Adaptive power balance control method for wind-solar hybrid power generation system

Abstract

The present invention provides an adaptive power balance control method for a wind-solar complementary power generation system, which relates to the technical field of power balance control, including: obtaining a first wind-solar complementary power generation unit in the wind-solar complementary power generation system, and performing load monitoring to obtain first wind-solar load monitoring information; introducing a load evaluation function to evaluate and analyze the first wind-solar load monitoring information to obtain a first predicted power generation load; if the first predicted power generation load is not within a predetermined power generation load threshold, issuing an adaptive control instruction; activating a power stabilizer, and generating a first power balance control decision for the first wind-solar complementary power generation unit; and performing adaptive power balance control processing on the first wind-solar complementary power generation unit according to the first power balance control decision. The present invention solves the technical problem that the prior art is often difficult to accurately balance the relationship between power generation and grid load under rapidly changing environmental conditions, and is unable to adjust the power control strategy in a timely manner, resulting in energy waste or insufficient power supply.

Description

Technical Field

[0001] The present invention relates to the technical field of power balance control, and in particular to an adaptive power balance control method for a wind-solar hybrid power generation system. Background Art

[0002] In the field of renewable energy, especially in wind and photovoltaic power generation systems, a core challenge is how to effectively manage and utilize the volatility and intermittency of these energy sources. The availability of wind and photovoltaic power is affected by a variety of environmental factors, such as wind speed, solar irradiation, etc. The unpredictability of these factors leads to fluctuations in power generation, which in turn affects the stability and power generation efficiency of the power grid. However, traditional power generation system management methods often rely on static scheduling strategies, which may not be flexible enough when faced with high variations in energy output. In addition, existing control systems often control wind power and photovoltaic systems independently, lacking an integrated approach to coordinate the complementary advantages of these two energy sources and optimize the energy output and stability of the entire system. Summary of the invention

[0003] This application provides an adaptive power balancing control method for a wind-solar complementary power generation system, aiming to solve the technical problems that the prior art often finds it difficult to accurately balance the relationship between power generation and grid load under rapidly changing environmental conditions, and is unable to adjust the power control strategy in a timely manner, resulting in energy waste or insufficient power supply.

[0004] The present application discloses an adaptive power balancing control method for a wind-solar complementary power generation system, the method comprising: obtaining a first wind-solar complementary power generation unit in the wind-solar complementary power generation system, and performing load monitoring on the first wind-solar complementary power generation unit to obtain first wind-solar load monitoring information; introducing a load evaluation function to evaluate and analyze the first wind-solar load monitoring information to obtain a first predicted power generation load; if the first predicted power generation load is not within a predetermined power generation load threshold, issuing an adaptive control instruction; activating a power stabilizer based on the adaptive control instruction, and generating a first power balancing control decision for the first wind-solar complementary power generation unit through the power stabilizer; and performing adaptive power balancing control processing on the first wind-solar complementary power generation unit according to the first power balancing control decision.

[0005] One or more technical solutions provided in this application have at least the following beneficial effects:

[0006] By monitoring the load of the first wind-solar complementary generator set in the wind-solar complementary power generation system, real-time first wind-solar load monitoring information is obtained, which allows the system to make instant adjustments based on actual power generation and load conditions, thereby enhancing the system's ability to respond to fluctuations; a load evaluation function is introduced to evaluate and analyze the monitoring information to generate a first predicted power generation load. This prediction capability enables the power generation system to proactively adjust the power generation plan and optimize energy distribution; when the predicted power generation load does not meet the predetermined power generation load threshold, an adaptive control instruction is automatically issued. This adaptive control strategy can automatically adjust the system operation based on real-time data and prediction results, thereby increasing the flexibility and stability of the system; based on the adaptive control instruction, the power stabilizer is activated and a power balance control decision is generated, which enables the system to effectively manage the output of the generator set, reduce power fluctuations, and improve the energy efficiency and reliability of the overall system; based on the power balance control decision, an adaptive power balance control process is implemented on the wind-solar complementary generator set, thereby ensuring that the power generation system can maintain efficient and stable operation under changing environmental and load conditions, thereby optimizing resource utilization.

[0007] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A schematic flow chart of an adaptive power balancing control method for a wind-solar hybrid power generation system is provided for an embodiment of the present application.

[0009] Figure 2 A schematic diagram of a process for obtaining a first predicted power generation load in an adaptive power balancing control method for a wind-solar hybrid power generation system is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0010] The embodiment of the present application provides an adaptive power balancing control method for a wind-solar hybrid power generation system, thereby solving the technical problem that the prior art often finds it difficult to accurately balance the relationship between power generation and grid load under rapidly changing environmental conditions, and is unable to adjust the power control strategy in a timely manner, resulting in energy waste or insufficient power supply.

[0011] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0012] like Figure 1 As shown, the embodiment of the present application provides an adaptive power balance control method for a wind-solar hybrid power generation system, the method comprising:

[0013] A first wind-solar complementary generator set in the wind-solar complementary power generation system is obtained, and load monitoring is performed on the first wind-solar complementary generator set to obtain first wind-solar load monitoring information.

[0014] In the wind-solar complementary power generation system, there is a joint power generation system composed of multiple wind turbines and photovoltaic units. The first wind-solar complementary power generation unit is randomly selected as the analysis object. The unit consists of at least one wind turbine and one photovoltaic unit, and can use wind energy and solar energy to generate electricity at the same time.

[0015] The purpose of load monitoring is to obtain real-time power output data, load demand data, equipment operating status and other information related to the selected first wind-solar hybrid generator set. These data are helpful for analyzing the load fluctuation, power generation capacity and whether the system load demand is met. In order to realize load monitoring, sensors, smart meters, power metering devices and other equipment are deployed to collect the working status of wind turbines and photovoltaic units in real time. For example, wind turbines can monitor wind speed, wind turbine power and load changes through wind speed sensors; photovoltaic units can obtain photovoltaic power output and load changes through light sensors, inverters and other equipment.

[0016] After the load monitoring information is collected, the collected data constitutes the first wind-solar load monitoring information, which includes the operating status, real-time load demand, power generation and other related data of the first wind-solar hybrid generator set. These monitoring information will be used for subsequent load assessment, power forecasting and system regulation to ensure the stable operation and efficient energy output of the wind-solar hybrid power generation system.

[0017] A load evaluation function is introduced to evaluate and analyze the first wind and solar load monitoring information to obtain a first predicted power generation load.

[0018] The load assessment function is used to assess the power supply load of the wind-solar complementary power generator set. The purpose of this function is to predict the power generation load through the input monitoring data, so as to assess the current and future power supply status of the system. Specifically, the power supply load data and plant load data in the first wind-solar load monitoring information are extracted and input into the load assessment function. The load assessment function analyzes these input data and calculates the first predicted power generation load, which is an estimate showing the possible power generation capacity of the system in the future.

[0019] If the first predicted power generation load is not within a predetermined power generation load threshold, an adaptive control instruction is issued.

[0020] The first predicted power generation load is compared with the predetermined power generation load threshold, which is set based on grid demand, safety standards and operating efficiency. If the predicted power generation load is lower than the threshold, it indicates that the power supply capacity is insufficient and it is necessary to increase power generation or take energy-saving measures. If the predicted power generation load is higher than the threshold, it will cause overload or energy waste, and it is necessary to adjust to reduce power generation or increase energy storage. According to the comparison result between the predicted power generation load and the threshold, the corresponding adaptive control instructions are automatically issued, including adjusting the operating parameters of the generator set, starting the backup power supply, adjusting the status of the energy storage device, etc., which are used to respond to the actual operating conditions of the system in real time to ensure the stability and efficiency of the power supply.

[0021] A power stabilizer is activated based on the adaptive control instruction, and a first power balancing control decision of the first wind-solar complementary generator set is generated through the power stabilizer.

[0022] The power stabilizer is used to adjust and stabilize power fluctuations in the power generation system, especially in the wind-solar hybrid system. Due to the instability of wind speed and solar radiation, the power output may fluctuate significantly. The power stabilizer mitigates these fluctuations by adjusting the power generation output or enabling the energy storage system to maintain the stability of the power grid. The power stabilizer is automatically activated according to the adaptive control instruction. After the power stabilizer is activated, the first power balance control decision is generated according to the current power demand and supply situation. This decision includes determining how much power needs to be stabilized and the selected stabilization strategy, such as power regulation, demand response, and energy storage use.

[0023] Adaptive power balancing control processing is performed on the first wind-solar complementary generator set according to the first power balancing control decision.

[0024] Adaptive power balance control processing refers to dynamically adjusting the control strategy based on real-time data to cope with changes in the environment and operating status, with the aim of ensuring that the output power of the generator set matches the needs of the power grid, thereby optimizing the operating efficiency and reliability of the entire system. According to the first power balance control decision, the decision is executed through control software and hardware. The control execution process involves adjusting the converter settings, activating or adjusting the energy storage system, modifying the blade angle of the wind turbine or the tilt angle of the photovoltaic panel, etc. Through adaptive control and power leveling technology, it can effectively cope with the instability of wind power and photovoltaic power generation, ensure the stable operation of the power grid and the reliability of power supply, and ensure that the power generation system can maintain an efficient and stable operating state under changing environmental conditions.

[0025] Furthermore, if Figure 2 As shown, a load evaluation function is introduced to evaluate and analyze the first wind and solar load monitoring information to obtain a first predicted power generation load, including:

[0026] Extract first load monitoring information of the first wind turbine group in the first wind-solar complementary generator group, wherein the first load monitoring information includes first power supply load data and first plant load data; extract second load monitoring information of the first photovoltaic group in the first wind-solar complementary generator group, wherein the second load monitoring information includes second power supply load data and second plant load data; perform load-weighted evaluation on the first power supply load data, the first plant load data, the second power supply load data and the second plant load data according to the load evaluation function to obtain the first predicted power generation load.

[0027] The first wind-solar complementary generator set includes a first wind turbine set and a first photovoltaic unit. In the first wind-solar load monitoring information, the first load monitoring information is extracted with the first wind turbine set as an index, wherein the first power supply load data reflects the actual load situation of the first wind turbine set providing electricity to the power grid or users, including the total output power of the generator set, time series power data, etc., which are used to evaluate the operating efficiency and power supply capacity of the generator set; the first plant load data is the power load required for the operation of the first wind turbine set itself. Plant power is usually used to drive various equipment inside the generator set, such as cooling system, control system, lighting, etc. Monitoring this part of the load is used to evaluate the internal energy efficiency and operating cost of the wind turbine set.

[0028] In the first wind and solar load monitoring information, the second load monitoring information is extracted with the second wind turbine set as the index, wherein the second power supply load data reflects the actual load situation of the second wind turbine set providing electricity to the power grid or users; the second plant load data is the power load required for the second wind turbine set's own operation.

[0029] The importance and reliability of different energy sources are combined to weight various data. For example, if the photovoltaic capacity is more stable in a specific period of time, its output will be given a higher weight. According to the load assessment function, various load data are weighted and calculated to obtain the first predicted power generation load, which predicts the power supply capacity of the system in the future. This supports the prediction of future power demand and improves the system's adaptability and response efficiency to unstable factors.

[0030] Furthermore, if the first predicted power generation load is not within a predetermined power generation load threshold, issuing an adaptive control instruction includes:

[0031] When the first predicted power generation load is greater than the predetermined power generation load threshold, an adaptive verification instruction is issued; based on the adaptive verification instruction, first real-time monitoring information of the first wind-solar complementary power generator group is obtained, and the first real-time monitoring information is used as input data of the power generation prediction model; the first real-time monitoring information is predicted and analyzed by the power generation prediction model to obtain a first predicted power generation; when the first predicted power generation is not within the predetermined power generation threshold, the adaptive control instruction is issued.

[0032] When the first predicted generation load is greater than a predetermined generation load threshold, an adaptive verification instruction is issued, which is intended to initiate a check and verification process to determine the cause of exceeding the threshold and to evaluate whether adjustment measures need to be taken.

[0033] Based on the adaptive verification instruction, the first real-time monitoring information is obtained from the first wind-solar hybrid generator set, including but not limited to real-time power output, environmental conditions (such as wind speed, solar irradiance), unit operation status, etc. These data are collected in real time by sensors and monitoring systems in the unit. The collected first real-time monitoring information is used as input data and sent to the power generation prediction model. This model can be built based on historical data and machine learning algorithms to predict short-term or long-term power generation and system behavior. The injection of real-time data enables the model to adjust the prediction according to the latest operating conditions, thereby improving the accuracy and response speed of the prediction.

[0034] The power generation prediction model analyzes the first real-time monitoring information and calculates the expected first predicted power generation. This calculation result is based on the analysis of known equipment performance, historical data and environmental factors, and indicates the amount of electricity that the wind-solar complementary generator set is expected to generate under given conditions and time frames.

[0035] Compare the first predicted power generation with the predetermined power generation threshold. The threshold is set according to the grid demand, system capacity and safety standards to ensure that the system will not be overloaded or under-capacity. If the first predicted power is lower than the threshold, it means that the power supply will be insufficient for a period of time in the future, and measures need to be taken to increase power generation or adjust consumption; if the first predicted power exceeds the threshold, it may cause the system to be overloaded, and it is necessary to reduce power generation or increase power storage. According to the comparison results, the corresponding adaptive control instructions are automatically issued, including adjusting the output power of the generator set, activating or adjusting the energy storage system, and starting demand response measures.

[0036] Through the above steps, the wind-solar hybrid power generation system can dynamically adjust its operating status to cope with changing environmental conditions and grid demands. This adaptive control mechanism helps to improve the system's adaptability to unstable factors and overall operating efficiency.

[0037] Furthermore, performing prediction analysis on the first real-time monitoring information by using the power generation prediction model to obtain a first predicted power generation includes:

[0038] Extract the first real-time weather information from the first real-time monitoring information; extract the first monitoring information of the first wind turbine group from the first real-time monitoring information; extract the second monitoring information of the first photovoltaic group from the first real-time monitoring information; use the first real-time weather information and the first monitoring information as input data of the wind power prediction channel of the power generation prediction model; obtain the first predicted power of the first wind turbine group through the wind power prediction channel; use the first real-time weather information and the second monitoring information as input data of the photovoltaic power prediction channel of the power generation prediction model; obtain the second predicted power of the first photovoltaic group through the photovoltaic power prediction channel; take the sum of the first predicted power and the second predicted power as the first predicted power generation power.

[0039] Extract the first real-time weather information from the first real-time monitoring information. Weather information is crucial for the performance evaluation of wind power and photovoltaic power generation systems because their output is directly affected by weather conditions, including wind speed, solar radiation, temperature, humidity, etc. These data can be collected in real time using weather monitoring stations or meteorological sensors integrated with the system.

[0040] The first monitoring information of the first wind turbine includes the power output, rotation speed, wind rotor blade angle, gearbox temperature, etc. of the first wind turbine. These are key indicators for evaluating the performance and health status of the wind turbine. This information is obtained through real-time monitoring by sensors installed on the wind turbine.

[0041] The second monitoring information of the first photovoltaic unit includes the current and voltage output of the photovoltaic panel, etc. This information is used to evaluate the efficiency and output performance of the photovoltaic panel. This information is collected using the built-in monitoring tools of the photovoltaic system, such as sensors in the inverter.

[0042] The first real-time weather information is integrated with the first monitoring information and used together as input data for the wind power prediction channel in the power generation prediction model, because these parameters directly affect the power generation efficiency and output power of the wind turbine. The wind power prediction channel is built based on historical data and machine learning algorithms to analyze the input weather and monitoring information and predict the power generation that the wind turbine may achieve under current and upcoming weather conditions.

[0043] After analysis and prediction by the wind power prediction channel, the first predicted power of the first wind turbine is output. The first predicted power is the estimated power generation of the first wind turbine in the upcoming period, which is used for scheduling and grid operation management, especially in areas where wind power generation is the main power generation mode.

[0044] The first real-time weather information is integrated with the second monitoring information as input data for the photovoltaic power prediction channel in the power generation prediction model, because these parameters directly affect the power output of the photovoltaic panel. The photovoltaic power prediction channel is built based on historical data and machine learning algorithms to analyze the input weather and monitoring information and predict the power generation that the photovoltaic unit may achieve under current and upcoming weather conditions.

[0045] After analysis and prediction of the photovoltaic power prediction channel, the second predicted power of the first photovoltaic unit is output. The second predicted power is the estimated power output of the first photovoltaic unit in the upcoming period, which is used for scheduling and grid operation management, especially in areas where photovoltaic power generation is the main power generation mode.

[0046] The first predicted power is added to the second predicted power, and the result of the addition is used as the first predicted power generation power. This addition operation provides a total power generation power forecast for the entire first wind-solar complementary power generator set within the predicted time period, which is a comprehensive evaluation of the total energy output.

[0047] Further, activating a power stabilizer based on the adaptive control instruction, and generating a first power balancing control decision of the first wind-solar hybrid generator set through the power stabilizer, includes:

[0048] The first predicted power is compared with the second predicted power to obtain a power comparison result; according to the power comparison result, if the first predicted power is greater than the second predicted power, the first wind turbine unit is used as a target control unit; according to the power comparison result, if the first predicted power is less than the second predicted power, the first photovoltaic unit is used as a target control unit; based on the adaptive control instruction, the power stabilizer is activated, and the power stabilizer generates a target power balance control decision for the target control unit; and the target power balance control decision is used as the first power balance control decision.

[0049] The first predicted power is compared with the second predicted power to determine which power generation source has a greater contribution, and the comparison is implemented by a simple numerical comparison.

[0050] If the first predicted power of the first wind turbine group is greater than the second predicted power of the first photovoltaic group, the first wind turbine group is selected as the target control group. That is, since the predicted output of the first wind turbine group is higher, its contribution to the entire system is also greater, so it becomes the focus of control and can more effectively manage the total output of the system.

[0051] On the contrary, if the first predicted power of the first wind turbine unit is less than the second predicted power of the first photovoltaic unit, the first photovoltaic unit is selected as the target control unit. That is, since the first photovoltaic unit shows a higher predicted output in comparison, the control focus is shifted to the photovoltaic unit, which can optimize energy production under conditions of sufficient sunshine and improve the energy efficiency of the system.

[0052] The power stabilizer is used to adjust the power output of the generator set to cope with power fluctuations and maintain grid stability. It optimizes the operation of the generator set by smoothing the power peak or filling the power valley. The power stabilizer is activated based on the adaptive control instruction, instructing it to adjust the power output of the target unit according to the current power demand and forecast results. The power stabilizer analyzes the real-time operating data of the target unit and the grid demand, and generates specific target power balance control decisions, such as adjusting the generated power, modifying the operating parameters, etc., to achieve the best power supply and demand matching.

[0053] Implementing the target power balance control decision as the first power balance control decision in the entire wind-solar hybrid power generation system means that the control decision will directly affect the operation of the target control unit and adjust its power output to adapt to current and predicted power demand. Through effective power balance, the system can reduce energy waste, improve power generation efficiency, and maintain stable operation of the power grid, thereby supporting more sustainable and efficient energy management.

[0054] Furthermore, activating the power stabilizer based on the adaptive control instruction, and generating a target power balance control decision of the target control unit by the power stabilizer, includes:

[0055] Read the predetermined weather index, and perform weather feature traversal extraction on the first real-time weather information based on the predetermined weather index to obtain a first real-time weather index parameter set; introduce a weather evaluation function to evaluate and analyze the first real-time weather index parameter set to obtain a first real-time weather index; obtain the power balance control database embedded in the power stabilizer, and filter the power balance control database with the first real-time weather index and the target control unit as constraints to obtain a target control data group; extract the first control record in the target control data group, the first control record including the first unit operation information and the first unit power generation; obtain the target power generation optimization threshold, and determine whether the first unit power generation meets the target power generation optimization threshold; if so, use the first unit operation information as the target power balance control decision.

[0056] Predetermined weather indicators include wind speed, wind direction, temperature, humidity, solar irradiance, etc. These are key weather factors that affect the performance of wind power and photovoltaic power generation. These indicators are usually pre-set according to the geographical location of the power generation system and historical weather data to ensure adaptability and responsiveness to local climate conditions. Based on these predetermined weather indicators, the first real-time weather information is traversed, the corresponding indicator parameters are extracted, and organized into the first real-time weather indicator parameter set, which provides detailed data support for subsequent evaluation and decision-making.

[0057] The weather evaluation function is used to analyze the first real-time weather indicator parameter set and evaluate its potential impact on the performance of the power generation system. The function is constructed based on the statistical analysis of historical data and can comprehensively consider the impact of various weather factors on wind power and photovoltaic power generation efficiency. Through evaluation and analysis, the first real-time weather index is obtained, which is a comprehensive indicator that reflects the positive or negative impact that current weather conditions may have on the power generation system.

[0058] The power balance control database stores a series of preset power balance control data, which are designed based on different equipment states and environmental conditions to optimize the power output and stability of the power generation system. The first real-time weather index and the selected target control unit are used as the key constraints for screening the database. The first real-time weather index provides operation guidance under the current environmental conditions, and the target control unit ensures that the screened control strategy is highly targeted and suitable for the equipment that most needs adjustment. According to the specific needs of the weather index and the target unit, the power balance control data suitable for the current situation is screened from the database to obtain the target control data group.

[0059] A random control record is extracted from the target control data group as the analysis object as the first control record. This randomly selected control record can ensure that the system does not always rely on the same set of records, thereby exploring more possible solutions and finding a better global strategy.

[0060] The first control record includes the first unit operation information and the first unit power generation power, wherein the first unit operation information is the power balance control information of the unit matching the current situation, and the first unit power generation power is the power generation power of the unit matching the current situation.

[0061] The target power generation optimization threshold is preset based on system design, historical performance data, expected power demand and safety standards. The purpose of this threshold is to ensure that the generator set operates at optimal efficiency while meeting the needs of the power grid. Compare the power generation of the first unit with the preset optimization threshold. If the actual power reaches or exceeds this threshold, it means that the unit is operating efficiently and the current operation strategy can be continued; if it does not reach it, it needs to be adjusted or abandoned.

[0062] If the power generation of the first unit meets the optimization threshold, the corresponding operation information of the first unit will be used as the target power balance control decision, which means that the corresponding operation settings will be used to optimize the overall power generation efficiency. This data-driven decision-making process helps to improve the accuracy of energy management and the responsiveness of the system, ensuring that efficient and stable energy output can be continuously provided under changing environmental and operating conditions.

[0063] Further, including:

[0064] Obtain a first deviation power between the first predicted power generation power and the predetermined power generation power threshold; obtain the predicted power of the target control unit, recorded as the target predicted power; and set the target power generation power optimization threshold according to the power difference between the first deviation power and the target predicted power.

[0065] The first deviation power is the deviation between the first predicted power generation power and the predetermined power generation power threshold. The deviation can be simply obtained by subtracting the predetermined power generation power threshold from the first predicted power generation power. A negative value indicates that the predicted power is lower than the threshold and power generation needs to be increased; a positive value indicates that the predicted power exceeds the threshold and power generation needs to be reduced or the load needs to be adjusted.

[0066] If the target control unit is the first wind turbine unit, the first predicted power of the first wind turbine unit is obtained and recorded as the target predicted power; if the target control unit is the first photovoltaic unit, the second predicted power of the first photovoltaic unit is obtained and recorded as the target predicted power.

[0067] The power difference between the first deviation power and the target predicted power is calculated as the target power generation power optimization threshold, which is designed to refine the control strategy and ensure that the output of the power generation system more accurately meets the needs of the power grid and the system. If the first deviation power indicates that the overall power generation of the system is lower than the demand, and the predicted power of the target control unit is also low, the optimization threshold needs to be increased to encourage the unit to increase output; on the contrary, if the deviation indicates excessive power generation, the threshold needs to be lowered to reduce the power generation of the unit.

[0068] Furthermore, after obtaining the target power generation optimization threshold and determining whether the power generation power of the first unit meets the target power generation optimization threshold, it also includes: if the power generation power of the first unit does not meet the target power generation optimization threshold, extracting the second control record in the target control data group, and performing optimization judgment analysis on the second control record.

[0069] When the power generation of the first unit does not reach the target power generation optimization threshold, it means that the corresponding first control record does not meet the current demand. The first control record is discarded, and the second control record in the target control data group is randomly extracted again. The second control record is any record different from the first control record. This random selection of different control records can ensure that the system will not always rely on the same set of parameters, thereby exploring more possible solutions and finding a better global strategy.

[0070] The same analysis process as the first control record is used to perform a judgment analysis on the second control record. If the judgment analysis shows that the power generation power of the second unit in the second control record successfully reaches the threshold, the operation information of the second unit in the second control record is used as the target power balance control decision; otherwise, if it is not reached, the second control record is discarded, and the next control record is analyzed, and this process is repeated until all target control data groups are traversed.

[0071] In summary, the adaptive power balance control method of the wind-solar hybrid power generation system provided in the embodiment of the present application has the following technical effects:

[0072] By monitoring the load of the first wind-solar complementary generator set in the wind-solar complementary power generation system, real-time first wind-solar load monitoring information is obtained, which allows the system to make instant adjustments based on actual power generation and load conditions, thereby enhancing the system's ability to respond to fluctuations; a load evaluation function is introduced to evaluate and analyze the monitoring information to generate a first predicted power generation load. This prediction capability enables the power generation system to proactively adjust the power generation plan and optimize energy distribution; when the predicted power generation load does not meet the predetermined power generation load threshold, an adaptive control instruction is automatically issued. This adaptive control strategy can automatically adjust the system operation based on real-time data and prediction results, thereby increasing the flexibility and stability of the system; based on the adaptive control instruction, the power stabilizer is activated and a power balance control decision is generated, which enables the system to effectively manage the output of the generator set, reduce power fluctuations, and improve the energy efficiency and reliability of the overall system; based on the power balance control decision, an adaptive power balance control process is implemented on the wind-solar complementary generator set, thereby ensuring that the power generation system can maintain efficient and stable operation under changing environmental and load conditions, thereby optimizing resource utilization.

[0073] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An adaptive power balance control method for a wind-solar hybrid power generation system, characterized in that: The method comprises: Acquire a first wind-solar complementary generator set in the wind-solar complementary power generation system, and perform load monitoring on the first wind-solar complementary generator set to obtain first wind-solar load monitoring information; The first wind-solar complementary power generation unit at least comprises a first wind turbine unit and a first photovoltaic unit; Introducing a load evaluation function to evaluate and analyze the first wind and solar load monitoring information to obtain a first predicted power generation load; If the first predicted power generation load is not within the predetermined power generation load threshold, issuing an adaptive control instruction includes: When the first predicted power generation load is greater than the predetermined power generation load threshold, issuing an adaptive verification instruction; Acquire first real-time monitoring information of the first wind-solar complementary generator set based on the adaptive verification instruction, and use the first real-time monitoring information as input data of a power generation prediction model; The first real-time monitoring information is predicted and analyzed by the power generation prediction model to obtain a first predicted power generation, including: Extracting first real-time weather information from the first real-time monitoring information; Extracting first monitoring information of the first wind turbine generator set from the first real-time monitoring information; Extracting second monitoring information of the first photovoltaic group from the first real-time monitoring information; Using the first real-time weather information and the first monitoring information as input data of a wind power prediction channel of the power generation prediction model; Obtaining a first predicted power of the first wind turbine generator set through the wind power prediction channel; Using the first real-time weather information and the second monitoring information as input data of a photovoltaic power prediction channel of the power generation prediction model; Obtaining a second predicted power of the first photovoltaic unit through the photovoltaic power prediction channel; taking the sum of the first predicted power and the second predicted power as the first predicted generated power; When the first predicted power generation is not within the predetermined power generation threshold, issuing the adaptive control instruction; activating the power stabilizer based on the adaptive control instruction, and generating a first power balance control decision of the first wind-solar complementary power generator set through the power stabilizer, including: Comparing the first predicted power with the second predicted power to obtain a power comparison result; According to the power comparison result, if the first predicted power is greater than the second predicted power, taking the first wind turbine set as a target controlled set; According to the power comparison result, if the first predicted power is less than the second predicted power, taking the first photovoltaic unit as the target control unit; activating the power stabilizer based on the adaptive control instruction, and generating a target power balance control decision of the target control unit by the power stabilizer; Using the target power balance control decision as the first power balance control decision; Adaptive power balancing control processing is performed on the first wind-solar complementary generator set according to the first power balancing control decision.

2. The adaptive power balance control method of the wind-solar hybrid power generation system according to claim 1 is characterized in that: Introducing a load evaluation function to evaluate and analyze the first wind and solar load monitoring information to obtain a first predicted power generation load, including: Extracting first load monitoring information of the first wind turbine generator set, wherein the first load monitoring information includes first power supply load data and first factory load data; Extracting second load monitoring information of the first photovoltaic group, wherein the second load monitoring information includes second power supply load data and second plant load data; A load-weighted evaluation is performed on the first power supply load data, the first plant load data, the second power supply load data and the second plant load data according to the load evaluation function to obtain the first predicted power generation load.

3. The adaptive power balance control method of the wind-solar hybrid power generation system according to claim 1, characterized in that: The power stabilizer is activated based on the adaptive control instruction, and the power stabilizer generates a target power balance control decision of the target control unit, including: Reading a predetermined weather index, and performing weather feature traversal extraction on the first real-time weather information based on the predetermined weather index to obtain a first real-time weather index parameter set; Introducing a weather evaluation function to evaluate and analyze the first real-time weather indicator parameter set to obtain a first real-time weather index; Acquire a power balance control database embedded in the power stabilizer, and filter the power balance control database based on the first real-time weather index and the target control unit as constraints to obtain a target control data group; Extracting a first control record from the target control data group, wherein the first control record includes operation information of the first unit and power generation power of the first unit; Obtaining a target power generation optimization threshold, and determining whether the power generation power of the first unit meets the target power generation optimization threshold; If so, the first unit operation information is used as the target power balance control decision.

4. The adaptive power balance control method of the wind-solar hybrid power generation system according to claim 3 is characterized in that: include: Obtaining a first deviation power between the first predicted power generation power and the predetermined power generation power threshold; Obtaining the predicted power of the target control unit, recorded as the target predicted power; The target power generation power optimization threshold is set according to the power difference between the first deviation power and the target predicted power.

5. The adaptive power balance control method of the wind-solar hybrid power generation system according to claim 3 is characterized in that: After obtaining the target power generation optimization threshold and determining whether the power generation power of the first unit meets the target power generation optimization threshold, it also includes: if the power generation power of the first unit does not meet the target power generation optimization threshold, extracting the second control record in the target control data group, and performing optimization judgment analysis on the second control record.

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