Power grid system, power grid power control method and storage medium

Abstract

The invention discloses a power grid system, a power grid power control method and a storage medium, the power grid system comprises a dispatching end master station and a station terminal sub-station, the dispatching end master station comprises a master station control center layer and a master station intermediate layer, and the station terminal sub-station comprises a substation control center layer, a substation intermediate layer and a station layer; the master station control center layer is used for generating a power adjustment strategy; the master station intermediate layer is used for decomposing a power regulation instruction in the power regulation strategy to obtain a station power control instruction; the substation control center layer is used for decomposing the station power regulation instruction to obtain an equipment power control instruction; the field station layer is used for sending the equipment power control instruction to an execution unit of the distributed new energy field station, so that the execution unit executes power adjustment operation corresponding to the equipment power control instruction, a power grid can rapidly and accurately cope with dynamic changes of distributed new energy, and power can be accurately adjusted under complex working conditions.

Description

Technical Field

[0001] The present invention relates to the field of new energy control technology, and in particular to a power grid system, a power grid power control method and a storage medium. Background Art

[0002] Traditional grid dispatching systems, designed primarily for centralized power stations, struggle to adapt to the integration and management needs of large numbers of distributed renewable energy sources. Therefore, effectively controlling and coordinating the active power output of these distributed renewable energy sources has become a key research topic in power systems.

[0003] At present, the active power control of distributed new energy stations usually relies on human judgment and manual operation, which cannot quickly respond to changes in grid load and emergencies. In complex working conditions, the active power regulation is not accurate enough, which may cause grid frequency and voltage fluctuations. Summary of the Invention

[0004] This application proposes a power grid system, a power grid power control method and a storage medium to solve the problem that the active power control of distributed new energy stations usually relies on human judgment and manual operation, cannot quickly respond to changes in grid load and emergencies, and under complex working conditions, the active power regulation is not accurate enough, which may cause grid frequency and voltage fluctuations.

[0005] In a first aspect, a power grid system is provided, comprising a dispatching master station and a field station terminal station, wherein the dispatching master station comprises a master station control center layer and a master station intermediate layer, and the field station terminal station comprises a substation control center layer, a substation intermediate layer, and a field station layer;

[0006] The master station control center layer is used to receive power grid dispatch information, obtain power grid operation data of the area to which the dispatching end master station belongs, and generate a power regulation strategy based on the power grid dispatch information and the power grid operation data;

[0007] The master station intermediate layer is used to decompose the power regulation instructions in the power regulation strategy to obtain the station power control instructions of each distributed new energy station in the area to which the station terminal station belongs;

[0008] The substation control center layer is used to decompose the station power adjustment instruction according to the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain the equipment power control instruction;

[0009] The station layer is used to send the device power control instruction to the execution unit of the distributed new energy station, so that the execution unit executes the power adjustment operation corresponding to the device power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

[0010] In one embodiment, the master station control center layer includes:

[0011] A working condition analysis module, used for analyzing the power grid operating data to obtain the power grid operating condition;

[0012] A strategy generation module, configured to generate a power regulation strategy based on the grid operating conditions and the grid dispatch information;

[0013] The master station middle layer includes:

[0014] The instruction decomposition module is used to decompose the power regulation instructions in the power regulation strategy based on the grid operation constraints to obtain the station power control instructions of each distributed new energy station in the area where the station terminal station belongs.

[0015] In one embodiment, the dispatching end master station and the yard terminal substation include a main communication link and at least one backup communication link, so that when the main communication link fails, data exchange can be performed through the at least one backup communication link.

[0016] In one embodiment, the master station control center layer and the master station intermediate layer perform data exchange via a fixed protocol; and

[0017] The master station middle layer and the field station terminal station exchange data via a non-fixed protocol / fixed protocol.

[0018] In one embodiment, the substation control center layer includes a main control unit and a backup control unit, so that when the main control unit fails, the backup control unit is started.

[0019] In one embodiment, the substation control center layer also includes a fault repair module, which is used to locate target data associated with the fault situation in the pre-stored backup data based on a data index mechanism when a fault occurs in the main control unit; and repair the fault situation based on the target data.

[0020] In one embodiment, the substation control center layer also includes a data backup module, which is used to fully back up the operating data of the substation according to a preset time period and store it in a backup storage space to obtain the backup data; and / or, the data backup module is used to detect changes in the operating data of the substation in real time; when the operating data changes, the changed operating data is recorded; and the changed operating data is backed up to a target incremental backup file to obtain the backup data.

[0021] In one embodiment, the grid dispatching information indicates batch control of multiple distributed new energy stations, and the master station control center layer also includes a batch control module, which is used to extract the power adjustment target value from the grid operation demand; and batch control the multiple distributed new energy stations according to the power adjustment target value.

[0022] In a second aspect, a power grid power control method is provided, which is applied to the power grid system described in any one of the first aspects above, the method comprising:

[0023] Receive grid dispatch information and obtain grid operation data of the area to which the dispatching master station belongs;

[0024] generating a power regulation strategy based on the grid dispatch information and the grid operation data, and decomposing the power regulation instructions in the power regulation strategy to obtain a station power control instruction for each distributed new energy station in the area to which the station terminal station belongs;

[0025] Decomposing the station power adjustment instruction according to the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain the equipment power control instruction;

[0026] The device power control instruction is sent to the execution unit of the distributed new energy site, so that the execution unit executes the power adjustment operation corresponding to the device power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

[0027] In a third aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned grid power control method are implemented.

[0028] The present application provides a power grid system, a power grid power control method, and a storage medium. The power grid system includes a dispatching-end master station and a station terminal station. The dispatching-end master station includes a master station control center layer and a master station intermediate layer, and the station terminal station includes a substation control center layer, a substation intermediate layer, and a station layer. The master station control center layer is used to receive power grid dispatch information, obtain power grid operation data of the area to which the dispatching-end master station belongs, and generate a power regulation strategy based on the power grid dispatch information and the power grid operation data. The master station intermediate layer is used to decompose power regulation instructions in the power regulation strategy to obtain station power control instructions for each distributed new energy station in the area to which the station terminal station belongs. The substation control center layer is used to decompose the station power regulation instructions based on the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain device power control instructions. The station layer is used to send the device power control instructions to the execution unit of the distributed new energy station, so that the execution unit executes the power regulation operation corresponding to the device power control instruction and feeds back the execution data to the master station control center layer and the master station intermediate layer. In this application, by clearly dividing the functional levels of the dispatching end master station and the substation terminal in the power grid system and ensuring close collaboration between the various levels, the efficiency of command transmission and data interaction is greatly improved. By receiving power grid dispatch information and obtaining power grid operation data of the area to which the dispatching end master station belongs, a power regulation strategy can be generated based on this information, and the power regulation instructions can be further decomposed into specific station power control instructions. Combined with the operating data of the distributed new energy station collected by the substation intermediate layer and the station layer, the station power regulation instructions are further decomposed into equipment power control instructions and sent to the execution unit of the distributed new energy station. After the execution unit performs the power adjustment operation, it feeds back the execution data to the master station control center layer and the master station middle layer, so that the power grid can quickly and accurately respond to the dynamic changes of distributed renewable energy, so as to quickly respond to changes in grid load and emergencies. In complex working conditions, it can accurately adjust the power to avoid causing grid frequency and voltage fluctuations, ensuring that the grid can still maintain stable operation under complex working conditions, enhancing the grid's regulation and adaptability to renewable energy, and realizing refined management from grid dispatching instructions to equipment execution, ensuring the stability and flexibility of grid operation, improving the utilization efficiency of renewable energy, and at the same time enhancing the grid's ability to respond to equipment failures, optimizing the overall dispatching efficiency and reliability of grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 A schematic diagram of the architecture of the power grid system provided in an embodiment of the present application;

[0031] Figure 2 A schematic diagram of the architecture of the dispatching terminal master station provided in an embodiment of the present application;

[0032] Figure 3 A schematic diagram of the architecture of a terminal station provided in an embodiment of the present application;

[0033] Figure 4 A schematic diagram of the site configuration of a terminal station provided in an embodiment of the present application;

[0034] Figure 5 A flowchart of equipment failure processing in a power grid system according to an embodiment of the present application;

[0035] Figure 6 A schematic diagram of the technical architecture of a power grid power control method provided in another embodiment of the present application;

[0036] Figure 7 A flowchart of a power grid power control method provided in an embodiment of the present application;

[0037] Figure 8 A flowchart of a grid power control method provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0038] The following exemplary embodiments are described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different figures represent the same or similar elements. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Instead, they are merely examples of systems and methods consistent with the following claims or aspects of the present application.

[0039] 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.

[0040] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0041] 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.

[0042] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0043] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0044] Embodiments of the present application provide a power grid system, a power grid power control method, and a storage medium.

[0045] Among them, the power grid system can be deployed in electronic devices, which may include computer devices and mobile communication devices. Computer devices may include personal computers, laptops, tablets, etc. Mobile communication devices may include smart phones, etc. In addition, electronic devices can communicate with servers via wired or wireless means. The server may include an independently operated server or a distributed server, or a server cluster composed of multiple servers. The terminal may include a mobile phone, a tablet computer or a personal computer (PC).

[0046] It should be noted that the order of description of the following embodiments does not limit the priority order of the embodiments.

[0047] See also Figure 1 , Figure 1 This is a schematic diagram of the architecture of the power grid system provided in this application. The power grid system may specifically include a dispatching end master station 101 and a station terminal station 102. The dispatching end master station 101 includes a master station control center layer 1011 and a master station intermediate layer 1012. The station terminal station 102 includes a substation control center layer 1021, a substation intermediate layer 1022, and a station layer 1023. Specifically, it may be as follows:

[0048] The master station control center layer 101 is used to receive power grid dispatching information, obtain power grid operation data of the area to which the dispatching end master station 101 belongs, and generate a power regulation strategy based on the power grid dispatching information and the power grid operation data.

[0049] The master station intermediate layer is used to decompose the power regulation instructions in the power regulation strategy to obtain the station power control instructions of each distributed new energy station in the area to which the station terminal station belongs.

[0050] The substation control center layer is used to decompose the station power adjustment instruction according to the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain the equipment power control instruction.

[0051] The station layer is used to send the device power control instruction to the execution unit of the distributed new energy station, so that the execution unit executes the power adjustment operation corresponding to the device power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

[0052] Grid dispatch information can be instructions for regulating power within the region of the grid system, such as province-wide grid load demand and frequency stability requirements. Power regulation strategies refer to the strategies used to regulate the active power of the grid system. Station operation data includes public network data and real-time station operation data.

[0053] At the dispatching master station, the power regulation instructions within the power regulation strategy refer to the regulation strategies and instructions from the global perspective of the dispatching master station's region. For example, a large-scale active power regulation strategy developed from the global perspective of the province's power grid covers the overall operation of all prefecture-level regions and renewable energy stations. This power regulation strategy sets a total output target at the instruction level (e.g., "the province needs to increase output by 200MW"). Decisions are based on macro-grid operational data such as load demand and frequency deviation across the entire grid. Adjustment cycles range from minutes to hours. It should be noted that the substation terminal performs fine-grained power regulation on a second-to-minute basis for specific equipment (such as inverter groups) at individual stations. This "macro-micro" hierarchical control ensures both global grid stability and precise regulation of distributed renewable energy.

[0054] At a station terminal, equipment power commands refer to the collective control of all power generation equipment (such as photovoltaic inverters, wind turbine converters, etc.) and their auxiliary systems within a single distributed renewable energy station. For example, the station terminal needs to coordinate the real-time operating status, regulation capabilities, and safety constraints of all power generation units within the distributed renewable energy station. It intelligently decomposes station power control commands issued by the master station's intermediate layer (such as "increase output by 10MW") into specific execution commands for each execution unit (such as "inverter A increases by 3MW, wind turbine B increases by 7MW"). It also monitors the dynamic response of the equipment during the coordinated execution process, ensuring that the entire distributed renewable energy station, as a unified entity, accurately responds to grid dispatch information. This "holistic" approach is reflected not only in the unified control of all equipment within the station, but also in the efficient coordination between the distributed renewable energy station as the smallest controllable unit and the grid's dispatching master station.

[0055] For example, specifically, Figure 2As shown in the figure, the provincial power grid system is divided into the provincial edge cluster / OCS Zone I (i.e., the master station control center layer), the prefectural edge cluster / OCS Zone I (i.e., the master station middle layer), and the edge gateway / station automation terminal (i.e., the station terminal station). The distributed new energy AGC in the provincial edge cluster / OCS Zone I serves as the top-level control center, receiving grid dispatch information from higher-level grid systems and formulating macro-power regulation strategies based on grid operation data from distributed new energy sources across the province. The distributed new energy AGC in the prefectural edge cluster / OCS Zone I is located in the middle layer, serving as a link between the upper and lower layers. The distributed new energy AGC in the prefectural edge cluster / OCS Zone I receives the power regulation strategy issued by the provincial edge cluster and, based on factors such as the local grid structure, the distribution of distributed new energy sites, and local load characteristics, refines and decomposes the instructions to generate specific control instructions suitable for the distributed new energy sites in the region. The station terminal station (edge gateway / station automation terminal) serves as the underlying execution unit and is directly connected to the execution unit (such as the inverter) of the distributed new energy station. When the station terminal station receives the station power control instructions of each distributed new energy station in the area to which the station terminal station belongs, which is decomposed by the prefectural edge cluster, the station terminal station controls the active power output of the distributed new energy station in real time, and uploads the real-time operating data of the distributed new energy station, such as power generation power, voltage, current, equipment status, etc., to the prefectural edge cluster through the edge gateway or station automation terminal, and then feeds back to the provincial edge cluster, forming a complete information closed loop, thereby realizing efficient management and precise regulation of distributed new energy active power control. In this way, the architectural division of the power grid system is conducive to the efficient management and precise regulation of distributed new energy active power control.

[0056] For example, specifically, Figure 3As shown in the figure, the station terminal station is also divided into three layers, including the top layer, which is the edge cluster / distribution network OCS I area (i.e., the substation control center layer), which includes the distributed new energy automatic generation control system (Distributed New Energy Automatic Generation Control, AGC), which is responsible for the formulation and coordination of active power control strategies for all distributed new energy stations in the area, and obtains the device power control instructions of the execution units connected to the distributed new energy stations; the substation middle layer is the security access area, which includes the public network data acquisition server and the distribution safety protection device, which can be used to collect data from various devices or systems connected to the distributed new energy stations from the public network (for example, it can collect the generated power of distributed photovoltaic power generation equipment, the electricity consumption data of user smart meters, the charging status of electric vehicle charging piles, etc.) and security protection functions; the bottom layer is the station layer, including the local monitoring system, edge gateway / station automation terminal, and various detection devices and inverters, etc., which are responsible for the real-time operation data collection and execution unit control of the distributed new energy stations. In this way, the station terminal stations of the power grid system are divided, and the equipment connection and data acquisition and transmission paths of the distributed new energy stations ensure that the real-time operation data of the distributed new energy stations are collected and uploaded in a timely manner. The efficient communication method with the dispatching end master station ensures that the station power control instructions are quickly issued and the execution data is fed back in time, providing physical support for the implementation of data interaction protocols at the station terminal stations, which is conducive to realizing the precise regulation of the active power of the distributed new energy stations and integrating them into the overall control of the power grid.

[0057] In one embodiment, the master station control center layer includes:

[0058] A working condition analysis module, used for analyzing the power grid operating data to obtain the power grid operating condition;

[0059] A strategy generation module, configured to generate a power regulation strategy based on the grid operating conditions and the grid dispatch information;

[0060] The master station middle layer includes:

[0061] The instruction decomposition module is used to decompose the power regulation instructions in the power regulation strategy based on the grid operation constraints to obtain the station power control instructions of each distributed new energy station in the area where the station terminal station belongs.

[0062] The grid operation constraints may include voltage range, frequency threshold and other conditions, for example, the voltage stability range is ±5% of the rated value, and the frequency fluctuation is allowed to be 50 Hz ± 0.2 Hz.

[0063] After the power grid system is divided into different structures, the following describes the site configuration of the dispatching master station and the field terminal station:

[0064] like Figure 4 As shown in the figure, the dispatching master station utilizes high-performance server processors in hardware, combined with large-capacity, high-speed memory and storage devices, to build a robust data processing system to handle the massive amounts of operational data generated by distributed renewable energy. On the software side, advanced and stable control algorithms and intelligent decision-making systems are embedded, enabling accurate calculation of power control commands for each distributed renewable energy station based on complex operating conditions such as real-time load fluctuations and voltage changes in the power grid system, thereby effectively promoting the absorption of renewable energy and ensuring the safety and stability of the power grid.

[0065] On the equipment, the communication module of the station terminal station is equipped with multiple communication links. When the main communication link fails, it can automatically switch to the backup communication link to ensure smooth communication with the dispatching master station. The control unit of the station terminal station adopts a redundant structure. When the main control unit fails, the backup control unit can be seamlessly enabled to maintain the execution of equipment power control instructions. At the software level, the station terminal station establishes a data backup and recovery mechanism, regularly backs up operating data and programs, and ensures that the working state can be quickly restored in the event of equipment failure, and control instructions and feedback information can be stably executed. The redundant configuration of the station terminal station can ensure that the station can still execute instructions and feedback information normally in emergencies such as equipment failure, greatly improving the overall stability of the system and reducing the risk of power grid fluctuations caused by local failures.

[0066] Regularly backed up operational data can include real-time operational data, operating status, equipment performance, and key data related to the control process of distributed renewable energy stations. This includes actual power generation data, including distributed photovoltaic and wind power. For photovoltaic plants, this includes the active power output of the inverter, DC side current and voltage, etc.; for wind farms, this includes the real-time power and speed of the wind turbines; equipment status data, such as whether the photovoltaic inverter is faulty, overheated, or experiencing insulation failures; environmental monitoring data, such as irradiance, component temperature, and solar intensity at the photovoltaic station; control command data and grid interaction data, such as "received command from the master station" and "command execution results." Emergency situations refer to unpredictable failures or abnormal events, such as direct damage to equipment hardware, explosions, natural disasters such as hailstorms, malicious cyberattacks, and operational errors caused by inexperienced personnel.

[0067] Predicting future grid operation trends based on the grid's real-time status and historical data allows for the calculation of precise active power regulation instructions in advance, including:

[0068] Data Collection and Integration: Leveraging the powerful data collection capabilities of the dispatching master station, we continuously collect real-time grid status data, covering various electrical quantities such as voltage, current, power, and frequency, as well as information such as the power generation and equipment status of distributed renewable energy stations. Simultaneously, we retrieve historical data from the database, which contains records of changes in various grid operating parameters over different timescales. By integrating real-time and historical data, we form a comprehensive, dynamic dataset, providing a foundation for subsequent analysis.

[0069] Data Analysis and Model Building: Utilize big data analysis techniques and intelligent algorithms to conduct in-depth mining of the integrated data. Time series analysis algorithms are used to capture patterns in grid operating parameters over time. For example, load trends across seasons and time periods are analyzed, and load changes within specific future time periods are predicted. Regression algorithms within machine learning are used to establish relationship models between grid operating parameters, such as those between load and voltage and frequency, to predict voltage and frequency changes under varying load conditions.

[0070] Forecasting and Command Calculation: Based on the above analysis and models, combined with the real-time state of the power grid, future grid operating trends are predicted. If a future load increase is predicted and there is margin for renewable energy generation, the master station will calculate the required active power increase for each distributed renewable energy station based on factors such as the predicted load increase, the generating capacity of the renewable energy station, and grid transmission limitations, and generate corresponding active power regulation commands. The calculation process also considers grid safety constraints, such as voltage stability range and power balance requirements, to ensure that the commands meet the grid's power needs while ensuring safe and stable operation.

[0071] The master station configuration function module analyzes and processes the collected data to classify and identify different power grid conditions and make optimal decisions based on predefined strategies. The process is as follows:

[0072] Working condition classification and identification: Set multiple key indicator thresholds to distinguish different grid working conditions. Taking load as an example, when the grid load exceeds a preset high load threshold and lasts for a certain period of time, it can be determined as a high load working condition; when the load is lower than a low load threshold, it is determined to be a low load working condition. For voltage and frequency, upper and lower thresholds are also set. If the voltage exceeds the upper or lower limit of the normal range, or the frequency deviates from the rated value to a certain extent, it is identified as an abnormal voltage working condition and an abnormal frequency working condition respectively. Use pattern recognition algorithms to analyze the change pattern of grid operation data. For example, when it is found that the power fluctuation shows a specific periodic or sudden change pattern, it is combined with other parameters to determine whether it belongs to a grid fault working condition.

[0073] Decision-making: The dispatching master station predefines corresponding strategies for different grid operating conditions. Under high-load conditions, the predefined strategy prioritizes increasing active power output by distributed renewable energy stations with large generation margins and fast response times. For example, when the master station identifies a high-load condition, it analyzes each station's real-time power generation data and equipment performance parameters to select eligible stations A, B, and C. Based on each station's generation capacity and the grid's transmission capacity, it calculates that station A needs to increase its active power by X megawatts, station B by Y megawatts, and station C by Z megawatts. Appropriate regulation instructions are then issued to meet the grid's power requirements. In the event of a grid failure, such as a transmission line tripping and causing a localized power imbalance, a predefined emergency control strategy rapidly disconnects non-critical distributed renewable energy stations, prioritizing power supply to key grid nodes and critical loads. Assuming a fault occurs in a certain area of the power grid, the master station determines, based on the fault type and grid topology, that stations D and E are in areas severely affected by the fault and have a relatively small impact on the overall grid stability. Therefore, it issues a disconnection command to disconnect these two stations from the grid, preventing the fault from further expanding and ensuring the safe and stable operation of the grid.

[0074] To effectively generate dispatch instructions, this application utilizes hardware sensor terminals and software integration to implement real-time data monitoring and collection. This data includes network-wide load and frequency data acquired by the dispatching master station, as well as grid operation data such as power generation power and equipment status uploaded by the stations. Based on this collected information, deep data mining and risk identification are achieved through big data analysis and algorithmic control. Big data analysis techniques are employed to deeply mine and process the massive amounts of collected data. For example, time series analysis is used to predict grid load trends and generate power regulation strategies based on grid dispatch information. If analysis indicates that grid load will increase over the next period of time and that there is sufficient generation capacity at the renewable energy station, this provides a basis for increasing the station's active power output. Conversely, if the load is predicted to decrease, adjustments to the station's power output are considered to maintain grid supply and demand balance. The dispatching master station has a series of preset control strategies that calculate station power control instructions based on grid operation constraints. These constraints include, but are not limited to, grid power balance, voltage stability range, and frequency fluctuation range. When generating power regulation strategies, the system combines grid operating conditions and dispatch information to ensure that the calculated power regulation strategies meet both real-time grid needs and the requirements for safe and stable grid operation. For example, while maintaining power balance, it prioritizes power adjustments to stations with high generating efficiency and good stability, while also ensuring that grid voltage and frequency remain within normal ranges. Based on the grid operating conditions, power regulation strategies, and grid operating constraints derived from data analysis, the dispatching master station generates precise station power control instructions. The instruction calculation method varies depending on grid operating conditions and station status. For example, during peak load periods, when the active power output of renewable energy stations needs to be rapidly increased, the dispatching master station prioritizes stations with large generating margins and fast response times, and accurately calculates the power increase for each station based on their equipment performance and grid transmission capacity. When a grid fault occurs, requiring emergency power adjustments, the dispatching master station rapidly calculates station power control instructions for each station according to the pre-set emergency control strategy (i.e., power regulation strategy) to ensure grid safety.

[0075] For example, suppose there is a regional power grid that includes multiple distributed renewable energy sites (such as photovoltaic power stations and wind farms), as well as some traditional power stations and substations. The grid operation data includes the real-time power generation power of each distributed renewable energy site, equipment status (such as photovoltaic panel temperature, wind turbine speed), substation voltage and current data, load-side power demand, etc. The grid dispatch information may include dispatch instructions (such as giving priority to renewable energy power generation), equipment operation constraints (such as maximum output power of the equipment, minimum stable operating power), etc. The grid operation constraints include the equipment operation constraints of each distributed renewable energy site (such as maximum output power, minimum stable operating power), grid topology, line transmission capacity, etc.

[0076] The operating condition analysis module uses grid operating data to calculate the grid's power balance, the equipment status of each distributed renewable energy station, and a 20% drop in photovoltaic power generation over the next two hours. This determines the grid's operating condition. For example, if the current total power generation is 1000MW and the total load demand is 950MW, the grid is under light load, and a 20% drop in photovoltaic power generation is predicted. A photovoltaic power station's panels are overheating, reducing power generation efficiency; or a wind farm's wind speed is low, resulting in insufficient power generation. Therefore, the grid's operating condition indicates that the grid is currently underloaded, but a power shortage is possible in the future, necessitating proactive adjustments to the power generation strategy.

[0077] The strategy generation module formulates a power regulation strategy based on grid dispatch information and grid operating conditions. For example, if the grid operating conditions indicate a light load, the PV power plant's power generation will decrease by 20%. This requires preemptive adjustments to the wind farm's power generation and the activation of backup conventional generators. In this way, within the next two hours, the wind farm's power generation can be increased from 300MW to 350MW; the PV power plant's power generation is expected to decrease by 20%, from 200MW to 160MW; and the backup conventional generators can be activated to increase power generation by 100MW. This results in a power regulation strategy containing specific power regulation instructions, such as increasing wind farm power by 50MW and conventional generator power by 100MW.

[0078] The command decomposition module decomposes power regulation commands to each distributed renewable energy site based on the power regulation strategy and operational constraints. For example, a wind farm's current total power regulation command is to increase by 50 MW. There are three wind farms in the area: Wind Farm A, Wind Farm B, and Wind Farm C. A photovoltaic power plant's current total power regulation command is to maintain the current status (a 20% decrease in power generation is expected, but this cannot be adjusted). A conventional generator set: Activate the standby conventional generator set to increase power generation by 100 MW. Specifically, Wind Farm A's current power generation is 100 MW, its maximum output is 120 MW, and it can increase by 20 MW. Wind Farm B's current power generation is 120 MW, its maximum output is 150 MW, and it can increase by 30 MW. Wind Farm C's current power generation is 80 MW, its maximum output is 100 MW, and it can increase by 20 MW. The total power regulation instruction is to increase by 50MW. According to the remaining regulation capacity of each wind farm, it is distributed as follows: Wind farm A: Increase power by 20MW (reaching the maximum output power). Wind farm B: Increase power by 20MW (reaching the maximum output power). Wind farm C: Increase power by 10MW (remaining regulation capacity). Traditional generator sets: Start the standby traditional generator sets and increase the power generation capacity by 100MW. Finally, the site power control instructions obtained include Wind farm A: Increase power by 20MW. Wind farm B: Increase power by 20MW. Wind farm C: Increase power by 10MW. Traditional generator sets: Increase power by 100MW.

[0079] In this embodiment, the dispatching master station can generate and decompose power regulation strategies based on grid operation data and power dispatching information, and ultimately send specific power control instructions to each distributed new energy station to achieve optimized dispatching and stable operation of the grid.

[0080] In one embodiment, the dispatching end master station and the yard terminal substation include a main communication link and at least one backup communication link, so that when the main communication link fails, data exchange can be performed through the at least one backup communication link.

[0081] Because the communication module in the terminal station is configured with multiple communication links, including a primary communication link and at least one backup communication link, the terminal station automatically switches to the backup communication link if the primary communication link fails, ensuring smooth communication between the terminal station and the dispatching master station. For example, if the primary communication link fails three times in a row, the terminal station automatically switches to the backup communication link.

[0082] In one embodiment, the master station control center layer and the master station intermediate layer perform data exchange via a fixed protocol; and

[0083] The master station middle layer and the field station terminal station exchange data via a non-fixed protocol / fixed protocol.

[0084] The architectural division of the power grid system establishes the physical framework for data transmission. The configuration of dispatching master stations and substations provides basic node support for these stations and data exchange within the power grid system. Efficient data exchange can fully leverage the functional advantages of the station configuration, jointly ensuring the effective control and efficient utilization of distributed renewable energy by the power grid. Data exchange between provincial and prefectural master stations, and between prefectural master stations and distributed renewable energy stations, each requires different data protocols and measurement data exchange specifications.

[0085] For example, the data interaction between the master station control center layer and the master station middle layer of the dispatching end master station is as follows:

[0086] Real-time data exchange between the master control center layer and the master intermediate layer relies on fixed protocols, such as 101 or 104. These protocols have mature frame formats and transmission mechanisms for power system communications, ensuring stable and efficient data transmission between master stations at different levels, effectively preventing packet loss and data reordering, and providing a reliable data link foundation for subsequent coordinated control. The real-time data exchanged includes monitored grid operation data, including interactive data related to power regulation, including power regulation strategies, feedback station operation data, grid operation status data such as voltage, real-time frequency of the regional power grid, and current, voltage, and even resistance values at key nodes. Safety constraint and alarm data, such as line load factor in equipment status, system activation and deactivation status of the ground-controlled AGC (including the corresponding activation and deactivation command status), and equipment protection models such as switching signals of regional devices.

[0087] For example, the data exchange content between the master station control center layer and the master station middle layer is shown in Table 1:

[0088] Table 1

[0089]

[0090]

[0091] The data interaction between the middle layer of the master station and the terminal station of the field station is as follows:

[0092] Edge cluster-based local master stations and distributed renewable energy stations exchange data using flexible protocols, such as the CEP plug-and-play protocol. For example, when temporary access to station equipment is required within the power grid system, this protocol supports rapid access and flexible configuration of station equipment, simplifying communication networking complexity, reducing operation and maintenance costs, and enabling efficient data exchange and intelligent management and control.

[0093] Based on the integrated power grid operation intelligent system (Operation Control System, OCS), the master station middle layer and the field terminal station exchange data through fixed protocols, such as 101 or 104 protocols. With its high reliability and versatility, it ensures stable communication between the field terminal station and the dispatching master station, seamlessly connects to the traditional power grid monitoring system, ensures smooth data flow under different technical architectures, and lays a solid communication foundation for active power control.

[0094] The data exchange content between the middle layer of the master station and the terminal station of the field station is shown in Table 2:

[0095] Table 2

[0096]

[0097]

[0098] In one embodiment, the substation control center layer includes a main control unit and a backup control unit, so that when the main control unit fails, the backup control unit is started.

[0099] Since the control unit at the substation control center layer adopts a redundant structure, in the event of a failure of the main control unit, the backup control unit can be seamlessly enabled when the main control unit fails, thereby maintaining the execution of equipment power control instructions.

[0100] In one embodiment, the substation control center layer also includes a fault repair module, which is used to locate the target data associated with the fault situation in the pre-backed up backup data based on the data index mechanism when a fault occurs in the main control unit; and repair the fault situation based on the target data.

[0101] For example, each backup data file contains a unique data index that can include information such as the backup time point, data type, and data source. The backup data can be stored in a hash table, and the data index mechanism is to quickly locate the target data associated with the failure situation from the hash table based on the unique data index.

[0102] Since the terminal station is at the software level, a data backup and recovery mechanism is established to back up the grid operation data and grid operation programs in the power grid system, ensuring that the main control unit can quickly restore to working status when a failure occurs, and stably execute equipment power control instructions and feedback information.

[0103] Assume that the master control unit at the substation control center layer is responsible for monitoring and controlling the operating status of multiple substations. The master control unit stores real-time operating data, equipment status information, historical data, and so on. If the master control unit fails, its functions must be quickly restored to ensure the normal operation of the power grid. The master control unit crashes due to a hardware failure and cannot operate normally. The substation terminal regularly backs up the key data of the master control unit (e.g., every hour) and stores it on a backup server. Each backup data file contains a unique data index that records information such as the backup time, data type, and data source. When a failure occurs, the backup control unit records the failure time as 2025-05-21 14:00:00 and the most recent backup time as 2025-05-21 13:00:00. Based on the failure time (i.e., the data index mechanism), the backup control unit queries the data index on the backup server and finds the most recently backed-up data file. The backup control unit retrieves backup data files (i.e., target data) from the backup server. These files include data such as voltage, current, and power for each substation; device status information (device_status): the operating status and fault signals of each device; and historical data (history_data): operational records from the past period. Next, the primary control unit's hardware is inspected and repaired to ensure proper operation. The data in the backup data files is imported into the primary control unit's database for data recovery. The voltage, current, and power data for each substation are restored to the primary control unit's real-time monitoring system for data recovery. The operating status and fault signals of each device are restored to the primary control unit's device management system for data recovery. The backed-up historical data is restored to the primary control unit's historical database to ensure that the primary control unit can query past data for data recovery. After the primary control unit starts up, it checks whether the real-time monitoring data is consistent with the backup data. It also checks whether the device status information is displayed correctly. It also checks whether the historical data can be queried normally. After verification, the primary control unit resumes normal operation, and grid monitoring and control functions are restored.

[0104] In one embodiment, the substation control center layer also includes a data backup module, which is used to fully back up the operating data of the substation according to a preset time period and store it in a backup storage space to obtain the backup data; and / or, the data backup module is used to detect changes in the operating data of the substation in real time; when the operating data changes, the changed operating data is recorded; and the changed operating data is backed up to a target incremental backup file to obtain the backup data.

[0105] like Figure 5As shown, the data backup method provided in this method includes regular full backup and real-time incremental backup, wherein the regular full backup is a full backup of the grid operation data and programs by the substation according to a preset time period, such as the period of low grid load in the early morning of each day. All data related to the operation of the distributed new energy station stored in the local storage device of the substation, including power generation power, equipment status, historical control instruction records, etc., as well as the program code on which the substation operation depends, are completely copied to an independent backup storage space. In this way, a complete system operation snapshot can be saved so that the data and program environment can be fully restored when needed. It is also convenient for subsequent review of the equipment operation status of the day, providing a full data mirror for subsequent inspections or operations and maintenance, and facilitating data comparison and related data analysis functions.

[0106] like Figure 5 As shown, real-time incremental data backup automatically detects and records new operational data and programs in the power grid system, backing them up in dedicated incremental backup files. For example, the power generated by a renewable energy station changes in real time, and the real-time monitoring data of equipment is constantly updated. This newly generated data is backed up promptly, ensuring data timeliness while reducing the backup data volume, improving backup efficiency, and minimizing the impact on system performance.

[0107] like Figure 5 As shown in the figure, in the application, when a device fails, the backup system's comprehensive data indexing mechanism, using timestamps and metadata (i.e., the data indexing mechanism), quickly locates and retrieves the most recent full backup and subsequent incremental backup data. An automated recovery program then initiates, writing the backup data and programs to the failed device's storage media in a specific order, using CRC calculations to verify data blocks for accuracy. Once data recovery is complete, the program automatically restores the system parameters, network settings, and device connection information from the time of the backup, enabling the slave device to quickly establish communication with the master and other field equipment, restoring control command execution and information feedback.

[0108] For example, suppose a lightning strike causes a failure in a substation at a distributed renewable energy station, damaging some storage devices and resulting in the loss of operational data. At this point, the substation's data backup and recovery mechanism kicks in. First, based on a time index, it locates the full backup data from the previous morning and the incremental backup data from the day before the failure. Then, an automated recovery program quickly extracts this backup data and writes it to a newly replaced storage device. During the write process, data integrity checks are performed to ensure data accuracy. After data recovery is complete, the system automatically performs initial configuration, resetting network parameters and enabling the substation to reestablish communication with the master station. After a brief system self-test and debugging, the substation quickly returns to its pre-failure operating state, resuming stable execution of control commands from the master station and feeding back real-time operational data to the master station. This ensures the normal operation of the entire distributed renewable energy active power automatic control system and minimizes the adverse impact of the failure on grid control.

[0109] In one embodiment, the grid dispatching information indicates batch control of multiple distributed new energy stations, and the master station control center layer also includes a batch control module, which is used to extract the power adjustment target value from the grid operation demand; and batch control the multiple distributed new energy stations according to the power adjustment target value.

[0110] The master station control center layer can simultaneously perform batch control of multiple distributed renewable energy stations based on grid regulation information. For example, during the peak regulation period of the grid, a unified power adjustment target value is sent to multiple distributed energy stations within the area through the batch control module to achieve overall output optimization of the distributed renewable energy stations. When an emergency failure occurs in the grid and some renewable energy power sources need to be quickly removed, the batch control module is used to batch issue remote control commands to control the grid-connected switches of the stations to ensure the safety and stability of the grid. In this way, efficient and coordinated control of the active power of distributed renewable energy stations is achieved, giving full play to the positive role of distributed renewable energy in grid operation, and improving the intelligent management level of the grid and its ability to cope with complex working conditions.

[0111] like Figure 6 As shown, in the power grid system provided in this application, a schematic diagram of the overall architecture of the power grid system is provided, and an overall framework and hierarchical structure of the dispatching end master station and the field station terminal station are constructed to ensure the security of data interaction and the effective transmission of instructions; the distributed new energy site configuration design ensures the reliability of data processing and instruction execution through the powerful configuration of the master station and the redundant design of the substation; the data interaction protocol design adopts appropriate protocols and standardized measurement data interaction according to different levels; thereby realizing the active power automatic control function, and utilizing monitoring and analysis, instruction generation and execution, group dispatching and group control mechanisms to achieve power grid security and high-quality operation. All links are closely connected, jointly promoting the effective control and coordinated development of distributed new energy in the power grid.

[0112] See also Figure 7 , Figure 7 The present application provides a power grid power control method, which is applied to the power grid system as described in any of the above embodiments, wherein the power grid power control method includes:

[0113] S201: Receive grid dispatch information, obtain grid operation data of the area to which the dispatching terminal master station belongs, and generate a power regulation strategy based on the grid dispatch information and the grid operation data.

[0114] Grid dispatch information can be power dispatch information for the power grid system. The region to which the dispatching master station belongs can be a provincial level. Grid operation data includes network-wide load and frequency data transmitted from the dispatching master station, as well as information such as power generation power and equipment status uploaded by substations. This data analysis results are generated by deeply mining and processing grid operation data using big data analysis technologies and intelligent algorithms, predicting grid load trends using time series analysis, and identifying the power generation performance and potential failure risks of distributed renewable energy stations using machine learning algorithms. Based on this data analysis and grid dispatch information, a power regulation strategy is generated.

[0115] For example, consider a provincial power grid system consisting of multiple distributed renewable energy sites (such as photovoltaic power plants and wind farms) as well as conventional power plants. The grid dispatching master station is responsible for monitoring and dispatching grid operations across the entire provincial region. Grid dispatch information includes the current provincial power dispatch indicators: ensuring a stable grid frequency of 50 Hz ± 0.2 Hz; prioritizing renewable energy generation to reduce carbon emissions; and ensuring stable grid operation to avoid overloads and power outages. Grid operation data includes network-wide load data: the current total load is 6000 MW, and the load is predicted to rise to 6500 MW within the next two hours. Frequency data includes the current grid frequency of 49.9 Hz. Data uploaded by the site terminal station includes: PV power plant A: current generating capacity is 300 MW, equipment is in normal condition, and the maximum output power is 500 MW. Wind farm B: current generating capacity is 400 MW, equipment is in normal condition, and the maximum output power is 600 MW. Thermal power unit C: current generating capacity is 2000 MW, equipment is in normal condition, and the maximum output power is 2500 MW. Other sites: Total generating capacity is 3300 MW. Grid-wide load and frequency data are obtained from the dispatching master station. Power generation and equipment status information is obtained from the site terminal. Grid operation data is preprocessed, such as data cleaning to remove outliers and noise; the data is formatted uniformly for subsequent analysis. Next, time series analysis is used to predict load trends within a preset timeframe (e.g., two hours). Based on historical load data and current trends, the load is predicted to increase from 6000 MW to 6500 MW in the next two hours. Machine learning algorithms (such as random forests or neural networks) are used to analyze the power generation performance of PV power plant A and wind farm B, assessing their power generation efficiency and stability. Based on equipment status data and historical fault records, machine learning algorithms (such as support vector machines) are used to identify potential failure risks. For example, equipment temperature data from PV power plant A is analyzed to predict whether there is an overheating risk. The resulting data analysis results include a load forecast: the load will increase from 6000 MW to 6500 MW in the next two hours. Power generation performance analysis: PV power plant A has good power generation efficiency, but there is a potential overheating risk. Wind farm B's power generation performance is stable, with no significant risk of failure. Equipment status: Thermal power unit C is operating normally and can serve as a backup power source. The power regulation strategy includes: PV power station A: Current power generation: 300 MW. Maximum output power: 500 MW. Increase power generation: 200 MW (reaching maximum output power). Wind farm B: Current power generation: 400 MW. Maximum output power: 600 MW. Increase power generation: 200 MW (reaching maximum output power). Thermal power unit C: Current power generation: 2000 MW. Maximum output power: 2500 MW. Increase power generation: 300 MW (meeting remaining load demand).

[0116] S202: Decompose the power regulation instructions in the power regulation strategy to obtain a station power control instruction for each distributed new energy station in the area to which the station terminal station belongs.

[0117] Assume that the grid dispatching master station has issued the following power regulation policy: Total power regulation target: Increase total generated power by 300 MW to meet future load demand. The dispatching master station's area includes the following distributed renewable energy sites: PV power plant A: Current generated power is 100 MW, with a maximum output of 200 MW. Wind farm B: Current generated power is 150 MW, with a maximum output of 300 MW. Small hydropower plant C: Current generated power is 50 MW, with a maximum output of 100 MW.

[0118] Power regulation instruction decomposition process:

[0119] Analyze the power generation margin of each site: PV plant A: Current power generation: 100 MW. Maximum output: 200 MW. Power generation margin: 200 MW - 100 MW = 100 MW. Wind farm B: Current power generation: 150 MW. Maximum output: 300 MW. Power generation margin: 300 MW - 150 MW = 150 MW. Small hydropower plant C: Current power generation: 50 MW. Maximum output: 100 MW. Power generation margin: 100 MW - 50 MW = 50 MW.

[0120] Decomposition of power regulation instructions:

[0121] Total power regulation target: Increase by 300MW. Allocation strategy: Prioritize sites with greater power generation margins to maximize renewable energy utilization. PV Plant A: Increase power generation by 100MW (reaching a maximum output of 200MW). Wind Farm B: Increase power generation by 150MW (reaching a maximum output of 300MW). Hydropower Plant C: Increase power generation by 50MW (reaching a maximum output of 100MW).

[0122] Generate site power control instructions: PV plant A: Increase power generation by 100 MW. Wind farm B: Increase power generation by 150 MW. Small hydropower plant C: Increase power generation by 50 MW.

[0123] S203: Decomposing the station power adjustment instruction according to the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain the equipment power control instruction.

[0124] Assume that the power adjustment command for a site includes: PV Plant A: Reduce power generation to 200 MW. The site operating data includes: PV Plant A: Current total power generation: 300 MW. Current power generation of each PV array: 30 MW.

[0125] The instruction decomposition process is as follows:

[0126] PV Plant A: Target total power: 200 MW. Current total power: 300 MW. Total power reduction required: 100 MW. Minimum stable operating power of PV Plant A: 100 MW. Maximum output power of each subarray: 30 MW. Minimum stable operating power of each subarray: 10 MW.

[0127] Decomposition strategy: Each subarray currently generates 30 MW, and the total power needs to be reduced by 100 MW. Select five subarrays and reduce their power by 20 MW each to reach the target power of 200 MW.

[0128] Device power control command: Subarray 1: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 2: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 3: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 4: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 5: Reduce power by 20 MW (from 30 MW to 10 MW). Subarrays 6, 7, 8, 9, and 10: Maintain the current power at 30 MW.

[0129] The specific power control instructions for distributed new energy stations are as follows:

[0130] PV power station A: Subarray 1: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 2: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 3: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 4: Reduce power by 20 MW (from 30 MW to 10 MW). Subarray 5: Reduce power by 20 MW (from 30 MW to 10 MW). Subarrays 6, 7, 8, 9, and 10: Maintain the current power at 30 MW.

[0131] S204: Send the device power control instruction to the execution unit of the distributed new energy site, so that the execution unit executes the power adjustment operation corresponding to the device power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

[0132] Through the local monitoring system and communication network of the terminal station, the power control instructions for the equipment corresponding to each distributed new energy station are quickly transmitted to the execution units such as inverters and power generation equipment. The execution unit accurately adjusts the power generation power of the execution unit according to the power control instructions of the instruction equipment. At the same time, the execution results and execution data such as the new station operation data are fed back to the middle layer of the master station. Then, it is uploaded to the master control center layer through the middle layer of the master station, forming a closed-loop control circuit. In this process, the redundant configuration and reliable communication of the terminal station ensure the timeliness and accuracy of the execution of the equipment power control instructions, and can guarantee the stable operation of the system even in the event of equipment failure or communication interference.

[0133] Optionally, based on grid dispatch information, multiple distributed renewable energy stations can be controlled simultaneously in batches. For example, during peak-shaving periods, the group control function can be used to send a unified power adjustment target value to multiple stations in the region to optimize the overall output of distributed renewable energy. When an emergency failure in the grid requires rapid removal of some renewable energy power sources, the group control function can be used to send batch remote control commands to control the station's grid-connected switches to ensure grid security and stability. In this way, efficient and coordinated control of the active power of distributed renewable energy stations can be achieved, fully leveraging the positive role of distributed renewable energy in grid operation and improving the grid's intelligent management level and ability to cope with complex operating conditions.

[0134] Take active power automatic control as an example, Figure 8 As shown, this application provides a power grid power control solution, which is as follows:

[0135] The implementation of active power automatic control is the core link of the entire distributed renewable energy active power automatic control system. It relies on the basic support of system architecture, site configuration and data interaction protocol, and realizes the safe and high-quality operation of the power grid through precise control strategies and efficient execution mechanisms. The specific function implementation logic is as follows:

[0136] The real-time data monitoring and analysis system continuously collects various operational data from the power grid and power plants. This includes grid-wide load and frequency data transmitted from provincial master stations, as well as information such as power generation and equipment status uploaded by power plants. This data is deeply mined and processed using big data analytics and intelligent algorithms. Time series analysis is used to predict grid load trends, and machine learning algorithms are used to identify the power generation performance and potential failure risks of renewable energy power plants. Based on this data analysis, combined with pre-set control strategies and grid operating constraints, precise active power adjustment commands are generated at the master station. For example, if grid load is predicted to increase within a certain period of time and renewable energy generation capacity is sufficient, the master station calculates and issues a command to increase the active power output of the power plant. If a station equipment anomaly is detected that could affect power generation safety, a power reduction or shutdown command is promptly issued. Once the command is issued to the power plant terminal, the substation rapidly transmits it to the execution units, such as inverters and power generation equipment, via the local monitoring system and communication network. The execution units precisely adjust power generation according to the command and simultaneously transmit the execution results and new operating data back to the substation, which then uploads them to the master station, forming a closed-loop control system. During this process, the redundant configuration and reliable communication of the substations ensure the timeliness and accuracy of command execution, and guarantee the stable operation of the system even in the event of equipment failure or communication interference. In terms of group adjustment and control, the master station can simultaneously perform batch control of multiple distributed renewable energy sites according to the operation requirements of the power grid. For example, during the peak regulation period of the power grid, the group adjustment function is used to send a unified power adjustment target value to multiple sites in the area to achieve overall output optimization of distributed renewable energy; when an emergency failure occurs in the power grid and some renewable energy power sources need to be quickly removed, the group control function is used to batch issue remote control commands to control the site grid-connected switches to ensure the safety and stability of the power grid. In this way, efficient and coordinated control of the active power of distributed renewable energy sites is achieved, giving full play to the positive role of distributed renewable energy in power grid operation, and improving the intelligent management level of the power grid and its ability to cope with complex working conditions.

[0137] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0138] In the embodiment of the present application, by clearly dividing the functional levels of the dispatching end master station and the substation terminal in the power grid system and ensuring close collaboration between the various levels, the efficiency of command transmission and data interaction is greatly improved. The power grid dispatching information is received and the power grid operation data of the area to which the dispatching end master station belongs is obtained. Based on this information, a power regulation strategy can be generated, and the power regulation instructions can be further decomposed into specific station power control instructions. Combined with the operation data of the distributed new energy station collected by the substation intermediate layer and the station layer, the station power regulation instructions are further decomposed into equipment power control instructions and sent to the execution unit of the distributed new energy station. After the execution unit performs the power adjustment operation, it feeds back the execution data to the master station control center layer and the master station middle layer, so that the power grid can quickly and accurately respond to the dynamic changes of distributed renewable energy, so as to quickly respond to changes in grid load and emergencies. In complex working conditions, it can accurately adjust the power to avoid causing grid frequency and voltage fluctuations, ensuring that the grid can still maintain stable operation under complex working conditions, enhancing the grid's regulation and adaptability to renewable energy, and realizing refined management from grid dispatching instructions to equipment execution, ensuring the stability and flexibility of grid operation, improving the utilization efficiency of renewable energy, and at the same time enhancing the grid's ability to respond to equipment failures, optimizing the overall dispatching efficiency and reliability of grid operation.

[0139] 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.

[0140] 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 power grid credit control methods provided in the embodiments of the present application. For example, the instructions can execute the following steps:

[0141] Receive grid dispatch information, obtain grid operation data of the area to which the dispatching end master station belongs, and generate a power regulation strategy based on the grid dispatch information and grid operation data; decompose the power regulation instructions in the power regulation strategy to obtain the station power control instructions of each distributed new energy station in the area to which the station terminal station belongs; decompose the station power regulation instructions according to the station operation data of the distributed new energy station collected by the substation middle layer and the station layer to obtain the equipment power control instructions; send the equipment power control instructions to the execution unit of the distributed new energy station, so that the execution unit executes the power regulation operation corresponding to the equipment power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

[0142] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0143] The storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0144] Since the instructions stored in the storage medium can execute the steps of any of the grid power methods provided in the embodiments of the present application, the beneficial effects that can be achieved by any of the grid power control methods provided in the embodiments of the present application can be achieved. For details, please refer to the previous embodiments and will not be repeated here.

[0145] The above is a detailed introduction to a power grid system, a power grid power control method and a storage medium provided in the embodiments 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 power grid system, characterized in that: The power grid system includes a dispatching end master station and a field station terminal station, wherein the dispatching end master station includes a master station control center layer and a master station middle layer, and the field station terminal station includes a substation control center layer, a substation middle layer and a field station layer; The master station control center layer is used to receive power grid dispatch information, obtain power grid operation data of the area to which the dispatching end master station belongs, and generate a power regulation strategy based on the power grid dispatch information and the power grid operation data; The master station intermediate layer is used to decompose the power regulation instructions in the power regulation strategy to obtain the station power control instructions of each distributed new energy station in the area to which the station terminal station belongs; The substation control center layer is used to decompose the station power adjustment instruction according to the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain the equipment power control instruction; The station layer is used to send the device power control instruction to the execution unit of the distributed new energy station, so that the execution unit executes the power adjustment operation corresponding to the device power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

2. The power grid system according to claim 1, characterized in that: The master station control center layer includes: A working condition analysis module, used for analyzing the power grid operating data to obtain the power grid operating condition; A strategy generation module, configured to generate a power regulation strategy based on the grid operating conditions and the grid dispatch information; The master station middle layer includes: The instruction decomposition module is used to decompose the power regulation instructions in the power regulation strategy based on the grid operation constraints to obtain the station power control instructions of each distributed new energy station in the area where the station terminal station belongs.

3. The power grid system according to claim 1, characterized in that: The dispatching end master station and the yard terminal substation include a main communication link and at least one backup communication link, so that data exchange can be performed through the at least one backup communication link in the event of a failure of the main communication link.

4. The power grid system according to claim 1, characterized in that: The master station control center layer and the master station intermediate layer perform data exchange through fixed protocols; and The master station middle layer and the field station terminal station exchange data via a non-fixed protocol / fixed protocol.

5. The power grid system according to claim 1, characterized in that: The substation control center layer includes a main control unit and a backup control unit, so that the backup control unit can be started in the event of a failure of the main control unit.

6. The power grid system according to claim 5, characterized in that: The substation control center layer further includes a fault recovery module, which is used to locate target data associated with the fault condition in the pre-backed-up backup data based on a data index mechanism when a fault occurs in the main control unit; The fault condition is repaired based on the target data.

7. The power grid system according to claim 6, characterized in that: The substation control center layer further includes a data backup module, which is used to perform a full backup of the substation's operating data according to a preset time period and store the full backup data in a backup storage space to obtain the backup data; And / or, the data backup module is used to detect changes in the operating data of the substation in real time; When the operating data changes, record the changed operating data; The changed running data is backed up to a target incremental backup file to obtain the backup data.

8. The power grid system according to any one of claims 1 to 7, characterized in that: The grid dispatching information indicates batch control of multiple distributed new energy stations. The master station control center layer also includes a batch control module, which is used to extract the power adjustment target value from the grid operation demand; and batch control the multiple distributed new energy stations according to the power adjustment target value.

9. A power grid power control method, characterized in that: Applied to the power grid system according to any one of claims 1 to 8, the method comprises: Receive grid dispatch information, obtain grid operation data of the area to which the dispatching terminal master station belongs, and generate a power regulation strategy based on the grid dispatch information and the grid operation data; Decomposing the power regulation instructions in the power regulation strategy to obtain a station power control instruction for each distributed new energy station in the area to which the station terminal station belongs; Decomposing the station power adjustment instruction according to the station operation data of the distributed new energy station collected by the substation intermediate layer and the station layer to obtain the equipment power control instruction; The device power control instruction is sent to the execution unit of the distributed new energy site, so that the execution unit executes the power adjustment operation corresponding to the device power control instruction, and feeds back the execution data to the master station control center layer and the master station middle layer.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the grid power control method according to claim 9 are implemented.

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