Active control method of distributed new energy station and related equipment

Abstract

The invention relates to the technical field of power systems, and discloses an active control method and related equipment for a distributed new energy station, and the method comprises the steps: receiving an active adjustment instruction issued by a main station through an edge gateway, verifying the active adjustment, and generating verified instruction data; dynamically selecting a control mode based on the verified instruction data and the real-time operation state of the new energy station, and adjusting the active power output of the power generation equipment according to the control mode; and triggering a corresponding safety protection strategy after detecting that the power grid operates abnormally so as to isolate the abnormities according to the safety protection strategy and maintain stable operation of the power grid. Accuracy, timeliness, flexibility and safety of active control of the distributed new energy station can be improved, stable operation in a complex and changeable power grid environment can be ensured, and stability and reliability of power grid operation are improved.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to an active power control method and related equipment for a distributed new energy station. Background Art

[0002] With the widespread adoption of distributed renewable energy stations in power systems, their active power control plays a vital role in ensuring the stable operation of the power grid. However, existing active power control technologies for distributed renewable energy stations suffer from the following deficiencies: During command reception, communication network delays or interference often prevent commands from reaching the control system in a timely and accurate manner, impacting real-time grid regulation. The lack of verification and error correction mechanisms can also lead to erroneous operations, threatening equipment and grid security. Regarding command execution, existing methods lack flexibility and accuracy, making it impossible to dynamically adjust to the station's actual operating status. Furthermore, the lack of real-time monitoring and feedback makes it difficult to detect and address anomalies in a timely manner. Furthermore, in emergencies, such as grid failures or communication interruptions, existing technologies lack comprehensive safety strategies. Stations may fail to respond correctly and continue to execute the original commands or operate in a disorderly manner, impacting the safety of their own equipment and potentially disrupting grid stability, triggering a chain reaction. Specifically, existing technologies suffer from untimely and unstable command reception, inflexible and inaccurate execution, and a lack of effective emergency safety strategies.

[0003] The preceding description is intended to provide general background information and does not necessarily constitute prior art. Summary of the Invention

[0004] The embodiments of the present application provide an active power control method and related equipment for a distributed new energy station, which receives and verifies the master station instructions through the edge gateway and dynamically selects the control mode to adjust the output of the power generation equipment. At the same time, it triggers the safety protection strategy when the power grid is abnormal, ensuring the efficiency, flexibility, accuracy and safety of the active power control of the distributed new energy station, and improving the stability and reliability of the power grid operation.

[0005] In a first aspect, an embodiment of the present application provides a method for controlling active power of a distributed new energy station, including:

[0006] Receiving active power regulation instructions issued by the master station through the edge gateway, verifying the active power regulation, and generating verified instruction data;

[0007] Based on the verified command data and the real-time operating status of the new energy station, dynamically select a control mode and adjust the active power output of the power generation equipment according to the control mode;

[0008] After detecting abnormal operation of the power grid, a corresponding safety protection strategy is triggered to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

[0009] Optionally, in some embodiments of the present application, the receiving, through the edge gateway, the active power adjustment instruction issued by the master station, verifying the active power adjustment, and generating verified instruction data includes:

[0010] Build redundant communication links including wireless communication and power distribution data networks, and dynamically switch between primary and backup channels based on network latency or signal quality;

[0011] The received active power regulation command is subjected to parity check and Hamming code check in sequence. If the check fails, the command retransmission mechanism is triggered until the check passes or an alarm is generated after the preset number of retransmissions is reached.

[0012] The verified active power regulation instructions are matched and analyzed with the real-time electrical parameters of the station. If the instructions exceed the equipment adjustment range or conflict with the current operating status, the abnormality is fed back to the master station and the instruction correction is requested.

[0013] Optionally, in some embodiments of the present application, the dynamic selection control mode includes:

[0014] If the control mode is the master station remote adjustment mode, the real-time active power target value issued by the master station is directly executed;

[0015] If the control mode is the master station planned value mode, the power generation planned value issued by the master station is executed according to the preset time period;

[0016] If the control mode is the station autonomous mode, the control target value is set autonomously based on the status of local power generation equipment and historical data.

[0017] Optionally, in some embodiments of the present application, adjusting the active power output of the power generation equipment according to the control mode includes:

[0018] For stations with flexible remote control of active power generation, the edge gateway proportionally allocates the active power control target value of each generating unit based on the active power control target value of the entire station and the real-time output of the generating unit, and sends it to the corresponding control device;

[0019] For stations that only have switch remote control functions, the grid connection point switch or grid connection point branch switch measurement and control device is controlled through the edge gateway, and control of the grid connection point switch is prohibited;

[0020] The deviation between the actual output and the active power control target value is monitored through a closed-loop feedback mechanism, and the control parameters are dynamically adjusted.

[0021] Optionally, in some embodiments of the present application, monitoring the deviation between the actual output and the active power control target value through a closed-loop feedback mechanism and dynamically adjusting the control parameters includes:

[0022] Collect the actual active power data of each power generation unit in the station in real time, compare it with the active power control target value, and calculate the corresponding deviation value;

[0023] Dynamically adjust the control parameters of the inverter or wind turbine controller according to the size and change trend of the deviation value, wherein the control parameters include proportional coefficient, integral time or adjustment step size;

[0024] The control parameters are continuously optimized through an iterative feedback loop until the actual active power data is within the error range of the active power control target value.

[0025] Optionally, in some embodiments of the present application, triggering a corresponding security protection strategy after detecting abnormal operation of the power grid, so as to isolate the abnormality and maintain stable operation of the power grid according to the security protection strategy, includes:

[0026] When it is detected that the voltage, frequency or power at the grid connection point exceeds the safety threshold, it automatically switches to the local safety mode and blocks the master station command;

[0027] When communication interruption is detected, the last valid instruction is maintained or control is suspended, and after communication is restored, the active power control target value is gradually transitioned through gradient adjustment;

[0028] The instructions issued by the master station are checked for interval limits, adjustment steps and gradients, and instructions that exceed the preset safety range are refused to be executed.

[0029] Optionally, in some embodiments of the present application, performing interval limit, adjustment step, and gradient verification on the active power regulation instructions issued by the master station and refusing to execute instructions that exceed a preset safety range includes:

[0030] Performing a set value interval check on the active power regulation instruction; if the active power set value issued by the dispatcher exceeds the pre-set reasonable interval limit, the active power regulation instruction is rejected;

[0031] The active power regulation instruction is checked for the adjustment step length. If the set value issued by the dispatching master station and the actual measured value of the control target exceed the maximum adjustment step length, the active power regulation instruction is rejected;

[0032] The active power regulation instruction is subjected to a set value gradient check. If the current set value issued by the dispatching master station and the last reasonable set value exceed the maximum regulation gradient, the active power regulation instruction is rejected.

[0033] In a second aspect, an embodiment of the present application provides an active power control device for a distributed new energy station, comprising:

[0034] An adjustment instruction module is used to receive the active power adjustment instruction issued by the master station through the edge gateway, verify the active power adjustment, and generate verified instruction data;

[0035] A regulation control module, configured to dynamically select a control mode based on the verified command data and the real-time operating status of the new energy station, and to regulate the active power output of the power generation equipment according to the control mode;

[0036] The safety protection module is used to trigger the corresponding safety protection strategy after detecting abnormal operation of the power grid, so as to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

[0037] In a third aspect, an embodiment of the present application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the active power control method of the distributed new energy station as described in the first aspect are implemented.

[0038] In a fourth aspect, an embodiment of the present application further provides a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements the computer program of the active power control method of the distributed new energy station as described in the first aspect.

[0039] The present application provides a method and related equipment for active power control of a distributed new energy station. First, the active power regulation instruction issued by the master station is received through the edge gateway and the instruction is verified to generate the verified instruction data to ensure the accuracy and reliability of the regulation instruction. Then, based on the verified instruction data and the real-time operation status of the new energy station, the control mode is dynamically selected, and the active power output of the power generation equipment is adjusted according to the control mode to achieve accurate and flexible control of the power generation equipment and improve the performance and reliability of active power control. At the same time, after detecting the abnormal operation of the power grid, the corresponding safety protection strategy is triggered, and the abnormality is isolated according to the safety protection strategy and the stable operation of the power grid is maintained to ensure the safety of the system operation, effectively improving the adaptability and safe and stable operation level of the distributed new energy station under complex working conditions. It can be seen that the active power control scheme of the distributed new energy station provided by the present application improves the active power control capability of the distributed new energy station from aspects such as instruction reception, control execution and safety protection, effectively improves the accuracy, timeliness, flexibility and safety of the active power control of the distributed new energy station, ensures stable operation in a complex and changeable power grid environment, and thus improves the stability and reliability of the power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 This is an application environment diagram of the active power control method of the distributed new energy station provided in the embodiment of the present application;

[0042] Figure 2 This is a flow chart of the active power control method of the distributed new energy station provided in the embodiment of the present application;

[0043] Figure 3 1 is a flow chart of receiving an active power regulation instruction provided in an embodiment of the present application;

[0044] Figure 4 This is a flow chart of checking and correcting errors in received instructions provided by an embodiment of the present application;

[0045] Figure 5 This is a flow chart of the control mode and control execution of a new energy station provided in an embodiment of the present application;

[0046] Figure 6 This is a flow chart of the safety protection strategy design for new energy stations provided in the embodiment of the present application;

[0047] Figure 7 This is another flowchart of the active power control method of the distributed new energy station provided by the embodiment of the present application;

[0048] Figure 8 This is a structural diagram of an active power control device for a distributed new energy station provided in an embodiment of the present application;

[0049] Figure 9 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of systems and methods consistent with aspects of the present application, as detailed in the appended claims.

[0051] It should be noted that, in this document, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive descriptions such as inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0052] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0053] In the subsequent description, the use of suffixes such as "module", "component" or "unit" to represent elements is only for the purpose of facilitating the description of the present application and has no specific meaning. Therefore, "module", "component" or "unit" can be used interchangeably.

[0054] When receiving active power control commands, existing technologies may suffer from issues such as delayed and unstable reception. For example, due to delays or interference in the communication network, commands may not reach the control system of the renewable energy station accurately and quickly, resulting in delayed control actions and impacting the real-time regulation requirements of the power grid. Furthermore, the lack of effective verification and error correction mechanisms during command reception can easily lead to erroneous control operations due to command errors, posing a threat to station equipment and power grid security. Existing methods for executing active power control commands are often inflexible and inaccurate. On the one hand, the execution process may not be dynamically adjusted to the actual operating status of the renewable energy station. For example, optimal active power output control cannot be achieved under varying conditions such as light intensity and wind speed. On the other hand, the lack of real-time monitoring and feedback mechanisms during the execution process prevents timely detection and adjustment of abnormalities during execution. Furthermore, most existing technologies lack comprehensive safety strategies for emergencies such as power grid failures and communication interruptions. New energy stations may not be able to respond quickly and correctly, and may continue to execute according to the original instructions or enter a disorderly operation state. This will not only affect the safety of their own equipment, but may also cause serious damage to the stability of the power grid, triggering chain reactions such as voltage fluctuations, frequency imbalances and other problems, and may even cause large-scale power outages.

[0055] In order to solve the above-mentioned technical problems and overcome the defects of the existing technology, the embodiment of the present application provides an active power control method and related equipment for a distributed new energy station, which receives and verifies the master station instructions through the edge gateway and dynamically selects the control mode to adjust the output of the power generation equipment. At the same time, it triggers the safety protection strategy when the power grid is abnormal, ensuring the efficiency, flexibility, accuracy and safety of the active power control of the distributed new energy station, and improving the stability and reliability of the power grid operation.

[0056] Figure 1 FIG. 1 is an application environment diagram of a method for controlling active power of a distributed new energy station in an embodiment. Figure 1 , the active power control method of the distributed new energy station is applied to the active power control system of the distributed new energy station. The active power control system of the distributed new energy station includes a terminal 110 and a server 120. The terminal 110 and the server 120 are connected through a network. The terminal 110 can be a desktop terminal or a mobile terminal. The mobile terminal can be at least one of a mobile phone, a tablet computer, a laptop computer, etc. The server 120 can be implemented as an independent server or a server cluster composed of multiple servers. The server 120 is used to receive the active power adjustment instructions issued by the master station through the edge gateway, verify the active power adjustment, and generate verified instruction data; based on the verified instruction data and the real-time operating status of the new energy station, dynamically select the control mode, and adjust the active power output of the power generation equipment according to the control mode; trigger the corresponding safety protection strategy after detecting the abnormal operation of the power grid, so as to isolate the abnormality according to the safety protection strategy and maintain the stable operation of the power grid.

[0057] See also Figure 2 , Figure 2 : This is a flow chart of a method for controlling active power of a distributed renewable energy station provided by an embodiment of the present application. This embodiment mainly uses the application of the method for controlling active power of a distributed renewable energy station to a computer device as an example. The method for controlling active power of a distributed renewable energy station provided by an embodiment of the present application may specifically include the following steps:

[0058] S1 receives the active power regulation command issued by the master station through the edge gateway, verifies the active power regulation, and generates the verified command data;

[0059] Specifically, in step S1, the edge gateway, acting as a key hub, utilizes technologies such as 5G high-speed wireless communications and a protocol stack compatible with various power industry standards to capture the active power regulation command signals issued by the master station. A combination of parity and Hamming code verification algorithms is used to rigorously verify the integrity and accuracy of the active power regulation commands. If a problem is detected, a command retransmission mechanism is triggered until the verification passes or a preset number of retransmissions is reached, generating an alarm.

[0060] In terms of communication network optimization, high-speed wireless communication technology can be combined with the power distribution data network to build redundant communication links. A network traffic monitoring and control system can also be deployed to dynamically allocate network resources, prioritizing bandwidth for active power regulation command transmission. To enhance edge gateway functionality, a command buffer can be set up to temporarily store received commands, perform preliminary parsing and preprocessing, extract key information, compare and analyze it with the current operating status parameters of the station, determine the rationality of the command, and promptly report any problems to the master station.

[0061] S2. Dynamically select the control mode based on the verified command data and the real-time operating status of the new energy station, and adjust the active power output of the power generation equipment according to the control mode;

[0062] Specifically, for step S2, the substations of the new energy station have two mutually exclusive control modes: master station regulation and station control, which can be flexibly selected based on actual conditions. During the control execution phase, based on different control modes, the characteristics of the station's internal power generation units, and the real-time status of the external power grid, advanced algorithms such as model-based predictive control (MPC) and adaptive neural fuzzy inference systems (ANFIS) are used to fine-tune and optimize the operating parameters of the power generation equipment, thereby effectively regulating the active power output of the power generation equipment.

[0063] In terms of control mode design, in addition to the three modes of master station remote regulation, master station planned value adjustment, and site control, control modes can be further refined and expanded to accommodate more complex operating conditions. In terms of control execution, more advanced control algorithms, such as fuzzy control algorithms, genetic algorithms, and particle swarm optimization algorithms, can be explored and applied to further improve control precision and reliability. At the same time, the control logic and regulation strategies of power generation equipment can be optimized. Based on the different types of power generation equipment and operational requirements, more reasonable regulation methods and procedures can be developed to ensure stable and efficient operation of power generation equipment under different control modes.

[0064] S3. After detecting abnormal operation of the power grid, trigger the corresponding security protection strategy to isolate the abnormality and maintain stable operation of the power grid according to the security protection strategy;

[0065] Specifically, in step S3, if a situation threatens the station's operational safety, such as when the grid-connected active power, voltage, or frequency exceeds fault limits, the substation's operating state automatically switches to exit mode, the control mode automatically switches to power plant control mode, and a timely alarm is issued. Manual control recovery is required after normal operating conditions return to normal. In abnormal situations, such as loss of communication with the master station, the substation enters a suspended control state for safety, maintaining the last command or automatically suspending control to prevent erroneous operations due to missing commands. Once the abnormal situation is resolved, the substation automatically resumes regulation, and the default command after restoration is the measured total active power value of the station.

[0066] In terms of safety and protection strategies, the indicators and thresholds for anomaly detection can be further refined and expanded to improve the accuracy and sensitivity of detecting abnormal grid operations. In addition to existing strategies such as automatic exit and lockout control, additional safety and protection measures can be researched and designed, such as fault recording, emergency plan activation, and intelligent fault diagnosis, to more effectively address various complex abnormal situations. Furthermore, a comprehensive fault alarm and recording system should be established to provide timely feedback to operations and maintenance personnel regarding abnormalities, facilitating rapid fault location and resolution, further improving system reliability and safety.

[0067] This embodiment ensures the accuracy and timeliness of active power regulation instructions by optimizing the receiving process. It dynamically selects and executes control modes based on the real-time operating status of the station, achieving precise and flexible regulation of the active power output of power generation equipment and improving the grid's ability to accept and utilize new energy. At the same time, it triggers safety protection strategies when the grid operates abnormally, effectively ensuring the safe and stable operation of the station and the grid. Comprehensively improving the active power control performance and reliability of distributed new energy stations, enabling them to better adapt to the requirements of modern power grids for efficient and stable access to distributed new energy, is of great significance for promoting the reliable application and sustainable development of distributed new energy in power systems, and driving the power industry towards a clean, efficient, and intelligent direction.

[0068] Optionally, in some embodiments, step S1 of “receiving, through the edge gateway, the active power adjustment instruction issued by the master station, verifying the active power adjustment, and generating verified instruction data” may specifically include:

[0069] S11. Build redundant communication links that include wireless communication and power distribution data networks, and dynamically switch between primary and backup channels based on network latency or signal quality.

[0070] Specifically, to ensure that active power regulation instructions can reach the distributed new energy station control system quickly and accurately, a redundant communication link including 5G high-speed wireless communication and distribution data network has been built. The system monitors the network latency and signal quality of the primary and backup links in real time, and automatically switches to the optimal link based on the preset switching threshold to ensure the continuity and stability of instruction transmission. For example, when the 5G network signal is weak or the latency is high, it quickly switches to the distribution data network link to transmit instructions. In addition to the existing combination of 5G and distribution data network, other high-speed communication technologies, such as Wi-Fi 6, can also be introduced as supplementary links to further improve the flexibility and reliability of communications. At the same time, more advanced network quality monitoring algorithms and switching logic, such as machine learning-based prediction models, are used to predict link status changes in advance, achieve smoother and more timely switching, and reduce transmission interruptions caused by switching.

[0071] S12. The received active power regulation command is subjected to parity check and Hamming code check in sequence. If the check fails, the command retransmission mechanism is triggered until the check passes, or an alarm is generated after the preset number of retransmissions is reached;

[0072] Specifically, at the command receiving end, a parity check algorithm is first used to verify the parity of the command data, quickly screening out commands that may contain errors. Subsequently, a Hamming code check algorithm is used for further verification of the command, not only detecting errors but also correcting them to a certain extent. If a command verification failure is detected, the system automatically triggers the command retransmission mechanism and sends a retransmission request to the master station. Upon receiving the request, the master station resends the command and records the number of retransmissions. If the number of retransmissions exceeds a set threshold (for example, three), the system generates an alarm, notifying operations and maintenance personnel to intervene and ensure the accuracy and reliability of the command. In addition to parity and Hamming code checks, more advanced forward error correction (FEC) technologies, such as low-density parity check (LDPC) or polar codes, can be introduced to further improve command error correction capabilities and transmission reliability. Furthermore, the command retransmission mechanism can be optimized, such as by adopting a strategy that dynamically adjusts the retransmission interval and number of retransmissions based on network congestion and command priority, thereby improving retransmission efficiency.

[0073] S13. Match the verified active power regulation command with the real-time electrical parameters of the station. If the command exceeds the equipment adjustment range or conflicts with the current operating status, the abnormality is reported to the master station and a command correction is requested.

[0074] Specifically, after receiving a verified instruction, the edge gateway compares and analyzes it with the real-time electrical parameters of the station (such as the active output of the power generation equipment, the voltage and frequency of the grid connection point, etc.). For example, if the active output required by the instruction exceeds the maximum adjustment range of the power generation equipment, or does not match the current grid connection point voltage, frequency and other parameters, which may cause the equipment to overload or unstable operation, the edge gateway will promptly feedback the abnormal situation to the main station and request the main station to reconfirm or adjust the instruction to prevent unreasonable instructions from entering the execution link. Using big data analysis and machine learning algorithms, a station operation status model is established to evaluate the rationality and feasibility of instructions in real time, thereby improving the accuracy and efficiency of anomaly detection. At the same time, an automatic instruction correction algorithm is designed to make appropriate adjustments to the instructions according to the real-time status of the station, reduce dependence on the main station, and improve the autonomy and response speed of the system.

[0075] This embodiment ensures high-precision and high-reliability reception and processing of active power regulation commands by establishing redundant communication links, employing a multi-level command verification mechanism, and intelligent command analysis and feedback. This not only improves the stability and reliability of command transmission, but also enhances the system's ability to identify and process abnormal commands, effectively avoiding control errors caused by communication problems or command errors, and ensuring the accuracy and timeliness of active power control at distributed renewable energy stations.

[0076] In a specific embodiment, in a specific embodiment, as Figure 3 As shown, Figure 3 A flow chart of a method for receiving an active power regulation instruction is provided.

[0077] In the complex operating system of distributed renewable energy stations, receiving active power regulation commands is a critical step in ensuring grid stability and efficient renewable energy utilization. The core executors are the control devices within these stations, particularly the edge gateways. As the source of these commands, the master station transmits them to the station via wireless or distribution data networks. The edge gateway, with its powerful data processing and communication capabilities, plays a pivotal role in this process. It utilizes 5G high-speed wireless communications and a protocol stack compatible with multiple power industry standards to capture command signals from the master station. Furthermore, it rigorously verifies the integrity and accuracy of received commands using parity and Hamming code algorithms to ensure they are correct. Upon receiving the command, the edge gateway performs preliminary analysis and plausibility assessment based on the station's real-time operating status, including the active power output of the generating equipment and the electrical parameters of the grid connection point. This lays the foundation for subsequent, precise execution.

[0078] In terms of receiving active power regulation instructions, the specific process includes:

[0079] 1) Communication network optimization.

[0080] ① Build redundant communication links by combining high-speed wireless communication technology with the power distribution data network. 5G communication's high speed and low latency are leveraged as the primary communication channel, while the power distribution data network serves as a backup channel to ensure reliable command transmission. In areas with good 5G network coverage, commands are received preferentially via the 5G network. If the 5G signal is interfered with or interrupted, the system automatically switches to the power distribution data network to ensure continuous and stable command reception.

[0081] ② Deploy a network traffic monitoring and control system to monitor network traffic in real time during command transmission. Dynamically allocate network resources based on network load at different times, prioritizing bandwidth for active power regulation commands. During peak hours, when the grid frequently demands active power regulation from renewable energy stations, the system automatically reserves sufficient bandwidth for command transmission, avoiding delays caused by network congestion and ensuring timely delivery of commands to the station control system.

[0082] 2) Instruction verification and error correction mechanism.

[0083] A combination of parity check and Hamming code checking algorithms is used to verify and correct received commands. At the command transmitter, the corresponding parity bit is calculated based on the byte length and format of the command data and the parity check rules. This bit is then added to the end of the command data. A Hamming code encoding algorithm is then used to generate the Hamming code check bit information, which is then sent to the station along with the command.

[0084] A command retransmission mechanism has been established. When a command error is detected and cannot be corrected by the error correction program, a retransmission request is automatically sent to the master station. Upon receiving the request, the master station resends the command and records the number of retransmissions. If the number of retransmissions exceeds a set threshold, such as three, the system issues an alarm to notify operations and maintenance personnel to intervene, identify the cause of the failure during command transmission, and promptly resolve the problem to ensure reliable command reception.

[0085] Among them, such as Figure 4 As shown, Figure 4 This is a flowchart for checking and correcting errors in received instructions. The specific process includes parity check and Hamming code check.

[0086] For parity checking, as a preliminary screening, the sender calculates the parity bit by counting the number of "1"s in the command data. For odd parity, if the number of "1"s in the command data is even, a "1" is added to the end of the command data as a parity bit; if the number of "1"s is odd, a "0" is added. For even parity, if the number of "1"s in the command data is odd, a "1" is added as a parity bit; if the number of "1"s is even, a "0" is added.

[0087] The receiving end performs a parity check. After receiving the command, the edge gateway counts the command data (excluding the parity bit added by the sender) according to the same parity check rules (which must be consistent with the sender). If the number of "1"s counted does not match the check rules, the command is initially judged to be incorrect. If it does, the command is likely correct, but further Hamming code verification is required.

[0088] For Hamming code check, as a further accurate detection and error correction, the sender generates a Hamming code check bit. First, the number of bits of the Hamming code is determined. Assume that the data bits are n bits and the check bits are k bits. The following conditions must be met: k -k-1≥n. Based on the data bits and the determined check bit position, a specific algorithm is used to calculate the value of each check bit. For example, for a check bit P i, it will perform an XOR operation with a specific data bit to determine its value. The calculated Hamming code check bit information is added to the corresponding position in the instruction data and sent to the station together with the instruction.

[0089] The receiving end performs Hamming code checksum and error correction. After receiving the command, the edge gateway extracts the data bits and Hamming code check bits. Based on the Hamming code checksum rules, a series of exclusive-or operations are performed on the data bits and check bits. If all checksums are 0, the command is correct; if any checksum is not 0, the command is erroneous. If the erroneous bits can be successfully corrected, the command can continue to be processed. If the error cannot be corrected (e.g., multiple errors or exceeding the Hamming code error correction capability), the command retransmission mechanism is triggered.

[0090] 3) Enhanced edge gateway functions.

[0091] A command cache is set up on the edge gateway. Upon receiving an active power regulation command from the master station, the command is temporarily stored in the cache. The edge gateway performs preliminary parsing and preprocessing on the command in the cache, extracting key information such as command type, target value, and execution time. At the same time, a comparison and analysis is performed with the station's current operating status parameters (such as the active power output of the power generation equipment, the grid connection point voltage, and frequency) to determine the rationality and feasibility of the command. If a problem with the command is detected, such as a target value that exceeds the equipment's adjustment range or conflicts with the current operating status, timely feedback is provided to the master station, requesting the master station to reconfirm or adjust the command to prevent unreasonable commands from entering the execution phase. The edge gateway's communication protocol stack is optimized, adopting a communication protocol that supports multi-protocol conversion and adaptation. For example, it supports multiple common protocols in the power industry, such as Modbus and IEC 61850, and can automatically convert and adapt according to the communication protocol requirements of the master station and internal equipment at the station.

[0092] Optionally, in some embodiments, the dynamic selection of the control mode in step S2 may specifically include:

[0093] If the control mode is the master station remote adjustment mode, the real-time active power target value issued by the master station is directly executed;

[0094] Specifically, in master station remote control mode, upon receiving the real-time active power target value from the master station, the edge gateway immediately executes the command, adjusting the active power output of the power generation equipment to meet the real-time dispatch requirements of the power grid. This mode is suitable for scenarios where the power grid experiences large load fluctuations and requires rapid response. For example, when the grid experiences a sudden load peak, the master station can quickly issue a command to the new energy station to increase its active power output to maintain the grid's supply and demand balance. Further optimizations can be made to the command execution process in master station remote control mode, such as by introducing real-time data encryption technology to ensure the security of commands during transmission and execution, preventing malicious attacks and command tampering. Furthermore, artificial intelligence technology can be incorporated to pre-process and optimize the commands issued by the master station, improving their rationality and execution effectiveness. In master station remote control mode, distributed new energy stations can closely follow the master station's commands and quickly adjust their active power output, ensuring stable operation of the grid under various operating conditions and enhancing the grid's capacity to accommodate and utilize new energy resources.

[0095] If the control mode is the master station planned value mode, the power generation plan value issued by the master station will be executed according to the preset time period;

[0096] Specifically, in the master station planned value model, the master station formulates power generation plans for each station in advance based on the overall grid planning and forecasts, and distributes the corresponding planned power generation values ​​to the stations during preset time periods. After receiving the planned values, the edge gateway gradually adjusts the active power output of the power generation equipment according to the set time period to ensure that the station's power generation is consistent with the planned values. For example, based on the daily load curve, the master station can require the station to generate at full power during peak daytime load periods and reduce power generation during low nighttime load periods. To further optimize the master station planned value model, a rolling generation planning mechanism can be considered to dynamically adjust the planned power generation values ​​based on real-time grid status and meteorological conditions, improving the accuracy and adaptability of the plan. Furthermore, big data analysis technologies can be used to deeply mine historical power generation and grid load data to optimize power generation planning. The master station planned value model helps achieve orderly power generation at distributed renewable energy stations, improves the planning and predictability of grid operations, facilitates grid dispatching departments to plan operating modes in advance, reduces grid operation risks, and facilitates stable operation and equipment maintenance at renewable energy stations.

[0097] If the control mode is the station autonomous mode, the control target value is set autonomously based on the status of local power generation equipment and historical data;

[0098] Specifically, in the station autonomous mode, the edge gateway leverages local power generation equipment status monitoring data, energy reserves, and historical power generation data to autonomously determine appropriate active power control targets. For example, if it detects rising temperature or declining conversion efficiency of photovoltaic panels, the station can autonomously lower the active power output target to protect the equipment. Alternatively, it can use historical data to predict the power generation potential of the equipment under specific meteorological conditions and adjust the power generation plan accordingly. To further enhance the intelligence of the station autonomous mode, deep learning algorithms can be introduced to conduct more in-depth analysis and mining of local data, improving the accuracy and foresight of control target setting. Furthermore, information exchange between the station and surrounding stations or microgrids can be strengthened to achieve more extensive collaborative control and improve overall operational efficiency. The station autonomous mode provides stations with a degree of autonomy, enabling them to flexibly adjust power generation strategies based on local conditions, better adapt to complex and changing operating environments, and enhance the operational stability and service life of power generation equipment. It can also alleviate scheduling pressure on the master station and enable refined management of distributed renewable energy stations.

[0099] This embodiment, through the design of multiple control modes, enables distributed renewable energy stations to flexibly adjust their active power output according to different operating scenarios and requirements, achieving precise and efficient control of renewable energy stations. The master station remote adjustment mode ensures rapid response to real-time grid dispatch requirements, the master station planned value mode improves the planning and predictability of grid operations, and the station autonomous mode enhances the station's adaptability and autonomy to local operating conditions.

[0100] Optionally, in some embodiments, “adjusting the active power output of the power generation equipment according to the control mode” in step S2 may specifically include:

[0101] For stations with flexible remote control of active power generation, the edge gateway proportionally allocates the active power control target value of each generating unit based on the active power control target value of the entire station and the real-time output of the generating unit, and sends it to the corresponding control device;

[0102] Specifically, after receiving the station-wide active power control target value from the master station, the edge gateway assigns specific active power control target values ​​to each power generation unit according to a certain ratio (such as equipment capacity, efficiency, etc.) based on the real-time output of each power generation unit (such as photovoltaic inverters, wind turbines, etc.). These target values ​​are then sent to the corresponding control devices (such as inverter controllers, wind turbine pitch controllers, etc.) to achieve refined control of power generation equipment. Artificial intelligence algorithms, such as deep reinforcement learning, are introduced to optimize the active power control target value allocation strategy of power generation units in real time to adapt to complex and changing operating environments and further improve control accuracy and power generation efficiency. At the same time, collaborative control between power generation units is strengthened, and more optimized power distribution is achieved by establishing communication and coordination mechanisms between units.

[0103] For stations that only have switch remote control functions, the grid connection point switch or grid connection point branch switch measurement and control device is controlled through the edge gateway, and control of the grid connection point switch is prohibited;

[0104] Specifically, after receiving control commands from the master station, the edge gateway controls the station's grid-connection point switches or branch switch measurement and control devices, such as opening or closing, to adjust the station's active power output. At the same time, the system prohibits control operations on the grid-connection point switches to prevent grid failures caused by misoperation. Developing more intelligent switch control logic, such as adaptive control strategies based on the real-time status of the grid and station operating conditions, will improve the accuracy and timeliness of switch operations. Furthermore, enhancing the remote monitoring and diagnostic capabilities of switchgear will enable timely detection and resolution of equipment failures, thereby improving system reliability.

[0105] The deviation between the actual output and the active power control target value is monitored through a closed-loop feedback mechanism, and the control parameters are adjusted dynamically;

[0106] Specifically, the actual active power output data of each power generation unit in the station is collected in real time, compared with the active control target value, and the deviation value is calculated. According to the size and changing trend of the deviation value, the control parameters (such as proportional coefficient, integration time, adjustment step size, etc.) are dynamically adjusted, and the control parameters are continuously optimized through iterative feedback loops until the actual active power output meets the error range of the target value. Advanced control algorithms such as adaptive fuzzy control and neural network control are used to further improve the performance and adaptability of closed-loop feedback control. At the same time, combined with big data analysis technology, historical control data is mined and analyzed, and the control parameter adjustment strategy is optimized to improve control accuracy and response speed.

[0107] This embodiment achieves efficient and precise regulation of the active power of distributed renewable energy stations through refined control strategies designed for different station types and control requirements. For stations with flexible remote regulation functions, precise control at the power generation unit level is achieved. For stations with only switch remote control functions, safe and reliable switching operations are ensured. The closed-loop feedback mechanism further improves the control accuracy and stability.

[0108] Optionally, in some embodiments, the step of “monitoring the deviation between the actual output and the active power control target value through a closed-loop feedback mechanism and dynamically adjusting the control parameters” may specifically include:

[0109] Collect the actual active power data of each power generation unit in the station in real time, compare it with the active power control target value, and calculate the corresponding deviation value;

[0110] Specifically, in distributed new energy sites, each power generation unit (such as photovoltaic inverters, wind turbines, etc.) is equipped with a power sensor to collect actual active power data in real time. The edge gateway or site monitoring system collects this data and compares it with the active power control target value issued by the master station to calculate the deviation value. For example, if the target value is 100kW and the actual total output power collected is 95kW, the deviation value is -5kW. Introduce high-precision, high-frequency sampling technology, such as faster sensor sampling frequency and more accurate analog-to-digital converters, to improve data accuracy and real-time performance. At the same time, use edge computing technology to pre-process data locally to reduce data transmission volume and latency.

[0111] Dynamically adjust the control parameters of the inverter or wind turbine controller according to the size and change trend of the deviation value, including the proportional coefficient, integral time or adjustment step size;

[0112] Specifically, based on the calculated deviation value and its changing trend, the control system dynamically adjusts the control parameters of the inverter or wind turbine controller. For example, if the deviation value is large and continuously increasing, it indicates that the current control parameters are unable to effectively regulate the output power. In this case, the proportional coefficient can be increased or the integral time can be shortened to enhance the regulation force. If the deviation value is small and tends to be stable, the adjustment step size can be appropriately reduced to avoid overshoot. Advanced control algorithms, such as adaptive control algorithms or intelligent control algorithms (such as neural network control and fuzzy control), are used to automatically optimize control parameters based on real-time data to adapt to different operating conditions and scenarios. At the same time, an online adjustment mechanism for control parameters is established to dynamically optimize parameter settings based on historical data and real-time operating status.

[0113] The control parameters are continuously optimized through an iterative feedback loop until the actual active power data is within the error range of the active power control target value;

[0114] Specifically, the control system adopts an iterative feedback mechanism to continuously monitor the deviation between the actual output power and the target value, and recalculate the deviation value after each adjustment. If the deviation value is still outside the allowable error range, the control parameters are adjusted again according to the new deviation value to form a closed-loop feedback control. This process continues until the actual output power stabilizes within the allowable error range of the target value. For example, if the error range is set to ±2%, if after several adjustments, the actual output power always fluctuates within the range of ±2% of the target value, the control process is considered to have reached a stable state. Machine learning technologies, such as reinforcement learning algorithms, are introduced to optimize the iterative feedback strategy and improve the control convergence speed and accuracy by learning and analyzing historical control data. At the same time, combined with big data analysis technology, the long-term operation data of the station is mined to further optimize the adjustment strategy of the control parameters.

[0115] This embodiment achieves precise control of the active power of distributed renewable energy stations through a closed-loop feedback mechanism and iterative optimization strategy. Real-time data collection and comparison ensure accurate understanding of the station's operating status. Dynamic adjustment of control parameters improves the system's adaptability and robustness. The iterative feedback loop further optimizes the control effect and ensures high-precision tracking of the output power.

[0116] In a specific embodiment, Figure 5 As shown, Figure 5 This is a flow chart of the control mode and control execution process for a new energy station. This process is the key to converting received active power regulation commands into actual equipment operations. The control mode macroscopically determines the strategic direction of active power control. It specifies the source of commands and how control targets are set, serving as the guiding framework for control execution. Control execution, on the other hand, is the specific implementation path of the control mode. By utilizing advanced algorithms and techniques, combined with the characteristics of the station's internal power generation units and the real-time status of the external power grid, the objectives set by the control mode are converted into actual adjustments to the operating parameters of the power generation equipment.

[0117] For the control mode and control execution of new energy stations, the specific process is as follows:

[0118] 1) New energy station control mode design. The substation of the new energy station has two modes: main station regulation and station control. These two modes are mutually exclusive and only one can be used at a time.

[0119] ① Master Station Remote Control: Substations can accept and execute only remote control or remote control commands issued by the master station through real-time peak shaving, section control, and free generation modes. In this mode, the substation closely follows the master station's instructions, adjusting the station's active output to meet the grid's real-time dispatch requirements and ensure stable operation under various operating conditions.

[0120] ② Master Station Plan Value Adjustment: Substations receive and execute power generation plan value adjustment instructions issued by the master station. Based on the overall grid planning and forecast, the master station formulates power generation plans for each station in advance. Substations systematically adjust their active power according to these plans. For example, at different times of the day, based on changing load trends, the master station sends corresponding power generation plan values ​​to substations. Substations use these values ​​to precisely control station equipment and ensure optimal distribution and supply of power.

[0121] ③ Station Control: In this mode, the station's active power control target is set by the substation itself. The substation will comprehensively consider factors such as the operating status of the station's internal power generation equipment, energy reserves, and historical power generation data to independently determine a reasonable active power control target.

[0122] 2) Control execution of new energy stations. When the control command is successfully received, the control execution link is quickly started, fully combining the detailed characteristics of each power generation unit within the station and the real-time operating status of the external power grid, and using model predictive control (MPC) and adaptive neural fuzzy inference system (ANFIS) algorithms to fine-tune and optimize the operating parameters of the power generation equipment to ensure efficient regulation of active power. The MPC algorithm can effectively predict and optimize the future state of the system through precise system modeling, prediction and optimization solution; the ANFIS algorithm uses fuzzy logic to deal with the uncertainty and nonlinearity of the system. The combination of the two can better adapt to the complex operating environment and changing control requirements of new energy stations, and improve the accuracy and reliability of control. The specific adjustment method is as follows:

[0123] ① Distributed new energy stations with flexible remote regulation of active power generation:

[0124] Sites with local monitoring systems: After receiving the site-wide active power control target value from the master station, the edge gateway distributes it to the local monitoring system or the edge gateway for direct control. Based on the site-wide target value and the real-time output of the inverters connected to the PV data acquisition device, the active power control target value is proportionally allocated to each PV data acquisition device. The PV data acquisition device then allocates the active power control target value to each inverter based on the received target value and distributes it to the inverter, which then adjusts flexibly based on the received target value.

[0125] For sites without a local monitoring system, the edge gateway receives the site-wide active power control target value from the master station. Based on the site-wide target value and the real-time output of the inverters connected to the PV data acquisition device, the edge gateway proportionally allocates the active power control target value to each PV data acquisition device and sends it to the data acquisition device. The subsequent process is the same as for sites with a local monitoring system. Through layered allocation and flexible adjustment of the inverter, effective control of active power is achieved, ensuring that the site's power generation output meets grid requirements while improving the operating stability and energy conversion efficiency of the power generation equipment.

[0126] ② Distributed new energy stations with only switch remote control functions:

[0127] At sites with local monitoring systems: The edge gateway receives control commands from the master station and controls the grid connection point switch or the grid connection point branch switch measurement and control device, either through the local monitoring system or direct control by the edge gateway. Control of the grid connection point switch is prohibited. During this process, the control logic of the measurement and control device is optimized using advanced algorithms to ensure accurate and timely switching operations.

[0128] For stations without a local monitoring system, the edge gateway receives control commands from the master station and directly controls the grid-connection point switch or the measurement and control device for the grid-connection point branch switch. Control of the grid-connection point switch is also prohibited. By precisely controlling the on / off states of the switches, the station's active power can be rigidly regulated, ensuring that the station can adjust its power generation output according to the master station's requirements under varying grid conditions, maintaining supply and demand balance and stable grid operation.

[0129] ③ Distributed new energy stations that do not currently have edge gateways: Station automation terminals can be used to achieve information exchange between the master station and the substation. The station automation terminal has the ability to exchange data with the local monitoring system, measurement and control devices, and photovoltaic data acquisition devices within the distributed new energy station, as well as the function of issuing switch control instructions to the measurement and control devices. During the control execution process, after receiving the instructions from the master station, the station automation terminal uses its own data processing and communication capabilities to accurately transmit the instructions to the measurement and control devices and other related equipment, and based on internal algorithms and preset rules, ensures the effective execution of the control instructions, realizes the reasonable adjustment of the active power of the station, and enables the station to maintain a good coordinated operation state with the power grid in the absence of an edge gateway, meeting the power grid's requirements for active power control of the station.

[0130] Optionally, in some embodiments, step S3 of “triggering a corresponding safety protection strategy after detecting abnormal operation of the power grid, so as to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid” may specifically include:

[0131] S31. When the voltage, frequency, or power at the grid connection point is detected to exceed the safety threshold, the system automatically switches to local safety mode and blocks the master station command.

[0132] Specifically, distributed renewable energy stations monitor key parameters such as voltage, frequency, and power at the grid connection point in real time. When these parameters exceed preset safety thresholds, the system automatically triggers a safety protection mechanism, switching the control mode to local safety mode and blocking commands from the master station to prevent unreasonable external commands from further exacerbating system anomalies. For example, if the grid connection point voltage exceeds ±10% of the rated voltage, the system automatically switches to local safety mode, where the station's internal control system adjusts according to local rules to ensure the safety of equipment and the grid. Intelligent prediction algorithms, such as deep learning-based time series prediction models, are introduced to predict trends in grid connection point voltage, frequency, and power, triggering safety protection mechanisms in advance and enhancing the system's proactive and proactive nature. Furthermore, by combining real-time meteorological data with grid load forecast information, the dynamic adjustment strategy for safety thresholds is optimized, improving the system's adaptability and flexibility.

[0133] S32. When a communication interruption is detected, the last valid instruction is maintained or control is suspended, and after communication is restored, the active control target value is gradually transitioned to by gradient adjustment;

[0134] Specifically, in the event of a communication interruption, the edge gateway or station control system maintains the last valid instruction received, maintains the current active power output status, or suspends control operations to avoid disordered operation due to missing instructions. When communication is restored, the system smoothly adjusts the station's active power to the target value issued by the master station through gradient adjustment (such as gradually increasing or decreasing the active power output), avoiding grid fluctuations caused by sudden changes. For example, if the station's active power output is 80kW when communication is interrupted and the master station's target value is 100kW, after communication is restored, the system increases by 10kW per minute until the target value is reached. Develop more intelligent communication interruption handling strategies, such as autonomous decision-making algorithms based on the station's current operating status and historical data, and perform limited autonomous adjustments based on local information during communication interruptions to improve the system's adaptability. At the same time, optimize the parameter settings of gradient adjustment, dynamically adjust the gradient step size according to the real-time load conditions of the power grid and the equipment status of the station, and improve the smoothness and efficiency of the adjustment.

[0135] S33. Perform interval limits, adjustment steps, and gradient checks on the instructions issued by the master station, and refuse to execute instructions that exceed the preset safety range;

[0136] Specifically, after receiving an active power regulation command from the master station, the system first performs a range limit check to verify that the command is within the equipment's safe operating range. It then performs a step size check to ensure that the command's adjustment amplitude meets the equipment's regulation capabilities. Finally, it performs a gradient check to verify that the command's adjustment speed is within a reasonable range. If the command exceeds any of these check ranges, the system rejects the command and reports an exception to the master station. For example, if the master station issues a command requiring a station to instantly increase its active power output by 50 kW, but the equipment's maximum adjustment step size is 30 kW / minute, the system rejects the command to prevent equipment overload. A dynamic command verification model is developed by combining real-time and historical operating data. This model dynamically adjusts the verification range and parameter settings based on the station's real-time operating status and equipment health, improving verification accuracy and adaptability. Furthermore, a command optimization algorithm is introduced to automatically adjust and optimize commands that exceed the verification range, generating reasonable control commands and reducing reliance on and interaction with the master station.

[0137] This embodiment effectively avoids equipment overload, misoperation or power grid fluctuations caused by unreasonable instructions through multi-dimensional instruction verification, ensures the safe and stable operation of the station and the power grid, and improves the reliability and anti-interference capability of the system.

[0138] Optionally, in some embodiments, step S33 of "checking the interval limit, adjustment step size, and gradient of the active power adjustment instruction issued by the master station, and refusing to execute instructions that exceed a preset safety range" may specifically include:

[0139] The active power regulation instruction is checked for the set value interval. If the active power set value issued by the dispatcher exceeds the pre-set reasonable interval limit, the active power regulation instruction is rejected.

[0140] Specifically, after receiving an active power regulation command from the master station, the system first performs a set value interval check on the active power setpoint in the command. The system presets reasonable interval limits, for example, based on the maximum capacity and minimum stable operating point of the station equipment. If the active power setpoint issued by the dispatcher falls outside this range, the system deems the command unreasonable, refuses to execute it, and reports the abnormality to the master station. For example, if the maximum active power output capacity of the station equipment is 100kW, and the master station issues a command requesting an output of 120kW, the system will refuse to execute the command.

[0141] The active power regulation instruction is calibrated for the adjustment step. If the set value issued by the dispatching master station and the actual measured value of the control target exceed the maximum adjustment step, the active power regulation instruction is rejected.

[0142] Specifically, before the instruction is executed, the adjustment step length is checked for the difference between the set value issued by the dispatching master station and the actual measured value of the current control target at the station. The system presets a maximum adjustment step length. For example, the maximum adjustment amount per minute is set to 10kW based on the adjustment capability of the equipment and the stability requirements of the power grid. If the difference between the set value and the measured value exceeds this maximum adjustment step length, the system refuses to execute the instruction and feedbacks the abnormal information to the master station. For example, if the current control target value is 80kW, the set value issued by the master station is 105kW, and the maximum adjustment step length is 10kW / minute, the system refuses to execute the instruction.

[0143] Perform set value gradient check on the active power regulation instruction. If the current set value issued by the dispatching master station exceeds the maximum regulation gradient with the last reasonable set value, the active power regulation instruction will be rejected.

[0144] Specifically, before the instruction is executed, the change gradient between the current set value issued by the dispatching master station and the last reasonable set value is checked. The system presets a maximum adjustment gradient. For example, the maximum change rate per minute is set to 5kW / min based on the adjustment characteristics of the equipment and the stability requirements of the power grid. If the change gradient between the current set value and the last reasonable set value exceeds this maximum adjustment gradient, the system refuses to execute the instruction and feedbacks abnormal information to the master station. For example, if the last reasonable set value is 80kW, the current set value is 100kW, and the maximum adjustment gradient is 5kW / min, the system refuses to execute the instruction.

[0145] This embodiment comprehensively ensures the rationality and safety of active power regulation instructions through an instruction verification mechanism with three dimensions: set value interval verification, adjustment step verification, and set value gradient verification. The set value interval verification prevents the execution of instructions that exceed the equipment capability range, the adjustment step verification avoids equipment shock and grid fluctuations caused by excessive adjustment amplitude, and the set value gradient verification ensures the smoothness and continuity of the regulation process.

[0146] In a specific embodiment, Figure 6 As shown, Figure 6 Schematic diagram of the safety protection strategy designed for new energy stations.

[0147] New energy station security plays a key role in ensuring stable station operation and grid security. When a distributed new energy station operates abnormally, the substation should trigger the corresponding security strategy and automatically exit or lock control. When the operating conditions return to normal operating conditions, the substation will automatically or manually unlock and resume normal control. The designed security protection strategy is as follows:

[0148] 1) Automatic Exit Strategy: When a situation threatens station operation safety, the substation can respond quickly. If the active power, voltage, or frequency at the grid connection point exceeds fault limits, potentially damaging station equipment or affecting grid power quality, the substation will automatically switch to exit mode, switching the control mode to power plant control mode, and providing a timely alarm. Once normal operating conditions return to normal, manual recovery control is required to ensure an orderly system restart after the abnormal condition is resolved, preventing further problems from persisting.

[0149] 2) Locking control strategy: Under various abnormal conditions, the substation will enter a suspended control state to ensure safety. When communication with the master station is interrupted, in the dispatching remote control mode, if no instruction is received from the dispatching master station, the substation will maintain the last instruction or automatically suspend control to prevent erroneous operation due to missing instructions; when communication with the booster station monitoring system or the new energy monitoring system is interrupted, the monitoring system sends an abnormal locking signal, and when data collection is abnormal (such as the key measurement data of the substation is not updated or an error occurs), control abnormality (such as the power increase or decrease direction is reversed when the substation responds to the master station instruction), etc., the substation will also automatically suspend control and issue an alarm. After the abnormal situation is resolved, the substation will automatically resume regulation, and the default instruction after restoration is the actual measured value of the total active power of the station, ensuring that the system can smoothly transition back to normal operation and minimize the impact on the power grid and station equipment.

[0150] 3) Dispatch instruction safety verification: After receiving the station control mode information and active remote adjustment instructions from the master station, the substation will strictly conduct rationality verification. In terms of dispatch set value interval verification, if the active set value issued by the dispatch exceeds the pre-set reasonable interval limit, the substation will refuse to execute this instruction to prevent the station equipment from overloading or the grid operation from being unbalanced due to unreasonable instructions; in the adjustment step verification link, when the set value issued by the dispatch master station and the actual value of the control target exceed the maximum adjustment step, the execution will also be refused to ensure that the adjustment process is smooth and gradual, and avoid the impact of excessive adjustment amplitude on the equipment; in the set value gradient verification, if the current set value issued by the dispatch master station and the last reasonable set value exceed the maximum adjustment gradient, the instruction will also be refused to execute, ensuring the continuity and rationality of the control instruction, effectively improving the accuracy and reliability of the control, and maintaining the safe and stable operation of the station and the power grid.

[0151] In order to facilitate understanding of the active power control method of the distributed new energy station provided by this application, Figure 7 As shown, this embodiment also provides a specific implementation of a method for controlling active power of a distributed new energy station, including the following steps:

[0152] 1. Active power regulation command reception

[0153] Communication network optimization: By establishing redundant communication links (such as 5G and power distribution data networks) and deploying network traffic monitoring and control systems, the stability and efficiency of command transmission can be ensured.

[0154] Instruction verification and error correction mechanism: Use parity check and Hamming code check algorithms to verify and correct instructions to ensure the accuracy of instructions.

[0155] Enhanced edge gateway functions: The edge gateway temporarily stores instructions, parses key information, evaluates the rationality of instructions, and adapts communication protocols to ensure the correct transmission and parsing of instructions.

[0156] Ensure that active power regulation instructions are transmitted stably and accurately from the master station to distributed new energy stations, and provide reliable and high-quality instruction information for subsequent control operations to ensure smooth information transmission.

[0157] 2. Analysis of data misoperation types

[0158] Instruction source verification: Verify the legitimacy of the instruction source and ensure that the instruction comes from the authorized master station.

[0159] Reasonableness check: Check whether the instructions are consistent with the current operating status of the station and equipment capabilities.

[0160] Communication content verification: Ensure that the command content has not been tampered with or lost during the communication process.

[0161] Fine-tune and optimize the operating parameters of power generation equipment to achieve precise control of active power, ensuring that the station's power output meets grid demand and equipment operates stably

[0162] 3. Design of safety protection strategies for new energy stations

[0163] Dispatch instruction safety check: Comprehensively check the instructions issued by the master station to ensure that the instructions are within a reasonable range.

[0164] Locking control strategy: In the event of communication interruption or abnormality, maintain the last valid instruction or suspend control to ensure stable operation of the station.

[0165] Suspend control and resume regulation: Suspend control operations under abnormal circumstances and gradually resume regulation after returning to normal.

[0166] Automatic exit strategy: In the event of serious abnormalities, it will automatically switch to local safety mode and block the main station instructions.

[0167] Abnormal monitoring and alarm: Real-time monitoring of abnormal situations and issuing alarms so that timely measures can be taken.

[0168] State transition and recovery operation: After the abnormal situation is resolved, the normal operation state of the station is automatically or manually restored.

[0169] Ensure the safe and stable operation of the station and power grid under abnormal circumstances, prevent equipment damage and power grid imbalance, and ensure smooth system transition and rationality of control instructions.

[0170] During implementation, communication network optimization and command verification and error correction mechanisms ensure stable and accurate transmission of active power regulation commands from the master station to distributed renewable energy stations. MPC and ANFIS algorithms are employed to fine-tune and optimize the operating parameters of power generation equipment, achieving precise control. Multiple safety protection strategies ensure safe and stable operation of stations and the power grid in abnormal situations, preventing equipment damage and grid imbalance.

[0171] It can be seen that this embodiment has constructed a complete and efficient distributed new energy station active power remote control system. In terms of command reception, the redundant communication links and flow control mechanism greatly reduce the interruption rate of command transmission, and the check and error correction and retransmission mechanism ensures that the command error rate is almost zero, which effectively guarantees the efficiency and reliability of command reception. In the control execution link, advanced algorithms and fine adjustment strategies have significantly improved the active power regulation accuracy of new energy stations, enhanced the stability of equipment operation, effectively met the scheduling needs under complex working conditions of the power grid, and made the power distribution more reasonable. At the security protection level, the perfect strategy can quickly respond to various anomalies, successfully avoid power grid fluctuations and power outages caused by station failures, build a solid line of defense for the safe and stable operation of the power grid, and give full play to the positive role of distributed new energy in power supply.

[0172] In summary, the active power control solution for distributed new energy stations provided by this embodiment is that the edge gateway is close to the new energy station end and can quickly receive and decode active power control instructions from the dispatch center. Compared with the centralized control mode, the instructions need to be transmitted over long distances and processed multiple times before reaching the station, which greatly shortens the time delay of instruction transmission and ensures that the station can respond to the active power regulation needs of the power grid more promptly. Unlike the local feedback autonomous control solution, the edge gateway of this embodiment can quickly upload the station operation status information to the dispatch center in real time. The dispatch center can adjust and issue more accurate active power control instructions based on this information, realizing the timeliness of information exchange between the station and the power grid, making the active power control more consistent with the real-time operation status of the power grid; in this embodiment, the new energy station can flexibly select multiple control modes and strategies based on the different instructions and real-time operation status received by the edge gateway, which is more flexible than the single reliance on the dispatch center instruction execution in the centralized control mode; when a fault occurs in the power grid, such as a short circuit or overvoltage, the edge gateway of this embodiment can quickly detect and isolate the fault area, prevent the fault from spreading within the new energy station, and protect the safety of the station equipment. In the case of a centralized control model, all stations rely on unified dispatching instructions when facing a power grid failure. Once the dispatch center is affected by a failure, the control of the entire distributed new energy system will be thrown into chaos, making fault isolation and recovery difficult. Local autonomous control may also fail due to a lack of global information, resulting in disordered recovery, increasing secondary impacts on the power grid. In short, the method of the present invention can receive instructions in a timely manner and accurately control execution, which can better balance the safety of the station itself and the overall stability of the power grid in emergency situations.

[0173] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0174] To facilitate better implementation of the distributed renewable energy station active power control method of the present application embodiment, the present invention also provides an active power control device for a distributed renewable energy station based on the above-mentioned distributed renewable energy station active power control method. The meanings of the terms herein are the same as those in the above-mentioned distributed renewable energy station active power control method. For specific implementation details, please refer to the description in the method embodiment.

[0175] See also Figure 8 , Figure 8 This is a schematic diagram of the structure of the active power control device of the distributed new energy station provided in an embodiment of the present application. The active power control device of the distributed new energy station may specifically include an adjustment instruction module 201, an adjustment control module 202 and a safety protection module 203, which may be specifically as follows:

[0176] The adjustment instruction module 201 is used to receive the active power adjustment instruction issued by the master station through the edge gateway, verify the active power adjustment, and generate verified instruction data;

[0177] The regulation control module 202 is used to dynamically select a control mode based on the verified command data and the real-time operating status of the new energy station, and adjust the active power output of the power generation equipment according to the control mode;

[0178] The safety protection module 203 is used to trigger a corresponding safety protection strategy after detecting abnormal operation of the power grid, so as to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

[0179] For the specific definition of the active power control device of the distributed new energy station, please refer to the definition of the active power control method of the distributed new energy station above, which will not be repeated here. The various modules in the above-mentioned active power control device of the distributed new energy station can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0180] The active power control device of the distributed new energy station provided in this embodiment receives and verifies the master station instructions through the edge gateway and dynamically selects the control mode to adjust the output of the power generation equipment. At the same time, it triggers the safety protection strategy when the power grid is abnormal, ensuring the efficiency, flexibility, accuracy and safety of the active power control of the distributed new energy station, thereby improving the stability and reliability of the power grid operation.

[0181] In addition, the present invention also provides an electronic device, such as Figure 9 , which shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically:

[0182] The electronic device may include one or more processors 301 of processing cores, one or more computer-readable storage media memories 302, a power supply 303, an input unit 304 and other components. Those skilled in the art will appreciate that Figure 9 The electronic device structure shown in the figure does not constitute a limitation of the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0183] The processor 301 is the control center of the electronic device. It connects all parts of the electronic device using various interfaces and lines. By running or executing software programs and / or modules stored in the memory 302 and accessing data stored in the memory 302, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor primarily processes the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into the processor 301.

[0184] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and the active power control method of the distributed new energy station by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0185] The electronic device also includes a power supply 303 for supplying power to various components. Preferably, the power supply 303 can be logically connected to the processor 301 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The power supply 303 can also include one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0186] The electronic device may further include an input unit 304, which may be configured to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0187] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302 to implement various functions as follows:

[0188] The active power regulation instructions issued by the master station are received through the edge gateway, the active power regulation is verified, and the verified instruction data is generated; based on the verified instruction data and the real-time operating status of the new energy station, the control mode is dynamically selected, and the active power output of the power generation equipment is adjusted according to the control mode; after detecting abnormal operation of the power grid, the corresponding safety protection strategy is triggered to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

[0189] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0190] The embodiment of the present application receives and verifies the master station instructions through the edge gateway and dynamically selects the control mode to adjust the output of the power generation equipment. At the same time, it triggers the safety protection strategy when the power grid is abnormal, ensuring the efficiency, flexibility, accuracy and safety of the active power control of the distributed new energy station, thereby improving the stability and reliability of the power grid operation.

[0191] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0192] To this end, an embodiment of the present application provides a storage medium storing a plurality of instructions that can be loaded by a processor to execute the steps of any of the methods for controlling active power of a distributed renewable energy station provided in the embodiments of the present application. For example, the instructions can execute the following steps:

[0193] The active power regulation instructions issued by the master station are received through the edge gateway, the active power regulation is verified, and the verified instruction data is generated; based on the verified instruction data and the real-time operating status of the new energy station, the control mode is dynamically selected, and the active power output of the power generation equipment is adjusted according to the control mode; after detecting abnormal operation of the power grid, the corresponding safety protection strategy is triggered to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

[0194] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0195] The storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0196] Since the instructions stored in the storage medium can execute the steps in any active power control method of a distributed new energy station provided in the embodiments of the present application, the beneficial effects that can be achieved by any active power control method of a distributed new energy station provided in the embodiments of the present application can be achieved. Please see the previous embodiments for details and will not be repeated here.

[0197] The above is a detailed introduction to the active power control method and related equipment of a distributed new energy station provided in the embodiment of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for controlling active power of a distributed new energy station, characterized in that: The steps include: Receiving active power regulation instructions issued by the master station through the edge gateway, verifying the active power regulation, and generating verified instruction data; Based on the verified command data and the real-time operating status of the new energy station, dynamically select a control mode and adjust the active power output of the power generation equipment according to the control mode; After detecting abnormal operation of the power grid, a corresponding safety protection strategy is triggered to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

2. The active power control method of a distributed new energy station according to claim 1, characterized in that: The receiving, through the edge gateway, the active power adjustment instruction issued by the master station, verifying the active power adjustment, and generating verified instruction data, includes: Build redundant communication links including wireless communication and power distribution data networks, and dynamically switch between primary and backup channels based on network latency or signal quality; The received active power regulation command is subjected to parity check and Hamming code check in sequence. If the check fails, the command retransmission mechanism is triggered until the check passes or an alarm is generated after the preset number of retransmissions is reached. The verified active power regulation instructions are matched and analyzed with the real-time electrical parameters of the station. If the instructions exceed the equipment adjustment range or conflict with the current operating status, the abnormality is fed back to the master station and the instruction correction is requested.

3. The active power control method of a distributed new energy station according to claim 1, characterized in that: The dynamic selection control mode includes: If the control mode is the master station remote adjustment mode, the real-time active power target value issued by the master station is directly executed; If the control mode is the master station planned value mode, the power generation planned value issued by the master station is executed according to the preset time period; If the control mode is the station autonomous mode, the control target value is set autonomously based on the status of local power generation equipment and historical data.

4. The active power control method of a distributed new energy station according to claim 1, characterized in that: The step of adjusting the active power output of the power generation equipment according to the control mode includes: For stations with flexible remote control of active power generation, the edge gateway proportionally allocates the active power control target value of each generating unit based on the active power control target value of the entire station and the real-time output of the generating unit, and sends it to the corresponding control device; For stations with only switch remote control functions, the grid connection point switch or grid connection point branch switch measurement and control device is controlled through the edge gateway, and control of the grid connection point switch is prohibited; The deviation between the actual output and the active power control target value is monitored through a closed-loop feedback mechanism, and the control parameters are dynamically adjusted.

5. The active power control method of a distributed new energy station according to claim 4, characterized in that: The method of monitoring the deviation between the actual output and the active power control target value through a closed-loop feedback mechanism and dynamically adjusting the control parameters includes: Collect the actual active power data of each power generation unit in the station in real time, compare it with the active power control target value, and calculate the corresponding deviation value; Dynamically adjust the control parameters of the inverter or wind turbine controller according to the size and change trend of the deviation value, wherein the control parameters include proportional coefficient, integral time or adjustment step size; The control parameters are continuously optimized through an iterative feedback loop until the actual active power data is within the error range of the active power control target value.

6. The active power control method of a distributed new energy station according to claim 1, characterized in that: The triggering of a corresponding safety protection strategy after detecting abnormal operation of the power grid, so as to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid, includes: When it is detected that the voltage, frequency or power at the grid connection point exceeds the safety threshold, it automatically switches to the local safety mode and blocks the master station command; When communication interruption is detected, the last valid instruction is maintained or control is suspended, and after communication is restored, the active power control target value is gradually transitioned through gradient adjustment; The instructions issued by the master station are checked for interval limits, adjustment steps and gradients, and instructions that exceed the preset safety range are refused to be executed.

7. The active power control method of a distributed new energy station according to claim 1, characterized in that: The active power regulation instructions issued by the master station are subjected to interval limit, regulation step and gradient verification, and instructions that exceed the preset safety range are rejected, including: Performing a set value interval check on the active power regulation instruction; if the active power set value issued by the dispatcher exceeds the pre-set reasonable interval limit, the active power regulation instruction is rejected; The active power regulation instruction is calibrated for the adjustment step. If the set value issued by the dispatching master station and the actual measured value of the control target exceed the maximum adjustment step, the active power regulation instruction is rejected. The active power regulation instruction is subjected to a set value gradient check. If the current set value issued by the dispatching master station and the last reasonable set value exceed the maximum regulation gradient, the active power regulation instruction is rejected.

8. An active power control device for a distributed new energy station, characterized in that: include: An adjustment instruction module is used to receive the active power adjustment instruction issued by the master station through the edge gateway, verify the active power adjustment, and generate verified instruction data; A regulation control module, configured to dynamically select a control mode based on the verified command data and the real-time operating status of the new energy station, and to regulate the active power output of the power generation equipment according to the control mode; The safety protection module is used to trigger the corresponding safety protection strategy after detecting abnormal operation of the power grid, so as to isolate the abnormality according to the safety protection strategy and maintain stable operation of the power grid.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the active power control method for a distributed new energy station as described in any one of claims 1 to 7 are implemented.

10. A storage medium, characterized in that: A computer program is stored which can be loaded by a processor and executes the active power control method of a distributed new energy station as described in any one of claims 1 to 7.

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