changes. When the system experiences frequency fluctuations, it cannot be adjusted in time, which may lead to a decrease in system stability.

[0004] Therefore, the present invention proposes a frequency optimization control method and system for a grid-connected wind power system. Summary of the invention

[0005] The present invention provides a frequency optimization control method and system for a grid-connected wind power system, which can effectively improve the frequency stability and reliability of the power system by monitoring the real-time power grid status and real-time node frequency distribution data of the grid-connected wind power system and the power grid disturbance amount within a preset monitoring period, and combining with a professional adaptive frequency optimization control model, and help improve the overall performance of the grid-connected wind power system, better adapt to changes and interference in the power grid, and ensure the safe and stable operation of the power system.

[0006] The present invention provides a frequency optimization control method for a grid-connected wind power system, comprising:

[0007] S1: monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system;

[0008] S2: Record the power grid disturbance amount within the preset monitoring period;

[0009] S3: The real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of the grid-connected wind power system are input into the adaptive frequency optimization control model to obtain a frequency optimization control scheme.

[0010] Preferably, the frequency optimization control method of the grid-connected wind power system, S1: monitoring the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system, including:

[0011] Determine the real-time grid flow distribution and real-time node voltage distribution data of the grid-connected wind power system as the real-time grid state of the grid-connected wind power system;

[0012] Obtain real-time node frequency distribution data of the grid-connected wind power system.

[0013] Preferably, the frequency optimization control method of the grid-connected wind power system determines the real-time grid flow distribution and real-time node voltage distribution data of the grid-connected wind power system, including:

[0014] Determine the real-time grid reactive power flow distribution and the real-time grid active power flow distribution of the grid-building type wind power grid-connected system as the real-time grid flow distribution of the grid-building type wind power grid-connected system;

[0015] Obtain real-time node voltage distribution data of the grid-connected wind power system.

[0016] Preferably, the frequency optimization control method of the grid-connected wind power system, which obtains the real-time node frequency distribution data of the grid-connected wind power system, includes:

[0017] Obtain all frequency monitoring points in the power grid of the grid-connected wind power system;

[0018] Among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the main frequency monitoring points and all the secondary frequency monitoring points of the current preset monitoring period are screened out;

[0019] Set the monitoring intervals for all primary frequency monitoring points and the monitoring intervals for all secondary frequency monitoring points;

[0020] Based on the monitoring intervals of all the main frequency monitoring points, the frequencies of all the main frequency monitoring points in the grid of the grid-connected wind power system are obtained. Meanwhile, based on the monitoring intervals of all the secondary frequency monitoring points, the frequencies of all the secondary frequency monitoring points in the grid of the grid-connected wind power system are obtained.

[0021] Based on the acquired frequencies of all primary frequency monitoring points and all secondary frequency monitoring points in the power grid of the grid-connected wind power system, real-time node frequency distribution data of the grid-connected wind power system is obtained.

[0022] Preferably, the frequency optimization control method of the grid-connected wind power system includes screening out all the main frequency monitoring points and all the secondary frequency monitoring points of the current preset monitoring period from all the frequency monitoring points in the power grid of the grid-connected wind power system, including:

[0023] In the historical frequency record data of all frequency monitoring points in the power grid of the grid-connected wind power system within a preset period, all abnormal frequency fluctuation records of each frequency monitoring point within the preset period are determined;

[0024] Based on all abnormal frequency fluctuation records of each frequency monitoring point within a preset period, all abnormal frequency fluctuation duration periods and all abnormal frequency fluctuation duration value records of each frequency monitoring point within the preset period are determined;

[0025] Determine the key coefficients of each frequency monitoring point in the grid of the grid-connected wind power system;

[0026] Based on the key coefficient of each frequency monitoring point in the grid of the grid-connected wind power system and all frequency abnormal fluctuation duration periods and all frequency abnormal fluctuation duration numerical records within a preset period, the importance of each frequency monitoring point is calculated;

[0027] Among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the frequency monitoring points whose importance is not less than the importance threshold are regarded as all the main frequency monitoring points of the current preset monitoring period. At the same time, among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the frequency monitoring points whose importance is less than the importance threshold are regarded as all the secondary frequency monitoring points of the current preset monitoring period.

[0028] Preferably, the frequency optimization control method of the grid-connected wind power system calculates the importance of each frequency monitoring point based on the key coefficient of each frequency monitoring point in the power grid of the grid-connected wind power system and all frequency abnormal fluctuation duration periods and all frequency abnormal fluctuation duration numerical records within a preset period, including:

[0029]

[0030] Where d is the importance of the frequency monitoring point, δ is the key coefficient of the frequency monitoring point, n is the total number of all frequency abnormal fluctuation duration periods of the frequency monitoring point within the preset period, and t is is the starting time of the ith abnormal frequency fluctuation duration period at the frequency monitoring point within the preset period, t ie is the end time of the duration of the ith abnormal frequency fluctuation at the frequency monitoring point within the preset time period, t0 is the current time, t s·min The earliest time among the starting times of all frequency abnormal fluctuation duration periods at the frequency monitoring point within the preset time period, FRQ imax FRQ is the maximum frequency value recorded in the continuous numerical record of the ith frequency abnormal fluctuation at the frequency monitoring point within the preset period. imin FRQ is the minimum frequency value recorded in the continuous numerical record of the ith frequency abnormal fluctuation at the frequency monitoring point within the preset period. 0·lim It is the maximum allowable frequency value of the frequency monitoring point.

[0031] Preferably, the frequency optimization control method of the grid-connected wind power system, based on the frequencies of all main frequency monitoring points and all secondary frequency monitoring points in the grid of the grid-connected wind power system, obtains the real-time node frequency distribution data of the grid-connected wind power system, including:

[0032] Based on the acquired frequencies of all main frequency monitoring points and all secondary frequency monitoring points in the power grid of the grid-connected wind power system, dynamic node frequency distribution data of the grid-connected wind power system is generated;

[0033] The dynamic node frequency distribution data of the grid-connected wind power system is sampled as a whole according to time slices to obtain the real-time node frequency distribution data of the grid-connected wind power system.

[0034] Preferably, the frequency optimization control method of the grid-connected wind power system acquires the real-time node voltage distribution data of the grid-connected wind power system, including:

[0035] Obtain all voltage monitoring points in the grid of the grid-connected wind power system;

[0036] The voltages of all voltage monitoring points in the power grid of the grid-connected wind power system are acquired in real time, and based on the voltages of all voltage monitoring points in the power grid of the grid-connected wind power system acquired in real time, real-time node voltage distribution data of the grid-connected wind power system is generated in real time.

[0037] Preferably, the frequency optimization control method of the grid-connected wind power system, S2: recording the grid disturbance amount within a preset monitoring period, comprises:

[0038] S201: Based on the real-time node voltage distribution data and the real-time node frequency distribution data of the grid-connected wind power system, identifying the voltage disturbance record and the frequency disturbance record occurring within a preset monitoring period;

[0039] S202: Obtaining power grid fault disturbance records within a preset monitoring period;

[0040] Among them, the power grid disturbance includes voltage disturbance records, frequency disturbance records and power grid fault disturbance records.

[0041] The present invention provides a frequency optimization control system for a grid-connected wind power system, which is applied to the frequency optimization control method for a grid-connected wind power system described in any one of Embodiments 1 to 9, comprising:

[0042] The grid status monitoring module is used to monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system;

[0043] A power grid disturbance recording module is used to record the power grid disturbance amount within a preset monitoring period;

[0044] The optimization scheme determination module is used to input the real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of the grid-connected wind power system into the adaptive frequency optimization control model to obtain the frequency optimization control scheme.

[0045] The beneficial effects of the present invention compared to the prior art are as follows: real-time monitoring of the grid status and node frequency distribution data of the grid-connected wind power system helps to timely understand the system operation status and provide accurate basic information for subsequent control and optimization. Recording the grid disturbance amount within the preset monitoring period can better analyze the interference to the system and provide a basis for frequency optimization control. By inputting the real-time grid status, real-time grid frequency and grid disturbance amount into the adaptive frequency optimization control model, a targeted frequency optimization control scheme can be obtained to improve the frequency stability and reliability of the system. It helps to improve the overall performance of the grid-connected wind power system, better adapt to changes and interference in the power grid, and ensure the safe and stable operation of the power system.

[0046] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0047] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0049] Figure 1 A flow chart of a frequency optimization control method for a grid-connected wind power system according to an embodiment of the present invention;

[0050] Figure 2 Schematic diagram of a frequency optimization control system for a grid-connected wind power system in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0052] Embodiment 1:

[0053] The present invention provides a frequency optimization control method for a grid-connected wind power system, referring to Figure 1 ,include:

[0054] S1: monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system;

[0055] S2: Record the power grid disturbance amount within the preset monitoring period;

[0056] S3: The real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of the grid-connected wind power system are input into the adaptive frequency optimization control model to obtain a frequency optimization control scheme.

[0057] In this embodiment, the grid-connected wind power system is a technology that connects a wind power generation system to a power grid. It mainly controls the output characteristics of wind turbines so that they can provide stable voltage and frequency support to the power grid like traditional synchronous generators, thereby enhancing the stability and reliability of the power grid.

[0058] In this embodiment, the real-time node frequency distribution data includes the latest obtained frequencies at all frequency monitoring points in the power grid.

[0059] In this embodiment, the preset monitoring period is a preset continuous monitoring and statistical period of the power grid disturbance amount.

[0060] In this embodiment, the adaptive frequency optimization control model is trained in advance using the real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of a large number of grid-connected wind power systems (as the model input in the model training process), and the frequency optimization control scheme determined by the above information of professionals (as the model output in the model training process) as training samples.

[0061] In this embodiment, the frequency optimization control scheme is a scheme to achieve optimized control of the grid frequency by controlling the change of specific state quantities in the grid. For example, when a sudden large load increase in the grid causes a drop in frequency, the grid-connected wind power system will immediately detect this change. The control system will increase the speed of the wind turbine to generate more electricity and inject it into the grid to help restore the frequency. At the same time, the energy storage system will also release electricity as needed to provide additional support.

[0062] The beneficial effects of the above technology are: real-time monitoring of the grid status and node frequency distribution data of the grid-connected wind power system helps to timely understand the system operation status and provide accurate basic information for subsequent control and optimization. Recording the grid disturbance within the preset monitoring period can better analyze the interference to the system and provide a basis for frequency optimization control. By inputting the real-time grid status, real-time grid frequency and grid disturbance into the adaptive frequency optimization control model, a targeted frequency optimization control solution can be obtained to improve the frequency stability and reliability of the system. It helps to improve the overall performance of the grid-connected wind power system, better adapt to changes and interference in the power grid, and ensure the safe and stable operation of the power system.

[0063] Embodiment 2:

[0064] Based on Example 1, a frequency optimization control method for a grid-connected wind power system, S1: monitoring the real-time grid state and real-time node frequency distribution data of the grid-connected wind power system, including:

[0065] Determine the real-time grid flow distribution and real-time node voltage distribution data of the grid-connected wind power system as the real-time grid state of the grid-connected wind power system;

[0066] Obtain real-time node frequency distribution data of the grid-connected wind power system.

[0067] In this embodiment, the real-time node voltage distribution data includes the latest obtained voltages at all voltage monitoring points in the power grid.

[0068] The beneficial effects of the above technologies are: being able to clearly understand the real-time grid flow distribution, which helps to optimize the power transmission path and distribution. Clarifying the real-time node voltage distribution data ensures the stable operation of the power grid and the quality of power. Mastering the real-time node frequency distribution data facilitates the effective regulation of the system frequency. By determining the real-time grid flow distribution, real-time node voltage distribution data, and real-time node frequency distribution data of the grid-connected wind power system, the real-time operating status of the grid-connected wind power system can be fully and accurately grasped, providing strong support for the optimized operation and control of the system.

[0069] Embodiment 3:

[0070] On the basis of Example 2, the frequency optimization control method of the grid-connected wind power system determines the real-time grid flow distribution and real-time node voltage distribution data of the grid-connected wind power system, including:

[0071] Determine the real-time grid reactive power flow distribution and the real-time grid active power flow distribution of the grid-building type wind power grid-connected system as the real-time grid flow distribution of the grid-building type wind power grid-connected system;

[0072] Obtain real-time node voltage distribution data of the grid-connected wind power system.

[0073] In this embodiment, the real-time grid reactive power flow distribution indicates the distribution of the direction and magnitude of reactive power flowing in each node and line in the grid. For example, in an electric power system, reactive power may flow from reactive compensation equipment (such as capacitor banks) to loads that require reactive power support to maintain the voltage within a suitable range.

[0074] In this embodiment, the real-time grid active power flow distribution indicates the distribution of the direction and size of the active power flowing in the grid at each node and line. For example, in a grid, the active power generated by a power plant is transmitted to each substation through a transmission line and then distributed to different users. The real-time grid active power flow distribution can help power system operators understand the operating status of the grid, ensure a stable supply of electric energy, and perform reasonable scheduling and control.

[0075] The beneficial effects of the above technologies are: clarifying the real-time reactive and active power flow distribution can optimize the power transmission and distribution of the power grid and reduce losses. It helps to detect power flow anomalies in a timely manner and ensure the stability and reliability of system operation. Obtaining real-time node voltage distribution data can effectively maintain the voltage stability of the power grid and improve the quality of power. This helps to fully and accurately grasp the operating status of the system, providing a key basis for optimizing the system's control, ensuring power quality and stable operation.

[0076] Embodiment 4:

[0077] On the basis of Example 2, a frequency optimization control method for a grid-connected wind power system is provided to obtain real-time node frequency distribution data of the grid-connected wind power system, including:

[0078] Obtain all frequency monitoring points in the power grid of the grid-connected wind power system;

[0079] Among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the main frequency monitoring points and all the secondary frequency monitoring points of the current preset monitoring period are screened out;

[0080] Set the monitoring intervals for all primary frequency monitoring points and the monitoring intervals for all secondary frequency monitoring points;

[0081] Based on the monitoring intervals of all the main frequency monitoring points, the frequencies of all the main frequency monitoring points in the grid of the grid-connected wind power system are obtained. Meanwhile, based on the monitoring intervals of all the secondary frequency monitoring points, the frequencies of all the secondary frequency monitoring points in the grid of the grid-connected wind power system are obtained.

[0082] Based on the acquired frequencies of all primary frequency monitoring points and all secondary frequency monitoring points in the power grid of the grid-connected wind power system, real-time node frequency distribution data of the grid-connected wind power system is obtained.

[0083] In this embodiment, the frequency monitoring point in the power grid refers to a specific location set in the power grid for measuring and monitoring the power grid frequency.

[0084] In this embodiment, the primary frequency monitoring point refers to a specific monitoring location that has a key position in the power grid and plays an important role in overall frequency monitoring and control.

[0085] In this embodiment, the secondary frequency monitoring point is a monitoring location that has a relatively lower status in the power grid compared to the primary frequency monitoring point, but can still provide supplementary and auxiliary information for power grid frequency monitoring.

[0086] In this embodiment, setting the monitoring interval of all primary frequency monitoring points and the monitoring interval of all secondary frequency monitoring points refers to clearly stipulating the time intervals for data collection and monitoring of primary frequency monitoring points that play a key role in the power grid and relatively secondary secondary frequency monitoring points.

[0087] For example, the monitoring interval of key frequency monitoring points may be set to every 5 minutes. This is because these points are crucial for timely grasping key changes in grid frequency. More frequent monitoring can quickly detect potential problems and take timely regulatory measures.

[0088] For secondary frequency monitoring points, the monitoring interval may be set to once every 15 minutes. Because the frequency changes at these points are relatively small or have a relatively weak impact on the overall stability of the power grid, less frequent monitoring can save monitoring resources and understand their frequency status to a certain extent.

[0089] In this embodiment, the frequency of the primary (secondary) frequency monitoring point is the frequency of the AC power of the power grid monitored at the location of the monitoring point.

[0090] The beneficial effects of the above technologies are: comprehensive acquisition of frequency monitoring points to ensure the integrity and accuracy of frequency monitoring. Distinguishing between primary and secondary monitoring points and setting different interval times to improve monitoring efficiency and rational resource utilization. Accurately acquiring frequency data helps to detect frequency anomalies in a timely manner and ensure the stable operation of the system. Obtaining real-time node frequency distribution data provides an important basis for the optimization control and operation strategy formulation of the system. By acquiring and screening the frequency monitoring points of the grid-connected wind power system, setting the monitoring interval time of different monitoring points, and acquiring frequency data accordingly, and finally obtaining real-time node frequency distribution data, it is possible to achieve refined monitoring and effective control of the system frequency, providing strong support for the stable operation and optimization regulation of the system.

[0091] Embodiment 5:

[0092] On the basis of Example 4, the frequency optimization control method of the grid-connected wind power system of the grid-connected wind power system selects all the main frequency monitoring points and all the secondary frequency monitoring points of the current preset monitoring period from all the frequency monitoring points in the grid of the grid-connected wind power system of the grid-connected wind power system, including:

[0093] In the historical frequency record data of all frequency monitoring points in the power grid of the grid-connected wind power system within a preset period, all abnormal frequency fluctuation records of each frequency monitoring point within the preset period are determined;

[0094] Based on all abnormal frequency fluctuation records of each frequency monitoring point within a preset period, all abnormal frequency fluctuation duration periods and all abnormal frequency fluctuation duration value records of each frequency monitoring point within the preset period are determined;

[0095] Determine the key coefficients of each frequency monitoring point in the grid of the grid-connected wind power system;

[0096] Based on the key coefficient of each frequency monitoring point in the grid of the grid-connected wind power system and all frequency abnormal fluctuation duration periods and all frequency abnormal fluctuation duration numerical records within a preset period, the importance of each frequency monitoring point is calculated;

[0097] Among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the frequency monitoring points whose importance is not less than the importance threshold are regarded as all the main frequency monitoring points of the current preset monitoring period. At the same time, among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the frequency monitoring points whose importance is less than the importance threshold are regarded as all the secondary frequency monitoring points of the current preset monitoring period.

[0098] In this embodiment, the preset period refers to a specific time period set in advance. Here, the "preset period" refers to a specific time period set in advance. It is a time period determined in advance according to actual needs, monitoring purposes or system design, and is used to analyze and process the frequency recording data of all frequency monitoring points in the grid of the grid-connected wind power system. This time period can be a few minutes, hours, days or even longer, depending on the focus and requirements of the research or monitoring.

[0099] In this embodiment, the historical frequency record data is the frequency-related data recorded at all frequency monitoring points in the grid of the grid-connected wind power system in the past period of time. These data reflect the frequency changes of each monitoring point in the system at different times in the past.

[0100] In this embodiment, the abnormal frequency fluctuation record refers to the relevant record of the fluctuation situation that deviates from the normal or expected frequency range monitored by each frequency monitoring point in the grid-connected wind power system. These records usually contain information such as the time when the frequency fluctuation occurs, the amplitude of the fluctuation, and the duration of the fluctuation.

[0101] In this embodiment, the duration of abnormal frequency fluctuation refers to the duration of abnormal frequency fluctuation at a certain frequency monitoring point in the grid-connected wind power system.

[0102] For example, the period from the moment when the abnormal frequency fluctuation is detected to the moment when the frequency returns to normal is the duration of abnormal frequency fluctuation, which is an important parameter for evaluating the severity and impact of abnormal frequency fluctuation.

[0103] In this embodiment, the continuous value record of abnormal frequency fluctuation refers to the specific frequency value recorded for each frequency monitoring point in the grid-connected wind power system during the period of continuous abnormal frequency fluctuation. These values ​​can reflect the change and amplitude of the frequency during the abnormal fluctuation period.

[0104] In this embodiment, the key coefficient of the frequency monitoring point is a specific value used to measure the relative importance or influence of the frequency monitoring point in the grid-connected wind power system. It may comprehensively consider multiple factors such as the location of the monitoring point, the importance of the connected equipment or line, and the degree of influence on the overall stability of the system.

[0105] In this embodiment, the importance of the frequency monitoring point refers to a quantitative index obtained by a certain calculation method by combining the key coefficient of each frequency monitoring point, the duration of all abnormal frequency fluctuations of the monitoring point within a preset period, and the continuous numerical records, etc., to indicate the importance of the monitoring point to the entire grid-connected wind power system. Frequency monitoring points with higher importance may require closer attention and more timely control measures to ensure the stability and normal operation of the system.

[0106] In this embodiment, the importance threshold refers to a pre-set critical value for distinguishing the importance of frequency monitoring points, and is usually set based on comprehensive consideration and trade-offs of multiple factors such as system operation requirements, stability requirements, and resource allocation strategies.

[0107] In this embodiment, the current preset monitoring period is the current preset monitoring period.

[0108] The beneficial effects of the above technologies are: being able to accurately identify and record abnormal frequency fluctuations and discover potential problems in a timely manner. Clarifying the duration and value of abnormal frequency fluctuations provides a detailed basis for in-depth analysis and response measures. Determining key coefficients and importance to achieve scientific evaluation and classification of frequency monitoring points. Distinguishing between primary and secondary frequency monitoring points facilitates targeted allocation of monitoring resources and the adoption of regulatory measures. Overall, the system's monitoring and management capabilities for frequency fluctuations are improved, and the stability and reliability of system operation are enhanced. By conducting in-depth analysis of the historical frequency record data of frequency monitoring points within the preset period of the grid-connected wind power system, determining abnormal fluctuation records, duration periods and continuous value records, calculating key coefficients and importance, and then distinguishing between primary and secondary frequency monitoring points, it is helpful to achieve accurate monitoring and classified management of system frequency, and provide strong support for ensuring stable system operation, optimizing resource allocation and improving power quality.

[0109] Embodiment 6:

[0110] On the basis of Example 5, the frequency optimization control method of the grid-connected wind power system of the grid-connected wind power system calculates the importance of each frequency monitoring point based on the key coefficient of each frequency monitoring point in the grid of the grid-connected wind power system and all frequency abnormal fluctuation duration periods and all frequency abnormal fluctuation duration numerical records within a preset period, including:

[0111]

[0112] Where d is the importance of the frequency monitoring point, δ is the key coefficient of the frequency monitoring point, n is the total number of all frequency abnormal fluctuation duration periods of the frequency monitoring point within the preset period, and t isis the starting time of the ith abnormal frequency fluctuation duration period at the frequency monitoring point within the preset period, t ie is the end time of the duration of the ith abnormal frequency fluctuation at the frequency monitoring point within the preset time period, t0 is the current time, t s·min The earliest time among the starting times of all frequency abnormal fluctuation duration periods at the frequency monitoring point within the preset time period, FRQ imax FRQ is the maximum frequency value recorded in the continuous numerical record of the ith frequency abnormal fluctuation at the frequency monitoring point within the preset period. imin FRQ is the minimum frequency value recorded in the continuous numerical record of the ith frequency abnormal fluctuation at the frequency monitoring point within the preset period. 0·lim It is the maximum allowable frequency value of the frequency monitoring point.

[0113] In this embodiment, the maximum allowable frequency value of the frequency monitoring point refers to the upper limit value that the frequency measured by the monitoring point cannot exceed during the operation of the power grid. For example, in my country's power system, the maximum allowable frequency value usually set may be 50.5Hz. This means that under normal operation, the frequency monitored by the frequency monitoring point should not be higher than 50.5Hz. Assume that a specific frequency monitoring point is located in a substation in a large industrial park, and its maximum allowable frequency value is set to 50.2Hz. If the monitored frequency exceeds this value, it may indicate that an abnormal situation has occurred in the power grid, such as excess power generation, a sudden and substantial reduction in load, etc., and corresponding control measures need to be taken to restore normal frequency.

[0114] The beneficial effects of the above technology are: calculating the importance of each frequency monitoring point in the grid-connected wind power system through a specific formula helps to more accurately understand the frequency conditions at different locations in the power grid. Taking into account multiple factors such as the key coefficient of the frequency monitoring point, the duration of all abnormal frequency fluctuations, and the continuous numerical recording, the importance of the frequency monitoring point can be comprehensively evaluated. It can provide a basis for the frequency optimization control of the grid-connected wind power system, which helps to improve the stability and reliability of the power grid.

[0115] Embodiment 7:

[0116] On the basis of Example 4, the frequency optimization control method of the grid-connected wind power system, based on the frequencies of all primary frequency monitoring points and all secondary frequency monitoring points in the grid of the grid-connected wind power system, obtains the real-time node frequency distribution data of the grid-connected wind power system, including:

[0117] Based on the acquired frequencies of all main frequency monitoring points and all secondary frequency monitoring points in the power grid of the grid-connected wind power system, dynamic node frequency distribution data of the grid-connected wind power system is generated;

[0118] The dynamic node frequency distribution data of the grid-connected wind power system is sampled as a whole according to time slices to obtain the real-time node frequency distribution data of the grid-connected wind power system.

[0119] In this embodiment, the dynamic node frequency distribution data of the grid-connected wind power system refers to a series of data that can reflect the frequency changes of each node in the grid-connected wind power system over time.

[0120] These data show how the frequency values ​​at each monitoring node in the system fluctuate and change at different times. It is not just the frequency value of a single node at a certain moment, but covers the frequency changes of all monitoring nodes over a period of time, thus showing the dynamic distribution characteristics of the frequency of the entire system.

[0121] For example, assuming there are 10 monitoring nodes in the system and frequency data is collected every 5 minutes within 1 hour, then the "dynamic node frequency distribution data" will include the frequency values ​​of these 10 nodes at these 12 time points, forming a multi-dimensional, time-varying data set that can clearly show the dynamic change trends, mutual relationships and overall distribution patterns of the frequencies of different nodes in the system.

[0122] The beneficial effects of the above technologies are: accurately presenting the dynamic changes of the frequency of each node in the system, which is conducive to timely detection of abnormal fluctuations and trends. Covering multi-node and multi-time point data, it can comprehensively analyze the overall frequency distribution characteristics of the system. Provide a detailed and comprehensive basis for system optimization and control strategy formulation. Clearly showing the relationship between the frequencies of different nodes is helpful for in-depth research on the interaction within the system. Help improve the accuracy and comprehensiveness of system monitoring and ensure stable and reliable operation of the system. Clearly defining the dynamic node frequency distribution data helps to fully and deeply understand the change law of each node frequency over time in the grid-connected wind power system, and provides a rich and accurate information basis for the analysis, monitoring, optimization and control of the system, thereby improving the stability, reliability and efficiency of system operation.

[0123] Embodiment 8:

[0124] On the basis of Example 3, a frequency optimization control method for a grid-connected wind power system is provided to obtain real-time node voltage distribution data of the grid-connected wind power system, including:

[0125] Obtain all voltage monitoring points in the grid of the grid-connected wind power system;

[0126] The voltages of all voltage monitoring points in the power grid of the grid-connected wind power system are acquired in real time, and based on the voltages of all voltage monitoring points in the power grid of the grid-connected wind power system acquired in real time, real-time node voltage distribution data of the grid-connected wind power system is generated in real time.

[0127] In this embodiment, the voltage monitoring point is a specific location specially selected in the power grid of the grid-connected wind power system for measuring and monitoring voltage.

[0128] In this embodiment, the voltage at the voltage monitoring point refers to the voltage value actually measured at these selected monitoring points. Assume that we have a grid-type wind power grid-connected system, which includes wind farms, substations, transmission lines and user terminals. At the exit of the wind farm, a voltage monitoring point will be set up. For example, the monitored voltage is 110 kV. This monitoring point allows us to understand whether the voltage output by the wind farm is stable and whether it meets the grid connection requirements.

[0129] For example, the voltage monitoring points set up at the grid connection point of a wind farm, important substation busbars, etc., the specific voltage values ​​obtained at a specific time by professional measuring equipment, such as 220 kV, 10 kV, etc., are the "voltage at the voltage monitoring point". Specifically, what is monitored is the line voltage (for example, the voltage between two phase lines) or the phase voltage (for example, the voltage between a phase line and a neutral line) at the location of the monitoring point.

[0130] For example, the voltage monitoring point set up at the distribution box for residential electricity usually monitors the phase voltage, which is about 220 volts; while the monitoring point at the substation bus may monitor the line voltage, such as 10 kV, 35 kV, etc.

[0131] The beneficial effects of the above technology are: it can comprehensively and timely grasp the voltage situation of the grid-connected wind power system, provide an accurate basis for the optimization and regulation of the system, and thus effectively ensure the stable and efficient operation of the grid-connected wind power system.

[0132] Embodiment 9:

[0133] Based on Example 2, a frequency optimization control method for a grid-connected wind power system, S2: recording a grid disturbance amount within a preset monitoring period, includes:

[0134] S201: Based on the real-time node voltage distribution data and the real-time node frequency distribution data of the grid-connected wind power system, identifying the voltage disturbance record and the frequency disturbance record occurring within a preset monitoring period;

[0135] S202: Obtaining power grid fault disturbance records within a preset monitoring period;

[0136] Among them, the power grid disturbance includes voltage disturbance records, frequency disturbance records and power grid fault disturbance records.

[0137] In this embodiment, based on the real-time node voltage distribution data and the real-time node frequency distribution data of the grid-connected wind power system, the voltage disturbance record and the frequency disturbance record occurring in the preset monitoring period are identified, including:

[0138] By using the relevant data on real-time node voltage and frequency distribution in the grid-connected wind power system, abnormal changes in voltage and frequency can be discovered and confirmed within a pre-set monitoring period, and recorded.

[0139] For example, the preset monitoring period is one day. During this day, through the analysis of real-time node voltage distribution data, if it is found that the voltage of a certain node suddenly drops from the normal 220 volts to 180 volts between 2 pm and 3 pm, and then returns to normal, this is identified as a voltage disturbance and recorded.

[0140] Similarly, for real-time node frequency distribution data, if it is monitored that the frequency suddenly increases from the standard 50Hz to 51Hz between 8 and 9 pm and lasts for a period of time, this will also be identified as a frequency disturbance and recorded.

[0141] In this way, abnormal conditions in the system can be detected in time so that appropriate measures can be taken to ensure the stable operation of the power grid.

[0142] In this embodiment, the power grid fault disturbance record refers to information recorded on abnormal states caused by various fault conditions in the power grid within a preset monitoring period.

[0143] For example, a short circuit occurs in a transmission line in a power grid, causing a sharp increase in current and a significant drop in voltage. This fault event and its related data (such as the time, location, type of fault, changes in voltage and current, etc.) will be recorded to form a power grid fault disturbance record.

[0144] For example, if an internal fault occurs in a transformer, causing its output voltage to be abnormal, or a key power equipment is suddenly damaged, causing a partial power outage in the grid, the abnormal information generated by these faults will be recorded in detail and are all considered grid fault disturbance records.

[0145] The beneficial effects of the above technology are: based on the real-time node voltage and frequency distribution data, the voltage and frequency disturbance records within the preset monitoring period can be accurately identified, and the monitoring accuracy of the system disturbance can be improved. The grid fault disturbance records within the preset monitoring period can be obtained, which comprehensively covers various types of grid disturbance conditions. The range of grid disturbance quantity is clarified, including voltage disturbance records, frequency disturbance records and grid fault disturbance records, which provides a clear basis for subsequent analysis and processing. It helps to deeply understand the operating status of the grid-connected wind power system within the preset monitoring period and discover potential problems in time. It provides key data support for the optimization, maintenance and stable operation of the system, and ensures the reliable operation of the system. Through these steps, various types of grid disturbance conditions in the grid-connected wind power system within the preset monitoring period can be comprehensively and accurately obtained, providing strong support and guarantee for subsequent fault analysis, system optimization and stable operation.

[0146] Embodiment 10:

[0147] The present invention provides a frequency optimization control system for a grid-connected wind power system, which is applied to the frequency optimization control method for a grid-connected wind power system described in any one of embodiments 1 to 9, referring to Figure 2 ,include:

[0148] The grid status monitoring module is used to monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system;

[0149] A power grid disturbance recording module is used to record the power grid disturbance amount within a preset monitoring period;

[0150] The optimization scheme determination module is used to input the real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of the grid-connected wind power system into the adaptive frequency optimization control model to obtain the frequency optimization control scheme.

[0151] The beneficial effects of the above technology are: real-time monitoring of the grid status and node frequency distribution data of the grid-connected wind power system helps to timely understand the system operation status and provide accurate basic information for subsequent control and optimization. Recording the grid disturbance within the preset monitoring period can better analyze the interference to the system and provide a basis for frequency optimization control. By inputting the real-time grid status, real-time grid frequency and grid disturbance into the adaptive frequency optimization control model, a targeted frequency optimization control solution can be obtained to improve the frequency stability and reliability of the system. It helps to improve the overall performance of the grid-connected wind power system, better adapt to changes and interference in the power grid, and ensure the safe and stable operation of the power system.

[0152] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A frequency optimization control method for a grid-connected wind power system, characterized in that: include: S1: monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system; S2: Record the power grid disturbance amount within the preset monitoring period; S3: The real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of the grid-connected wind power system are input into the adaptive frequency optimization control model to obtain a frequency optimization control scheme.

2. The frequency optimization control method of the grid-connected wind power system according to claim 1 is characterized in that: S1: Monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system, including: Determine the real-time grid flow distribution and real-time node voltage distribution data of the grid-connected wind power system as the real-time grid state of the grid-connected wind power system; Obtain real-time node frequency distribution data of the grid-connected wind power system.

3. The frequency optimization control method of the grid-connected wind power system according to claim 2 is characterized in that: Determine the real-time grid flow distribution and real-time node voltage distribution data of the grid-connected wind power system, including: Determine the real-time grid reactive power flow distribution and the real-time grid active power flow distribution of the grid-building type wind power grid-connected system as the real-time grid flow distribution of the grid-building type wind power grid-connected system; Obtain real-time node voltage distribution data of the grid-connected wind power system.

4. The frequency optimization control method of the grid-connected wind power system according to claim 2, characterized in that: Obtain real-time node frequency distribution data of the grid-connected wind power system, including: Obtain all frequency monitoring points in the power grid of the grid-connected wind power system; Among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the main frequency monitoring points and all the secondary frequency monitoring points of the current preset monitoring period are screened out; Set the monitoring intervals for all primary frequency monitoring points and the monitoring intervals for all secondary frequency monitoring points; Based on the monitoring intervals of all the main frequency monitoring points, the frequencies of all the main frequency monitoring points in the grid of the grid-connected wind power system are obtained. Meanwhile, based on the monitoring intervals of all the secondary frequency monitoring points, the frequencies of all the secondary frequency monitoring points in the grid of the grid-connected wind power system are obtained. Based on the acquired frequencies of all primary frequency monitoring points and all secondary frequency monitoring points in the power grid of the grid-connected wind power system, real-time node frequency distribution data of the grid-connected wind power system is obtained.

5. The frequency optimization control method of the grid-connected wind power system according to claim 4 is characterized in that: Among all the frequency monitoring points in the grid of the grid-connected wind power system, all the main frequency monitoring points and all the secondary frequency monitoring points in the current preset monitoring period are screened out, including: In the historical frequency record data of all frequency monitoring points in the power grid of the grid-connected wind power system within a preset period, all abnormal frequency fluctuation records of each frequency monitoring point within the preset period are determined; Based on all abnormal frequency fluctuation records of each frequency monitoring point within a preset period, all abnormal frequency fluctuation duration periods and all abnormal frequency fluctuation duration value records of each frequency monitoring point within the preset period are determined; Determine the key coefficients of each frequency monitoring point in the grid of the grid-connected wind power system; Based on the key coefficient of each frequency monitoring point in the grid of the grid-connected wind power system and all frequency abnormal fluctuation duration periods and all frequency abnormal fluctuation duration numerical records within a preset period, the importance of each frequency monitoring point is calculated; Among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the frequency monitoring points whose importance is not less than the importance threshold are regarded as all the main frequency monitoring points of the current preset monitoring period. At the same time, among all the frequency monitoring points in the power grid of the grid-connected wind power system, all the frequency monitoring points whose importance is less than the importance threshold are regarded as all the secondary frequency monitoring points of the current preset monitoring period.

6. The frequency optimization control method of the grid-connected wind power system according to claim 5, characterized in that: Based on the key coefficients of each frequency monitoring point in the grid of the grid-connected wind power system and all frequency abnormal fluctuation duration periods and all frequency abnormal fluctuation duration numerical records within a preset period, the importance of each frequency monitoring point is calculated, including: Where d is the importance of the frequency monitoring point, δ is the key coefficient of the frequency monitoring point, n is the total number of all frequency abnormal fluctuation duration periods of the frequency monitoring point within the preset period, and t is is the starting time of the ith abnormal frequency fluctuation duration period at the frequency monitoring point within the preset period, t ie is the end time of the duration of the ith abnormal frequency fluctuation at the frequency monitoring point within the preset time period, t0 is the current time, t s·min The earliest time among the starting times of all frequency abnormal fluctuation duration periods at the frequency monitoring point within the preset time period, FRQ imax FRQ is the maximum frequency value recorded in the continuous numerical record of the ith frequency abnormal fluctuation at the frequency monitoring point within the preset period. imin FRQ is the minimum frequency value recorded in the continuous numerical record of the ith frequency abnormal fluctuation at the frequency monitoring point within the preset period. 0·lim It is the maximum allowable frequency value of the frequency monitoring point.

7. The frequency optimization control method of the grid-connected wind power system according to claim 4, characterized in that: Based on the frequencies of all main frequency monitoring points and all secondary frequency monitoring points in the grid of the grid-connected wind power system, the real-time node frequency distribution data of the grid-connected wind power system is obtained, including: Based on the acquired frequencies of all main frequency monitoring points and all secondary frequency monitoring points in the power grid of the grid-connected wind power system, dynamic node frequency distribution data of the grid-connected wind power system is generated; The dynamic node frequency distribution data of the grid-connected wind power system is sampled as a whole according to time slices to obtain the real-time node frequency distribution data of the grid-connected wind power system.

8. The frequency optimization control method of the grid-connected wind power system according to claim 3, characterized in that: Obtain real-time node voltage distribution data of the grid-connected wind power system, including: Obtain all voltage monitoring points in the grid of the grid-connected wind power system; The voltages of all voltage monitoring points in the power grid of the grid-connected wind power system are acquired in real time, and based on the voltages of all voltage monitoring points in the power grid of the grid-connected wind power system acquired in real time, real-time node voltage distribution data of the grid-connected wind power system is generated in real time.

9. The frequency optimization control method of the grid-connected wind power system according to claim 2, characterized in that: S2: Record the power grid disturbance within the preset monitoring period, including: S201: Based on the real-time node voltage distribution data and the real-time node frequency distribution data of the grid-connected wind power system, identifying the voltage disturbance record and the frequency disturbance record occurring within a preset monitoring period; S202: Obtaining power grid fault disturbance records within a preset monitoring period; Among them, the power grid disturbance includes voltage disturbance records, frequency disturbance records and power grid fault disturbance records.

10. A frequency optimization control system for a grid-connected wind power system, characterized in that: The frequency optimization control method applied to the grid-connected wind power system according to any one of claims 1 to 9 comprises: The grid status monitoring module is used to monitor the real-time grid status and real-time node frequency distribution data of the grid-connected wind power system; A power grid disturbance recording module is used to record the power grid disturbance amount within a preset monitoring period; The optimization scheme determination module is used to input the real-time grid status, real-time grid frequency and grid disturbance amount within a preset monitoring period of the grid-connected wind power system into the adaptive frequency optimization control model to obtain the frequency optimization control scheme.

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