An automatic generation control method and system for a wind-solar-storage combined system

Abstract

The application discloses a kind of automatic generation control method and system for wind-light-storage combined system, it is related to electric power control technical field, the method includes: real-time acquisition wind-light-storage combined system instruction and active power measured value;Residual value is determined based on wind-light-storage combined system instruction and active power measured value;Residual statistics is determined based on residual value;Residual fault detection result is obtained based on residual statistics and threshold rule;Using fault mitigation strategy, correction instruction is obtained based on residual fault detection result;Determine allocation strategy based on input instruction;Determine wind farm AGC instruction, photovoltaic power station AGC instruction and energy storage power station AGC instruction based on allocation strategy and correction instruction.The application can improve the control accuracy of AGC and the overall stability of wind-light-storage combined system.

Description

Technical Field

[0001] This application relates to the field of power control technology, and in particular to an automatic power generation control method and system for wind-solar-storage integrated systems. Background Technology

[0002] To enhance the grid regulation capacity of renewable energy sources, it is essential to promote the coordinated development of power generation, grid, load, and energy storage. In particular, it is recommended to increase investment in energy storage facilities on the power generation side. Currently, integrated wind, solar, and energy storage projects are being implemented gradually, indicating that the deep integration of wind, solar, and energy storage systems is a key measure to improve the efficiency of renewable energy absorption and system flexibility.

[0003] Automatic Generation Control (AGC) requires power generation equipment to dynamically adjust its output based on AGC signals or frequency regulation power commands issued by the power dispatch center. This is a crucial mechanism for ensuring the grid-friendliness of each power generation unit. Given the increasing number of wind-solar-storage projects being put into practical application, there is an urgent need to develop an efficient AGC strategy for combined wind-solar-storage systems. This strategy must possess rapid response capabilities and high-precision tracking performance. However, most current research on AGC optimization relies primarily on idealized models or simulation environments, lacking on-site deployment and verification support. Therefore, its results are difficult to directly apply to the operation of real new energy power plants.

[0004] Furthermore, AGC control strategies in related studies are typically based on the ideal assumption of a fault-free operating environment to ensure the realization of predetermined performance and functions. However, in actual engineering practice, as the scale of wind, solar, and energy storage systems continues to expand, the number of controlled components increases dramatically, the probability of individual component failures also rises, and the risk of communication link interruptions also increases. These problems can seriously affect the control accuracy of AGC and the overall stability of the system.

[0005] In summary, although there has been considerable research on AGC strategies and fault-tolerant control for wind-solar-storage integrated systems, the following shortcomings remain: (1) Most current AGC optimization schemes are only at the theoretical simulation stage, lacking on-site testing and verification in actual engineering applications; (2) Related schemes generally fail to fully consider how to deal with various typical faults that may occur during actual operation; (3) Current research has not fully explored the close integration between AGC strategies and fault-tolerant control strategies. Therefore, existing AGC strategies and fault-tolerant control methods for wind-solar-storage integrated systems cannot guarantee the control accuracy of AGC and the overall stability of the wind-solar-storage integrated system. Summary of the Invention

[0006] The purpose of this application is to provide an automatic power generation control method and system for wind-solar-storage integrated systems, which can improve the control accuracy of AGC and the overall stability of wind-solar-storage integrated systems.

[0007] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides an automatic power generation control method for a wind-solar-storage integrated system, comprising: The system acquires commands and measured active power values ​​of the wind-solar-storage integrated system in real time; the integrated system includes a wind farm, a photovoltaic power station, and an energy storage power station. The residual value is determined based on the command and measured active power values ​​of the wind-solar-storage integrated system. Determine the residual statistics based on the residual values; The residual fault detection results are obtained based on the residual statistics and threshold rules. A fault mitigation strategy is adopted to obtain a correction instruction based on the residual fault detection results; The allocation strategy is determined based on the input command; the allocation strategy includes a wind power priority strategy, a photovoltaic priority strategy, and a wind-solar ratio strategy. Based on the allocation strategy and the correction instructions, AGC instructions for wind farms, photovoltaic power plants, and energy storage power plants are determined; the AGC instructions for wind farms are used to control the operation of the wind farms; the AGC instructions for photovoltaic power plants are used to control the operation of the photovoltaic power plants; and the AGC instructions for energy storage power plants are used to control the operation of the energy storage power plants.

[0008] Secondly, this application provides an automatic power generation control system for a wind-solar-storage integrated system, comprising: The fault diagnosis module, connected to the wind-solar-storage integrated system, is used to acquire the commands and measured active power values ​​of the integrated system. The fault diagnosis module is also used to determine residual values ​​based on the commands and measured active power values ​​of the integrated system. Furthermore, the fault diagnosis module is used to determine residual statistics based on the residual values. Finally, the fault diagnosis module is used to obtain residual fault detection results based on the residual statistics and threshold rules. The main control module is connected to the fault diagnosis module and the wind-solar-storage integrated system, respectively, and is used to obtain correction instructions based on the residual fault detection results using a fault mitigation strategy; the main control module is also used to determine the allocation strategy based on the input instructions; the main control module is also used to determine the AGC instructions for the wind farm, the AGC instructions for the photovoltaic power station, and the AGC instructions for the energy storage power station based on the allocation strategy and the correction instructions.

[0009] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides an automatic power generation control method and system for a wind-solar-storage integrated system. It determines residual values ​​based on commands and measured active power values ​​from the integrated system, then determines residual statistics, and obtains residual fault detection results based on the residual statistics and threshold rules. This fully considers and detects various typical faults that may occur in the actual operation of the wind-solar-storage integrated system. A fault mitigation strategy is adopted to obtain correction commands based on the residual fault detection results. Based on the allocation strategy and correction commands, AGC commands (including wind farm AGC commands, photovoltaic power station AGC commands, and energy storage power station AGC commands) for the wind-solar-storage integrated system are determined. The AGC strategy is closely integrated with the fault mitigation strategy to control the wind-solar-storage integrated system, improving the control accuracy of AGC and the overall stability of the integrated system. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart of an automatic power generation control method for a wind-solar-storage integrated system according to an embodiment of this application; Figure 2 A schematic diagram of an automatic power generation control system for a wind-solar-storage integrated system is provided as an embodiment of this application; Figure 3 A schematic diagram of the power response curve of a wind-solar-storage integrated system under a wind power priority strategy provided in an embodiment of this application; Figure 4 This is a schematic diagram of the AGC deviation curve of a wind-solar-storage integrated system under a wind power priority strategy provided in an embodiment of this application; Figure 5 A schematic diagram illustrating the changes in wind curtailment rate and solar curtailment rate during the noon period, provided as an embodiment of this application; Figure 6 This is a schematic diagram of the power response curve of a wind-solar-storage integrated system under a photovoltaic priority strategy, provided in an embodiment of this application. Figure 7 A schematic diagram of the AGC deviation curve of a wind-solar-storage integrated system under a photovoltaic priority strategy provided in an embodiment of this application; Figure 8 This is a schematic diagram illustrating the trend of curtailment rate under a photovoltaic priority strategy provided in an embodiment of this application. Figure 9 A schematic diagram of the power response curve of a wind-solar-storage integrated system under a wind-solar ratio strategy provided in an embodiment of this application; Figure 10 A schematic diagram of the AGC deviation curve of a wind-solar-storage integrated system under a wind-solar ratio strategy provided in an embodiment of this application; Figure 11 A schematic diagram illustrating the trend of curtailment rate under a wind-solar ratio strategy provided in an embodiment of this application; Figure 12 A schematic diagram of the power response process of a wind-solar-storage combined system when a wind farm failure occurs, provided in an embodiment of this application; Figure 13 A schematic diagram of residual statistics and fault identification process in fault-tolerant control when a wind farm fault occurs, provided as an embodiment of this application; Figure 14 A schematic diagram of the AGC deviation curve of a wind-solar-storage integrated system under unit failure provided in an embodiment of this application; Figure 15 This is a schematic diagram of the wind curtailment rate change curve under unit failure provided in an embodiment of this application; Figure 16 This is a schematic diagram of the power response process of a wind-solar-storage integrated system under a wind farm communication failure, provided in an embodiment of this application. Figure 17 A schematic diagram of residual statistics and fault identification process in fault-tolerant control under wind farm communication failure provided in an embodiment of this application; Figure 18 A schematic diagram of the AGC deviation curve of a wind-solar-storage integrated system under communication failure provided in an embodiment of this application; Figure 19 This is a schematic diagram of the wind curtailment rate change curve under communication failure provided in an embodiment of this application. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] In one exemplary embodiment, such as Figure 1 As shown, an automatic power generation control method for a wind-solar-storage integrated system is provided, including: Step S1: Obtain the commands and measured active power values ​​of the wind-solar-storage integrated system in real time. The wind-solar-storage integrated system includes a wind farm, a photovoltaic power station, and an energy storage power station.

[0015] Step S2: Determine the residual value based on the instructions and measured active power values ​​of the wind-solar-storage integrated system. Determine the residual statistics based on the residual value.

[0016] Step S3: Obtain residual fault detection results based on residual statistics and threshold rules.

[0017] Step S4: Using a fault mitigation strategy, a correction instruction is obtained based on the residual fault detection results.

[0018] Step S5: Determine the allocation strategy based on the input instructions. The allocation strategies include wind power priority strategy, photovoltaic priority strategy, and wind-solar ratio strategy.

[0019] Step S6: Based on the allocation strategy and correction instructions, determine the AGC instructions for wind farms, photovoltaic power plants, and energy storage power plants. The wind farm AGC instructions are used to control the operation of the wind farm. The photovoltaic power plant AGC instructions are used to control the operation of the photovoltaic power plant. The energy storage power plant AGC instructions are used to control the operation of the energy storage power plant.

[0020] In one embodiment, the process of determining the residual value based on the commands and measured active power values ​​of the wind-solar-storage combined system in step S2 includes: acquiring historical operating data of the wind-solar-storage combined system; determining the ARX parameters of the ARX model based on the historical operating data to construct an ARX prediction model; using the ARX prediction model to determine the predicted active power value based on the commands of the wind-solar-storage combined system; and determining the residual value based on the predicted active power value and the measured active power value.

[0021] For example, in this embodiment, a bidirectional CUSUM (Cumulative Sum) algorithm based on an Auto-Regressive with eXogenous Input (ARX) model is used to detect faults. After identifying and determining the ARX parameters of the ARX model based on historical operating data, the resulting ARX prediction model is shown in formula (1).

[0022] (1) In the formula, For the first determined according to the ARX prediction model One power station Predicted active power at time 10:00. Indicates the first One power station Measured active power at any given time. Indicates the first One power station The instructions of the moment, Indicates the first One power station External fluctuations at any given moment. Let represent the autoregressive order, exogenous input order, and external perturbation order of the ARX model, respectively. For ARX parameters.

[0023] Among them, the power station refers to the wind farm, photovoltaic power station or energy storage power station in the wind-solar-storage integrated system. That is, the instructions of the wind-solar-storage integrated system include the instructions of the wind farm, the instructions of the photovoltaic power station and the instructions of the energy storage power station. In this embodiment, the number of power stations in the wind-solar-storage combined system is indicated. It should be noted that in the following embodiments, subscripts... All indicate the first A power plant.

[0024] Define residual signal For the first One power station The residual between the measured active power and the predicted active power at time t is shown in formula (2).

[0025] (2) Under healthy operating conditions, the first One power station Residual value at time step It follows a Gaussian distribution with a mean of 0. , denoted as the standard deviation of the residuals. When a fault occurs in the combined wind, solar, and energy storage system, the mean of this Gaussian distribution will change significantly.

[0026] In this embodiment, a bidirectional CUSUM algorithm is proposed. This algorithm can accumulate the positive and negative offsets of the reference value (i.e., the command of the wind-solar-storage integrated system) in parallel as the wind-solar-storage integrated system is adjusted, thereby realizing omnidirectional fault diagnosis.

[0027] Assuming the wind-solar-storage integrated system is in a healthy operating condition (i.e., without faults, assuming it is...) (Next, the first) One power station Residual value at time step The noise is zero-mean random, and a fault occurs (i.e., the wind-solar-storage integrated system is in a fault condition, assuming it is zero-mean random noise). After that, the residual value The mean is The offset. Based on the sequential probability ratio test, The sequence of residual values ​​observed at time 1 correspond Compared to log-likelihood ratio The definition is shown in formula (3).

[0028] (3) In the formula, for Assume the probability density function of the residual value ( ), for Assume the probability density function of the residual value ( Based on the above residual values It follows a Gaussian distribution and is under healthy operating conditions. The fault caused the mean to shift. Then we have: (4) Accumulate formula (4) from 1 to... Log-likelihood ratio It can be expressed as formula (5).

[0029] (5) Based on the allowable adjustment accuracy in engineering applications, the acceptable range of residuals is set, and the maximum permissible deviation is introduced. For example, wind farms typically require regulation accuracy to be within 2% of rated capacity, meaning the residual deviation must be less than... When the residual amplitude exceeds a certain value, it is considered a non-faulty state (i.e., in a healthy operating condition). Only when this condition is met is the wind farm considered to have a potential fault (i.e., be in a fault condition). Based on this, a reference offset for the CUSUM criterion is set. , .

[0030] The statistic is recursively updated at each sampling time and reset when it falls below zero to ensure effective accumulation of the mean shift of the residual distribution. This is combined with a reference offset. Define residual statistics .

[0031] (6) The recursive formula is obtained from formula (6), as shown in formula (7).

[0032] (7) Based on this, update rules for the CUSUM statistics of positive and negative residuals are constructed respectively, as shown in formula (8). That is, the residual statistics include positive and negative residual statistics.

[0033] (8) In the formula, .

[0034] Through the above and Parallel cumulative updates enable synchronous monitoring of the mean positive and negative shifts in the residual value distribution.

[0035] In one embodiment, step S3 includes: obtaining an initial fault determination result based on residual statistics and threshold rules. When the residual statistics do not meet the threshold rules, the initial fault determination result is no fault. When the residual statistics meet the threshold rules, the initial fault determination result is a unit fault, and the instructions of the wind-solar-storage combined system are adjusted to obtain new instructions for the wind-solar-storage combined system. A new residual statistics is determined based on the new instructions of the wind-solar-storage combined system and the measured active power value of the new wind-solar-storage combined system. A secondary fault determination result is obtained based on the new residual statistics and threshold rules. The secondary fault determination result is either a fault or no fault. A residual fault detection result is obtained based on the initial fault determination result and the secondary fault determination result. The residual fault detection result is either no fault, communication fault, or unit fault.

[0036] The threshold rule construction process includes: obtaining the first expected residual mean and the second expected residual mean; determining the threshold based on the first expected residual mean and the second expected residual mean; and constructing the threshold rule based on the threshold.

[0037] For example, the threshold rule is constructed as shown in formula (9).

[0038] (9) When either statistic (positive residual statistic and negative residual statistic) exceeds the threshold When this happens, it can be determined that a fault has occurred (i.e.) In the formula, for The binary fault label at time (i.e., the fault determination result).

[0039] Among them, under fault conditions, the threshold For the average detection delay ( The average detection delay can be determined by the Average Run Length (ARL) function, as shown in formula (10).

[0040] (10) In the formula, This represents the mean of the cumulative sum and the increment. The standard deviation represents the cumulative and incremental values. It is an exponentially decaying term. For linear correction terms, This is the normalization factor. Equal to average detection delay ,That and As shown in formulas (11) and (12).

[0041] (11) (12) Then, the threshold is solved in reverse by using numerical methods combined with formula (10). .

[0042] To further identify specific fault types, refined analysis of detected anomalies is required, i.e., fault isolation. For two common fault types—communication faults and unit faults—this application proposes a fault type identification method based on quadratic residual response, building upon fault detection. This method employs a "two-stage detection + classification mitigation feedback" mechanism. When the initial fault determination result is a fault occurrence, a fine-tuning control command is actively triggered to re-detect the response residual. The final residual fault detection result is determined through these two determinations.

[0043] Specifically, the residual signal (i.e., residual value) of the power plant is detected to obtain a statistical quantity. and Then, the binary fault label (i.e. fault determination result) of the power station is obtained by using formula (9).

[0044] When a fault is detected for the first time at a power station (a binary fault is marked as 1, meaning the initial fault determination result is a fault), the fault is assumed to be a recoverable unit fault, and an incremental command correction mechanism is immediately triggered to fine-tune the commands of the power station (in this embodiment, commands from a wind farm, a photovoltaic power station, or an energy storage power station). This correction operation does not distinguish between specific fault types and aims to quickly mitigate the deviations caused in the early stages of a fault.

[0045] After mitigation, the residual value of the power plant is tested again to obtain new statistics, and then judged again by formula (9) to obtain the secondary fault judgment result of the power plant.

[0046] Finally, the residual fault detection results of the power station are obtained based on the initial fault judgment results and the secondary fault judgment results of the power station, as shown in formula (13).

[0047] (13) in, Indicates the first One power station Residual fault detection results at any given time. Indicates the first One power station The initial fault diagnosis result at that moment. Indicates the first One power station The result of the secondary fault determination at a given time.

[0048] Each power station in the wind-solar-storage combined system underwent two-stage testing to obtain... Residual fault detection results of the wind-solar-storage integrated system As shown in formula (14).

[0049] (14) In one embodiment, the fault mitigation strategy includes a unit fault mitigation mechanism and a communication fault mitigation mechanism. Based on this, the implementation process of step S4 includes: when the residual fault detection result is a communication fault, a correction instruction is obtained using the communication fault mitigation mechanism; when the residual fault detection result is a unit fault, a correction instruction is obtained using the unit fault mitigation mechanism.

[0050] in, Indicates the first One power station No malfunctions occurred at any time. Indicates the first One power station Communication failures occur frequently. Indicates the first One power station Unit failures can occur at any time.

[0051] For example, after completing fault detection and fault type identification, corresponding measures need to be taken according to the current fault type to maintain the stable operation of the power plant and provide basic support for subsequent command allocation. In this embodiment, this application, combined with the actual operating characteristics of the wind-solar-storage integrated system, designs a control reconfiguration mechanism based on fault classification (i.e., fault mitigation strategy, including unit fault mitigation mechanism and communication fault mitigation mechanism) to achieve differentiated responses to unit faults and communication faults.

[0052] (1) Unit fault mitigation mechanism. When the first fault is detected... When a unit failure occurs at a power plant, an incremental instruction reconfiguration strategy is used for mitigation. According to the... residual signal of a power station The cumulative value correction instructions for the wind-solar-storage integrated system The correction instructions after mitigation are as shown in formula (15).

[0053] (15) In the formula, This indicates the command for the wind-solar-storage integrated system at the next moment after correction (i.e., the correction command).

[0054] (2) Communication Fault Mitigation Mechanism. A command reconstruction mechanism based on mode switching is used to mitigate communication faults. Firstly, based on the residual fault detection results of the wind-solar-storage integrated system... Determine the operating mode of each power generation unit and obtain the mode flag bit. .

[0055] (16) Commands from the wind-solar-storage integrated system The actual output of power plants that have experienced communication failures is removed from the calculation, and a correction instruction (i.e., net demand instruction) is generated, as shown in formula (17).

[0056] (17) In the formula, Indicates the first The actual output of each power station.

[0057] By implementing the above-mentioned fault mitigation strategies, interference from unit faults and communication faults can be effectively isolated, and operating modes and correction instructions that match abnormal operating conditions can be dynamically generated.

[0058] In one embodiment, after determining the wind farm AGC command, photovoltaic power station AGC command, and energy storage power station AGC command based on the allocation strategy and correction command in step S6, during the process of controlling the operation of the wind farm, photovoltaic power station, and energy storage power station respectively using the wind farm AGC command, photovoltaic power station AGC command, and energy storage power station AGC command, it is determined whether the correction command meets the set conditions based on the measured active power value of the wind-solar-storage combined system.

[0059] When the set conditions are met, the AGC commands for wind farms and photovoltaic power plants are frozen, and the AGC commands for energy storage power plants are corrected to obtain corrected AGC commands. Boundary constraints are then used to verify the corrected AGC commands, resulting in updated AGC commands. The updated AGC commands are then used to control the operation of the energy storage power plant.

[0060] To ensure tracking accuracy and speed while maximizing renewable energy absorption, three allocation strategies were designed, taking into account grid performance and power plant economics: a wind power priority strategy, a photovoltaic priority strategy, and a wind-solar ratio strategy. These strategies are described using IF-THEN rules. The allocation strategies are pre-embedded in the rule base.

[0061] (1) Design of wind power priority strategy.

[0062] The wind power priority strategy applies when grid-side wind power performance targets are stringent or wind power prices are high, in which the combined wind-solar-storage system prioritizes wind power output. The wind power priority strategy can be expressed as: (18) (19) (20) In the formula, This indicates a wind power priority strategy. Represents the set of key parameters. This represents the set of prerequisite attributes for a wind power priority strategy. This represents the set of wind power priority strategy allocation results. This represents the logical function for the wind power priority strategy. All three allocation strategies share a common set of key parameters. These are the initial AGC instructions for wind farms, the initial AGC instructions for photovoltaic power plants, and the initial AGC instructions for energy storage power plants determined under the wind power priority strategy. and These represent the minimum and maximum power output boundaries of the wind farm, respectively. and These represent the minimum and maximum output boundaries of a photovoltaic power station, respectively. and These represent the maximum chargeable and maximum dischargeable boundaries of an energy storage power station. AGC instructions (i.e., correction instructions) for wind-solar-storage integrated systems ).

[0063] The prerequisite attributes for a wind power priority strategy are: (twenty one) In the formula, , , , and These are all condition label variables in the wind power priority strategy. In actual implementation, condition label variables need to be combined with other strategy judgment conditions to determine the final instruction allocation path.

[0064] Logical function of wind power priority strategy for: (twenty two) (twenty three) (twenty four) In the formula: , , , and This represents the opposite of the condition.

[0065] (2) Photovoltaic priority strategy design.

[0066] The photovoltaic (PV) priority strategy is applicable to avoid power curtailment during peak PV output periods, smooth out peak loads, or during PV power generation assessment periods. The PV priority strategy can be expressed as: (25) (26) In the formula, It is the set of prerequisite attributes for the photovoltaic priority strategy; It is the logical function of the photovoltaic priority strategy. This represents the set of allocation results for the photovoltaic priority strategy. These are the initial AGC instructions for wind farms, initial AGC instructions for photovoltaic power plants, and initial AGC instructions for energy storage power plants determined under the photovoltaic priority strategy.

[0067] The prerequisite attributes for the photovoltaic priority strategy are: (27) In the formula: , , , and All of these are conditional label variables in the photovoltaic priority strategy.

[0068] Logical function of photovoltaic priority strategy for: (28) (29) (30) In the formula: , , , and This represents the opposite of the condition.

[0069] (3) Design of the landscape ratio strategy.

[0070] The wind-solar ratio strategy is suitable for scenarios where wind and solar power are priced similarly, achieving a balanced absorption of both. The wind-solar ratio strategy can be expressed as: (31) (32) In the formula, It is the set of prerequisite attributes for the landscape ratio strategy; It is the logical function of the landscape ratio strategy. This represents the set of results from the wind-solar ratio allocation strategy. These are the initial AGC instructions for wind farms, initial AGC instructions for photovoltaic power plants, and initial AGC instructions for energy storage power plants determined under the wind-solar ratio strategy.

[0071] The prerequisite attribute for the landscape-sun ratio allocation strategy is: (33) In the formula: , and All of these are conditional label variables in the wind-solar ratio allocation strategy.

[0072] Logical function of the landscape ratio strategy for: (34) (35) (36) (37) (38) In the formula, , and This represents the opposite of the condition. This indicates the maximum adjustable power output range of the wind farm. This indicates the maximum adjustable output range of a photovoltaic power station.

[0073] After completing the allocation strategy design, the AGC control process must be executed according to a pre-defined rule base and a specific judgment procedure. Together, these two processes achieve coordinated control of the wind-solar-storage integrated system, adapting to the flexible needs of diverse collaborative scenarios involving wind, solar, and storage, and improving the AGC's responsiveness and control performance to scheduling commands.

[0074] Among them, fault tolerance has a higher priority than conventional AGC control.

[0075] The fault detection process described in the above embodiments determines whether a fault exists in the wind-solar-storage integrated system. If no fault occurs, the initial AGC instructions for each power station are calculated based on a pre-designed rule base. If a fault occurs, correction instructions are determined. The corresponding allocation strategy is retrieved from the rule base using the acquired input instructions. The initial AGC instructions for the wind farm, the initial AGC instructions for the photovoltaic power station, and the initial AGC instructions for the energy storage power station are determined based on the allocation strategy and the correction instructions. Boundary constraints are used to verify the initial AGC instructions for the wind farm, the initial AGC instructions for the photovoltaic power station, and the initial AGC instructions for the energy storage power station, resulting in the final AGC instructions for the wind farm, the photovoltaic power station, and the energy storage power station.

[0076] Specifically, boundary constraints are used to verify the AGC commands (such as initial wind farm AGC commands) of each power station to ensure that the generated AGC commands are within the actual operating capacity of the equipment (i.e., the wind-solar-storage integrated system), thus avoiding equipment overload, protection actions, or failure to meet grid dispatch assessment standards due to commands exceeding the limits. The boundary constraints are as follows: , and If the AGC commands of each power station satisfy their respective constraints, then the AGC commands of each power station will be used as the AGC commands for the wind farm, photovoltaic power station, and energy storage power station, respectively. If the AGC command of a certain power station does not satisfy its corresponding constraints, then the boundary value closest to the AGC command of that power station will be used as the final AGC command, thus obtaining the AGC commands for the wind farm, photovoltaic power station, and energy storage power station.

[0077] To achieve high-precision tracking of commands, this embodiment proposes a dynamic fine-tuning compensation method for energy storage. When wind farm AGC commands, photovoltaic power station AGC commands, and energy storage power station AGC commands are used to control the operation of wind farm, photovoltaic power station, and energy storage power station respectively, when the correction command meets the set conditions and enters the small deviation range, the wind farm AGC command and photovoltaic power station AGC command are frozen. The energy storage performs dynamic fine-tuning correction operation to correct the energy storage power station AGC command, thereby achieving rapid suppression and stable elimination of AGC errors.

[0078] (39) (40) In the formula, To fine-tune the tolerance range, This represents the measured active power of the combined wind, solar, and energy storage system. The corrected AGC command for the energy storage power station. for Measured active power of the wind farm at any given time. for The measured active power of the photovoltaic power station at any given time.

[0079] After receiving the corrected AGC command from the energy storage power station, boundary constraints are used to verify the corrected AGC command, resulting in an updated AGC command to control the operation of the energy storage power station.

[0080] Based on the above embodiments, to meet the requirements of wind-solar-storage integrated systems for multiple operating modes and high tracking performance in Automatic Generation Control (AGC), as well as to address issues such as operational fault disturbances, this application proposes a collaborative optimization method integrating rule-driven and fault-tolerant control (i.e., an automatic generation control method for wind-solar-storage integrated systems). At the control level, a rule base containing three allocation strategies is constructed to achieve rapid and accurate tracking of grid dispatch commands. At the fault handling level, a bidirectional cumulative sum (CUSUM) detection algorithm and a two-stage fault identification mechanism are designed, combined with incremental command correction and mode reconstruction strategies, to form a "detection-isolation-mitigation" closed-loop fault-tolerant control framework.

[0081] The wind-solar-storage control framework adopts a two-layer "supervision-execution" control architecture. Fault-tolerant control strategies are implemented in the supervision layer, achieving effective detection and classification responses to unit and communication faults through a "fault diagnosis-isolation-mitigation" closed loop, thus ensuring the tracking performance of this application under fault scenarios. Rule-driven AGC optimization strategies are implemented in the execution layer, aiming to improve the wind-solar absorption capacity and enhance the response accuracy and speed of the wind-solar-storage integrated system to grid AGC commands, thereby determining and issuing AGC commands to each power station.

[0082] In normal scenarios, the AGC instructions for each power station can be directly determined after receiving the grid dispatch instructions. In fault scenarios, the monitoring layer detects the fault and, through the "fault diagnosis-isolation-mitigation" closed loop, transmits the reconstructed control instructions (i.e., correction instructions) to the execution layer. Based on the correction instructions, the AGC instructions for each power station are determined to control the operation of the wind-solar-storage combined system, thereby suppressing the impact of the fault.

[0083] In one exemplary embodiment, the above method is used for control of the actual operation of the wind-solar-storage integrated system. The control effects of different allocation strategies are explained, and field tests and verifications are conducted in actual engineering applications to verify the effectiveness of the technical solution provided in this application. Here, "the entire station" refers to the wind-solar-storage integrated system. "Active power command" refers to the AGC command.

[0084] 1. Operational effectiveness of the wind power priority strategy.

[0085] Under a wind power priority strategy, wind power resources are maximized through dynamic optimization of command allocation. For example... Figure 3As shown, the operating curve corresponds to the noon period, during which the maximum power generation of the photovoltaic power station reaches 70~75MW. However, the method provided in this application controls the output of the photovoltaic power station within the minimum active power operating boundary allowed by photovoltaics to avoid regulation competition with wind power output. At the same time, the energy storage power station operates at the maximum charging power, releasing regulation space for wind power and maximizing the utilization of wind power output.

[0086] Figure 4 The AGC deviation curve of the wind-solar-storage combined system under the wind-power-priority strategy is shown. After each AGC command change, the wind-solar-storage combined system quickly converges to the error tolerance range within a short period of time. The dynamic fine-tuning mechanism of energy storage enables the error of the wind-solar-storage combined system to converge to the ±0.5% range after entering steady state, further verifying the good performance of this strategy in terms of response speed and control accuracy.

[0087] Figure 5 The chart shows the changes in wind curtailment rate and solar curtailment rate during the corresponding time period (i.e., noon). It can be seen that under the wind power priority dispatch strategy, the system significantly suppressed the increase in wind curtailment rate, with a portion of photovoltaic power being diverted for wind power grid connection, effectively improving the utilization efficiency of wind power resources.

[0088] Table 1 shows the tracking performance evaluation results of the wind-solar-storage combined system under the wind power priority strategy of the wind-solar-storage mode. As can be seen from Table 1, the average tracking accuracy is ≤0.56%, which is 75% lower than the target requirement; the settling time is between 21s and 25s, which is 58.3% shorter than the target requirement of 60s.

[0089] Table 1. Tracking performance evaluation results under the wind power priority allocation strategy.

[0090] 2. The effectiveness of the photovoltaic priority strategy.

[0091] The photovoltaic priority strategy prioritizes photovoltaic output by dynamically adjusting the charging and discharging power of the energy storage system. For example... Figure 6 As shown, the actual power output of the photovoltaic power station always closely follows the maximum available power output. The energy storage system adjusts its power output in real time according to the AGC instructions of the entire station, flexibly switching between charging and discharging, thereby maximizing the wind and solar power integration capacity while meeting the system dispatch requirements. Figure 6 As shown, during some command changes, wind power exhibits a certain tracking deviation. At this time, the energy storage dynamic fine-tuning mechanism slightly adjusts the energy storage output to maintain the average tracking accuracy within 0.5% after entering steady state. Figure 7 As shown.

[0092] like Figure 8As shown, under the photovoltaic priority strategy, except for sudden fluctuations in photovoltaic power, the curtailment rate of solar power has remained below 2.5%, maintaining a low level, while the curtailment rate of wind power has fluctuated within the range of 3% to 18%.

[0093] Table 2 shows the tracking performance evaluation results of the wind-solar-storage integrated system under the photovoltaic priority strategy of wind-solar-storage mode. As can be seen from Table 2, the average tracking error is ≤0.23%, which is 90% lower than the target requirement; the settling time is between 5s and 10s, which is 83.3% shorter than the target requirement of 60s. These results indicate that this strategy not only improves the utilization efficiency of photovoltaic resources but also possesses good AGC response performance and system control capabilities.

[0094] Table 2. Tracking performance evaluation results under the photovoltaic priority strategy.

[0095] 3. The effectiveness of the wind-solar ratio strategy.

[0096] The wind-solar ratio strategy, through a certain allocation ratio of wind and solar power output, achieves the synchronous and coordinated utilization of wind and solar resources while meeting active power dispatch instructions. Figure 9 During the first 13 minutes (11:30:42~11:43:12) and the following 15 minutes (11:45:42~12:00:42), influenced by the high command levels of the wind-solar-storage integrated system, both wind and solar power output were largely released. During this period, the energy storage station operated in charging mode, effectively absorbing excess power, and the integrated system was in a low-curtailment state, fully utilizing wind and solar resources. However, between 11:43:12 and 11:45:42, the command levels of the integrated system were at a low point. Even with the energy storage station operating at its maximum charging capacity, it could not fully absorb the total output of wind and solar power, necessitating a coordinated wind-solar curtailment operation. During this phase, both wind and solar power experienced significant power limiting, and the actual power output curves showed a certain proportional change trend. This verifies that the wind-solar ratio strategy can dynamically suppress power output according to a certain proportion in power excess scenarios, maintaining a balance in load sharing among resources.

[0097] like Figure 10 As shown, the average tracking accuracy of the wind-solar-storage integrated system after entering steady state remains within ±2%, with the control error converging to within ±0.3% for most of the time periods.

[0098] like Figure 11 As shown, under the wind-solar ratio strategy, the wind-solar-storage integrated system exhibits a clear characteristic of proportional curtailment of wind and solar power during the off-peak periods of dispatch instructions. Furthermore, since the instructions from each power station are issued periodically, there are instances within some instruction cycles where wind and solar power have a surplus capacity but are not fully dispatched, thus resulting in localized curtailment during certain operating cycles.

[0099] Table 3 shows the tracking performance evaluation results of the wind-solar-storage combined system under the wind-solar-storage ratio strategy. As can be seen from Table 3, under the wind-solar ratio strategy, the average tracking error is ≤0.27%, which is 88.5% lower than the target requirement; the settling time is between 7s and 55s, which is 8.33%~88.3% shorter than the target requirement of 60s. Compared with wind-first or solar-first strategies, this strategy is more suitable for scenarios with balanced resource output.

[0100] Table 3. Tracking performance evaluation results under the wind-solar ratio strategy.

[0101] In summary, the rule-driven AGC control strategy demonstrates good tracking performance under three allocation strategies: wind power priority, photovoltaic priority, and wind-solar ratio. The AGC tracking accuracy reaches within ±0.56%, which is 72%~90% higher than the standard requirement, and the adjustment time does not exceed 55s, which is 8.3%~91.7% higher than the standard requirement, and is significantly improved compared with the current standard requirements.

[0102] 4. Analysis of unit fault simulation results.

[0103] like Figure 12 As shown, a sudden fault occurred at the wind farm at approximately 82 seconds, resulting in a step drop in output power. This resulted in a significant deviation between the actual power output at the power station and the AGC commands. The solution is to first activate the energy storage dynamic fine-tuning mechanism, leveraging the rapid charging and discharging capabilities of the energy storage units to quickly compensate for the output deviation. Simulation results show that the fault recovery process takes only 1.6 seconds.

[0104] Further by Figure 13 As shown in the fault-tolerance process, after a fault occurs, the residual sequence exhibits a negative shift. Based on the improved bidirectional CUSUM algorithm, when the negative bias statistic... When the threshold is exceeded, a fault is initially identified. At this point, the fault characteristics do not yet meet the unit fault determination mode of the structure matrix F, so the incremental instruction correction stage is entered, and a fault mitigation instruction is issued. After the mitigation period ends, the fault detection stage is entered again. Since the residual statistics have fallen back to the normal range at this time, the fault is determined to be eliminated (it is a unit fault rather than a communication fault). The fault type is determined by the secondary fault determination result, and the fault mitigation operation is continued, demonstrating the effective closed loop of the proposed "two-stage detection + classification mitigation feedback" fault-tolerant logic.

[0105] like Figure 14As shown, after a communication failure, the system achieved rapid response and stable recovery through a fault-tolerant mechanism. The total station power deviation exhibited a step disturbance in the early stages of the fault, but converged within 1.6 seconds and remained within ±2% throughout the process.

[0106] In addition, such as Figure 15 As shown, around 30 seconds, the AGC command was lowered, causing the wind farm to reduce its output power and the wind curtailment rate to increase in stages; around 82 seconds, the wind farm experienced a sudden fault, resulting in... Figure 15 The power deviation shown led to an increase in the wind curtailment rate again; the fault mitigation mechanism was triggered around 92s, increasing the power command of the wind farm, and the energy storage simultaneously dropped slightly back to the maximum charging boundary, reducing the wind curtailment rate by 3.24%, balancing wind power absorption rate, tracking accuracy and system stability.

[0107] 5. Analysis of communication fault simulation results.

[0108] Under the wind power priority allocation strategy, this section constructs a wind farm communication failure scenario to verify the dynamic response capability of the proposed fault-tolerant control strategy.

[0109] like Figure 16 As shown, approximately 24 seconds prior, the wind farm was in a communication outage state. However, because the AGC command remained constant during this period, the wind farm maintained its original output level, making it impossible to identify the fault through power response; thus, it was in a fault-concealing period. Around 24 seconds after the AGC command was raised, the energy storage power response was first improved through a dynamic fine-tuning mechanism, while simultaneously raising the wind power output command. As the overall power of the wind-solar-storage integrated system entered a steady state, a significant deviation persisted between the actual wind farm power generation and its control command, triggering a fault-tolerant control strategy.

[0110] Further by Figure 17 As shown in the fault-tolerance process, the fault-tolerance control mechanism 40 seconds prior is consistent with the strategy under the aforementioned unit failure scenario, completing the initial fault determination and executing mitigation operations. However, after the mitigation period, the system initiates a secondary bidirectional CUSUM residual detection. The wind farm residual signal continuously exhibits a negative offset and rapidly exceeds the threshold H, leading the system to determine that a fault exists again. At this point, the residual characteristics satisfy the matching pattern of communication faults in the structure matrix F, and the system enters the communication fault mitigation phase. Figure 16 The fault mitigation command is restored, the mode switching flag is set to exit control, and the control command is reconstructed. The wind power command is restored to the current AGC target level to reduce the risk of power fluctuations during the fault recovery process. The energy storage power gradually decreases back to the maximum charging boundary, and the photovoltaic power station correspondingly increases its output, effectively filling the power gap caused by wind power de-control and improving the renewable energy consumption rate.

[0111] Around 104 seconds, the wind farm's communication failure was gradually resolved, and the photovoltaic power station adjusted accordingly. When the wind farm's deviation entered the dead zone, the fault flag was reset to zero, and the wind farm re-entered the joint control mode.

[0112] like Figure 18 As shown, the fault-tolerant control strategy proposed in this application can achieve rapid response after a fault occurs. At the moment of fault triggering, the power deviation of the entire station experiences a brief spike, but it quickly converges to within ±2% within 1.1 seconds and maintains stable fluctuations throughout the entire fault duration. In addition, such as Figure 19 As shown, after the communication failure mitigation measures were triggered at 32 seconds, the curtailment rate of solar power began to decrease, decreasing by 20.50% compared to before the failure. After 110 seconds, the wind farm's output gradually recovered, and the curtailment rate of wind power also decreased by 5.45% compared to before, with the curtailment rate of solar power returning to the level before the failure.

[0113] The above results show that the fault-tolerant control strategy provided in this application not only achieves effective identification and classification response to communication faults, but also further improves the utilization efficiency of new energy resources while ensuring the stable operation of the wind-solar-storage integrated system.

[0114] Based on the same inventive concept, this application also provides an automatic power generation control system for a wind-solar-storage integrated system. This system can implement the automatic power generation control method for a wind-solar-storage integrated system described above. The solution provided by this system is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more embodiments of the automatic power generation control system for a wind-solar-storage integrated system provided below can be found in the limitations of the method above, and will not be repeated here.

[0115] In one exemplary embodiment, such as Figure 2 As shown, an automatic power generation control system for a wind-solar-storage integrated system is provided, comprising: The fault diagnosis module, connected to the wind-solar-storage integrated system, is used to acquire the system's commands and measured active power values. It also determines residual values ​​based on these values, determines residual statistics, and finally obtains residual fault detection results based on the residual statistics and threshold rules.

[0116] The main control module, connected to both the fault diagnosis module and the wind-solar-storage integrated system, is used to generate correction commands based on residual fault detection results using fault mitigation strategies. The main control module also determines allocation strategies based on input commands. Furthermore, it determines AGC commands for wind farms, photovoltaic power plants, and energy storage power plants based on the allocation strategies and correction commands.

[0117] As an optional implementation, the main control module includes an instruction reconfiguration unit and a controller unit.

[0118] The instruction reconfiguration unit is connected to both the fault diagnosis module and the controller unit. The controller unit is connected to the wind-solar-storage integrated system.

[0119] The instruction refactoring unit is used to obtain corrective instructions based on residual fault detection results using fault mitigation strategies.

[0120] The controller unit is used to determine the allocation strategy based on input instructions. The controller unit is also used to determine AGC instructions for wind farms, photovoltaic power plants, and energy storage power plants based on the allocation strategy and correction instructions.

[0121] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0122] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0123] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0124] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0125] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0126] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An automatic power generation control method for a wind-solar-storage integrated system, characterized in that, include: The system acquires commands and measured active power values ​​of the wind-solar-storage integrated system in real time; the integrated system includes a wind farm, a photovoltaic power station, and an energy storage power station. The residual value is determined based on the command and measured active power values ​​of the wind-solar-storage integrated system. Determine the residual statistics based on the residual values; The residual fault detection results are obtained based on the residual statistics and threshold rules. A fault mitigation strategy is adopted to obtain a correction instruction based on the residual fault detection results; The allocation strategy is determined based on the input instructions; The allocation strategies include wind power priority strategy, photovoltaic priority strategy, and wind-solar ratio strategy; Based on the allocation strategy and the correction instructions, AGC instructions for wind farms, photovoltaic power plants, and energy storage power plants are determined; the AGC instructions for wind farms are used to control the operation of the wind farms; the AGC instructions for photovoltaic power plants are used to control the operation of the photovoltaic power plants; and the AGC instructions for energy storage power plants are used to control the operation of the energy storage power plants.

2. The automatic power generation control method for a wind-solar-storage integrated system according to claim 1, characterized in that, The process of determining the residual value based on the command and measured active power values ​​of the wind-solar-storage integrated system includes: Obtain historical operational data of the wind-solar-storage integrated system; The ARX parameters of the ARX model are determined based on the historical operating data in order to construct an ARX prediction model; The active power prediction value is determined by using the ARX prediction model based on the instructions of the wind-solar-storage combined system. The residual value is determined based on the predicted active power value and the measured active power value.

3. The automatic power generation control method for a wind-solar-storage integrated system according to claim 1, characterized in that, The process of obtaining residual fault detection results based on the residual statistics and threshold rules includes: The initial fault determination result is obtained based on the residual statistics and the threshold rule; When the residual statistics do not meet the threshold rule, the initial fault determination result is that no fault has occurred. When the residual statistics meet the threshold rule, the initial fault determination result is that a unit fault has occurred, and the instructions of the wind-solar-storage combined system are adjusted to obtain new instructions for the wind-solar-storage combined system. A new residual statistic is determined based on the new wind-solar-storage integrated system instructions and the measured active power value of the new wind-solar-storage integrated system; a secondary fault determination result is obtained based on the new residual statistic and the threshold rule; the secondary fault determination result is either a fault occurred or no fault occurred. The residual fault detection result is obtained based on the initial fault determination result and the secondary fault determination result; the residual fault detection result is no fault, communication fault, or unit fault.

4. The automatic power generation control method for a wind-solar-storage integrated system according to claim 3, characterized in that, The fault mitigation strategy includes a unit fault mitigation mechanism and a communication fault mitigation mechanism; The fault mitigation strategy, based on the residual fault detection results, generates a correction instruction, including: When the residual fault detection result is a communication fault, the correction instruction is obtained by using the communication fault mitigation mechanism; When the residual fault detection result is a unit fault, the correction instruction is obtained by using the unit fault mitigation mechanism.

5. The automatic power generation control method for a wind-solar-storage integrated system according to claim 1, characterized in that, During the process of controlling the operation of the wind farm, the photovoltaic power station and the energy storage power station respectively using the wind farm AGC command, the photovoltaic power station AGC command and the energy storage power station AGC command, the determination of whether the correction command meets the set conditions is based on the measured active power value of the wind-solar-storage combined system; When the set conditions are met, the wind farm AGC command and the photovoltaic power station AGC command are frozen, the energy storage power station AGC command is corrected to obtain the corrected energy storage power station AGC command; the corrected energy storage power station AGC command is verified using boundary constraint conditions to obtain the updated energy storage power station AGC command; the updated energy storage power station AGC command is used to control the operation of the energy storage power station.

6. The automatic power generation control method for a wind-solar-storage integrated system according to claim 1, characterized in that, The wind power priority strategy is expressed as follows: ； In the formula, This indicates a wind power priority strategy. Represents the set of key parameters. This represents the set of prerequisite attributes for a wind power priority strategy. This represents the set of wind power priority strategy allocation results. The logical function representing the wind power priority strategy.

7. The automatic power generation control method for a wind-solar-storage integrated system according to claim 1, characterized in that, The photovoltaic priority strategy is expressed as follows: ； In the formula, This indicates a photovoltaic-first strategy. Represents the set of key parameters. This represents the set of prerequisite attributes for a photovoltaic-first strategy. This represents the set of allocation results for the photovoltaic priority strategy. The logical function representing the photovoltaic priority strategy.

8. The automatic power generation control method for a wind-solar-storage integrated system according to claim 1, characterized in that, The process of constructing the threshold rule includes: Obtain the mean of the first expected residual and the mean of the second expected residual; The threshold is determined based on the mean of the first expected residual and the mean of the second expected residual; The threshold rule is constructed based on the threshold.

9. An automatic power generation control system for a wind-solar-storage integrated system, characterized in that, include: The fault diagnosis module is connected to the wind-solar-storage integrated system and is used to obtain the instructions and measured active power values ​​of the integrated system. The fault diagnosis module is further used to determine the residual value based on the command and measured active power value of the wind-solar-storage integrated system; the fault diagnosis module is further used to determine the residual statistic based on the residual value; the fault diagnosis module is further used to obtain the residual fault detection result based on the residual statistic and threshold rules; The main control module is connected to the fault diagnosis module and the wind-solar-storage integrated system, respectively, and is used to obtain correction instructions based on the residual fault detection results using a fault mitigation strategy; the main control module is also used to determine the allocation strategy based on the input instructions; the main control module is also used to determine the AGC instructions for the wind farm, the AGC instructions for the photovoltaic power station, and the AGC instructions for the energy storage power station based on the allocation strategy and the correction instructions.

10. The automatic power generation control system for a wind-solar-storage integrated system according to claim 9, characterized in that, The main control module includes an instruction reconfiguration unit and a controller unit; The instruction reconfiguration unit is connected to both the fault diagnosis module and the controller unit; the controller unit is connected to the wind-solar-storage integrated system. The instruction reconstruction unit is used to obtain a correction instruction based on the residual fault detection result using a fault mitigation strategy. The controller unit is used to determine the allocation strategy based on input instructions; The controller unit is also used to determine AGC instructions for wind farms, AGC instructions for photovoltaic power plants, and AGC instructions for energy storage power plants based on the allocation strategy and the correction instructions.

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