A source-network-load-storage collaborative regulation method, electronic equipment, computer readable storage medium and program product

Abstract

The application relates to the field of smart grids, and provides a source-grid-load-storage collaborative regulation method, an electronic device, a computer readable storage medium and a program product. The method comprises the following steps: acquiring source-grid-load-storage data of a region to be regulated, wherein the source-grid-load-storage data comprises power supply side data, grid side data, load side data and energy storage side data; inputting the source-grid-load-storage data into a preset large language model to obtain second source-grid-load-storage data; determining a first adjustment range based on the second source-grid-load-storage data; generating a first parameter set of a grid cloud control platform according to the first adjustment range and a preset grid-connected power interval; and adjusting grid-connected power of the terminal power equipment to the preset grid-connected power interval through the grid cloud control platform based on the first parameter set. The application can improve the efficiency of source-grid-load-storage data collaboration and rational resource scheduling.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, and more specifically, to a method for coordinated regulation of power generation, grid, load and storage, electronic equipment, computer-readable storage medium and program products. Background Technology

[0002] Against the backdrop of the deepening "dual-carbon" strategy and the accelerated construction of new power systems, the integration of power generation, grid, load, and storage has become a core path to solve the challenges of the volatility and intermittency of distributed energy sources (photovoltaics, wind power, etc.) access. Currently, the smart grid faces pain points such as heterogeneous and fragmented multi-source data, insufficient precision in coordinated regulation, and lagging cloud-edge-device response. Traditional data governance methods are ill-suited to the real-time integration needs of multi-dimensional data from photovoltaics, energy storage, load, and grid operation. Regulation strategies lack deep coupling with dual-carbon objectives and electricity market transactions, limiting grid operating efficiency and renewable energy absorption capacity. Simultaneously, with the implementation of the PMS3.0 architecture and the rapid development of virtual power plants and the electricity trading market, there is an urgent need to build an efficient and collaborative power generation, grid, load, and storage regulation system based on digital technology. In practical applications, multi-dimensional data from photovoltaics, energy storage, load, and grid operation typically come from different devices and platforms. Existing technologies largely rely on manual configuration of fixed data templates or preset interface specifications to complete data access and processing. When the type of accessed equipment changes or different manufacturers use different data formats, the efficiency of subsequent regulation strategies is affected. Therefore, how to adopt a data coordination method for source-grid-load-storage to ensure the rational scheduling of distributed energy and improve the regulation efficiency of the source-grid-load-storage regulation system is an urgent technical problem to be solved. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a source-grid-load-storage coordinated control method, electronic device, computer-readable storage medium and program product, which can improve the efficiency of source-grid-load-storage data coordination and resource rational scheduling.

[0004] To achieve the above technical objectives, the technical solution adopted in this application is as follows:

[0005] In a first aspect, embodiments of this application provide a method for coordinated regulation of power generation, grid, load, and storage, characterized in that the method is used in a power grid cloud control platform, and the method includes:

[0006] The source-grid-load-storage data of the area to be regulated is obtained. The source-grid-load-storage data includes power source data, grid-side data, load-side data, and energy storage-side data. The power source data is used to characterize the actual output power of the power generation equipment. The grid-side data is used to characterize the real-time exchange power of the grid connection point. The load-side data is used to characterize the actual load power and the power adjustment range of the load equipment. The energy storage-side data is used to characterize the actual charging and discharging power and state of charge of the energy storage equipment.

[0007] The source-grid-load-storage data is input into a preset large language model. Based on a preset keyword library, the source-grid-load-storage data is identified by keywords through the preset large language model and output according to a preset data format to obtain second source-grid-load-storage data. The second source-grid-load-storage data includes second power source side data, second grid side data, second load side data, and second energy storage side data.

[0008] Based on the second source-grid-load-storage data, a first adjustment range is determined. The first adjustment range is used to characterize the power boundary of the terminal power equipment. The first adjustment range includes the charging and discharging power range of the energy storage equipment, the power adjustment range of the load equipment, and the power limiting range of the power generation equipment. The terminal power equipment includes energy storage equipment, load equipment, and power generation equipment.

[0009] Based on the first adjustment range and the preset grid-connected power range, a first parameter set of the power grid cloud control platform is generated. The first parameter set is a reference adjustment value for the terminal power equipment. The reference adjustment value is obtained based on the second source-grid-load-storage data and the preset grid-connected power range.

[0010] Based on the first set of parameters, the grid-connected power of the terminal power equipment is adjusted to a preset grid-connected power range through the power grid cloud control platform. The preset grid-connected power range is used to characterize the target control range of the grid-connected power by the power grid cloud control platform.

[0011] According to the first aspect, the second source-grid-load-storage data is obtained by identifying keywords in the source-grid-load-storage data based on a preset keyword library and using the preset large language model, and outputting the data according to a preset data format, including:

[0012] The semantic information of the source network load storage data is extracted using the preset large language model. The semantic information includes field names and units of measurement.

[0013] The mapping relationship between the field names of the semantic information and the keywords of the preset keyword library is determined by the preset large language model. The preset keyword library is a pre-constructed mapping library that uses power generation, grid, load and storage terms as keywords.

[0014] Using the preset large language model, the field names with determined mapping relationships and the corresponding units of measurement are output according to a preset data format to obtain the second source-grid-load-storage data. The preset data format includes preset field names and preset units of measurement.

[0015] According to the first aspect, between obtaining the second source-grid-load-storage data and determining the first adjustment range based on the second source-grid-load-storage data, the method further includes:

[0016] Numerical boundary verification is performed based on the rated parameters and operating thresholds of the terminal power equipment. The numerical boundary verification is used to determine whether the actual output power of the power generation equipment, the actual charging and discharging power of the energy storage equipment, and the state of charge are within the allowable range.

[0017] The second source-grid-load-storage data that fails the numerical boundary verification is identified as abnormal data;

[0018] The historical data of the terminal power equipment corresponding to the abnormal data is used as the replacement data to replace the abnormal data. The historical data is the data of the second source-grid-load-storage data of the terminal power equipment when it most recently passed the numerical boundary check.

[0019] According to the first aspect, determining the first adjustment range based on the second source-grid-load-storage data includes:

[0020] Based on the state of charge, preset charge limit range, maximum charge and discharge power and actual charge and discharge power of the energy storage device in the second energy storage side data, the charge and discharge power range of the energy storage device is determined.

[0021] Based on the actual power and preset power range of the load equipment in the second load-side data, the power adjustment range of the load equipment is determined;

[0022] Based on the actual output power and preset minimum allowable output power of the power generation equipment in the second power supply side data, the power limit range of the power generation equipment is determined.

[0023] The charging and discharging power range of the energy storage device, the power adjustment range of the load device, and the power limiting range of the power generation device are defined as the first adjustment range.

[0024] According to the first aspect, the generation of a first parameter set through the power grid cloud control platform based on the first adjustment range and the preset grid-connected power range includes:

[0025] The theoretical grid-connected power is calculated based on the actual charging and discharging power in the second energy storage side data, the actual power in the second load side data, and the actual output power in the second power supply side data.

[0026] Based on the second grid-side data, the theoretical grid-connected power is corrected to obtain the corrected grid-connected power;

[0027] When the corrected grid-connected power is not within the preset grid-connected power range, the adjustment amount is obtained based on the difference between the corrected grid-connected power and the limit of the preset grid-connected power range;

[0028] Based on the adjustment amount and the first adjustment range, the adjustment amount is allocated according to the preset adjustment priority through the power grid cloud control platform to obtain the reference adjustment value of the terminal power equipment;

[0029] The first parameter set is generated based on the reference adjustment value.

[0030] According to the first aspect, the step of allocating the adjustment amount according to a preset adjustment priority through the power grid cloud control platform based on the adjustment amount and the first adjustment range to obtain the reference adjustment value of the terminal power equipment includes:

[0031] If the corrected grid-connected power is less than the lower limit of the preset grid-connected power range, the preset adjustment priority is determined to sequentially increase the actual charging power of the second energy storage side data, the actual power of the second load side data, and decrease the actual output power of the second power supply side data. The adjustment amount is allocated to the corresponding terminal power equipment through the power grid cloud control platform, and the reference adjustment value of the terminal power equipment is determined within the corresponding first adjustment range.

[0032] If the corrected grid-connected power is greater than the upper limit of the preset grid-connected power range, the preset adjustment priority is determined as follows: increase the actual output power of the second power source data, increase the actual discharge power of the second energy storage data, and decrease the actual power of the second load data in sequence. The adjustment amount is allocated to the corresponding terminal power equipment through the power grid cloud control platform, and the reference adjustment value of the terminal power equipment is determined within the corresponding first adjustment range.

[0033] If the adjustment amount to be allocated to the current terminal power device does not fall within the first adjustment range in the current preset adjustment priority, the unallocated adjustment amount will be allocated to the terminal power device corresponding to the next priority.

[0034] Secondly, embodiments of this application also provide an electronic device, the electronic device including a processor and a memory coupled to each other, the memory storing a computer program, and when the computer program is executed by the processor, causing the electronic device to perform the method as described in the first aspect.

[0035] Thirdly, embodiments of this application also provide a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, which, when run on a computer, causes the computer to perform the method described in the first aspect.

[0036] Fourthly, embodiments of this application also provide a program product, characterized in that it includes a computer program, which, when executed by a processor, implements the method described in the first aspect.

[0037] The invention employing the above technical solution has the following advantages:

[0038] This application utilizes a pre-defined large language model to perform semantic recognition on source-grid-load-storage data. It avoids relying on fixed interface templates and can uniformly identify data that matches keywords but has different expressions, thereby improving the accuracy of heterogeneous source-grid-load-storage data access and data processing efficiency. By determining the first adjustment range based on second source-grid-load-storage data, the control is combined with the boundary of the actual adjustable power of the terminal power equipment in the current state. This avoids unreasonable control ranges that could trigger chain reactions when adjusting equipment power, improving the rationality of coordinated control. By controlling the terminal power equipment through a first parameter set, coordinated control is both constrained by the actual capacity of the terminal power equipment and serves the grid-connected power target control, thereby achieving coordinated allocation among terminal power equipment and improving the efficiency of source-grid-load-storage data coordination and rational resource scheduling. Attached Figure Description

[0039] This application can be further illustrated by the non-limiting embodiments given in the accompanying drawings. It should be understood that the following drawings only illustrate some embodiments of this application and should not be considered as limiting the scope. For those skilled in the art, other related drawings can be obtained from these drawings without any inventive effort.

[0040] Figure 1 A flowchart of a source-grid-load-storage coordinated regulation method provided in an embodiment of this application. Detailed Implementation

[0041] The present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that similar or identical parts are referred to by the same reference numerals in the drawings or description. Implementations not shown or described in the drawings are forms known to those skilled in the art. In the description of this application, terms such as "first" and "second" are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0042] Please refer to Figure 1 This application provides a method for coordinated regulation of power generation, grid, load, and energy storage, which can be applied to electronic devices and can be executed or implemented by electronic devices. The electronic devices can be, but are not limited to, personal computers, smartphones, and other electronic devices. The coordinated regulation method for power generation, grid, load, and energy storage may include the following steps:

[0043] S10 acquires the source-grid-load-storage data of the area to be regulated. The source-grid-load-storage data includes power source side data, grid side data, load side data, and energy storage side data. The power source side data is used to characterize the actual output power of the power generation equipment. The grid side data is used to characterize the real-time exchange power of the grid connection point. The load side data is used to characterize the actual load power and the power adjustment range of the load equipment. The energy storage side data is used to characterize the actual charging and discharging power and state of charge of the energy storage equipment.

[0044] S20 inputs the source-grid-load-storage data into a preset large language model, and based on a preset keyword library, performs keyword recognition on the source-grid-load-storage data through the preset large language model, and outputs it according to a preset data format to obtain second source-grid-load-storage data. The second source-grid-load-storage data includes second power source side data, second grid side data, second load side data, and second energy storage side data.

[0045] S30 determines a first adjustment range based on the second source-grid-load-storage data. The first adjustment range is used to characterize the power boundary of the terminal power equipment. The first adjustment range includes the charging and discharging power range of the energy storage equipment, the power adjustment range of the load equipment, and the power limiting range of the power generation equipment. The terminal power equipment includes energy storage equipment, load equipment, and power generation equipment.

[0046] S40 generates a first parameter set for the power grid cloud control platform based on the first adjustment range and the preset grid-connected power range. The first parameter set is a reference adjustment value for the terminal power equipment. The reference adjustment value is obtained based on the second source-grid-load-storage data and the preset grid-connected power range.

[0047] Based on the first set of parameters, S50 adjusts the grid-connected power of the terminal power equipment to a preset grid-connected power range through the power grid cloud control platform. The preset grid-connected power range is used to characterize the target control range of the grid-connected power by the power grid cloud control platform.

[0048] In S10, the grid connection point, power generation equipment, load equipment, and energy storage equipment corresponding to the area to be regulated are identified. According to a preset regulation cycle, corresponding operational data is obtained from the corresponding data acquisition devices, energy management systems, edge gateways, or cloud data interfaces of each device. The area to be regulated can be a park microgrid, a building distribution area, or other power consumption area with source-grid-load-storage resources. To facilitate subsequent unified processing, each source-grid-load-storage data item can carry a corresponding data identifier, acquisition time, and unit of measurement.

[0049] The power supply side data is used to characterize the actual output power of power generation equipment within the controlled area. This data also includes the power curtailment currently implemented by the power generation equipment. The power generation equipment can include distributed photovoltaic (PV), distributed wind power, gas turbine generators, or other distributed power sources. The actual output power can be the active power output of the power generation equipment at the current data collection time, reflecting the scale of electricity currently supplied by local power sources in the controlled area. For example, when multiple PV inverters are installed within the controlled area, the actual output power of each inverter can be obtained separately as power supply side data. The grid side data is used to characterize the real-time exchange power between the controlled area and the external grid at the grid connection point. The grid connection point can be understood as the power exchange node connecting the controlled area to the public grid. The real-time exchange power can be collected by the grid connection point metering device and the distribution monitoring device. The real-time exchange power reflects whether the controlled area is currently drawing power from or sending power to the external grid. A positive real-time exchange power is defined as the controlled area purchasing power from the external grid, and a negative real-time exchange power is defined as the controlled area sending power in reverse to the external grid. Load-side data is used to characterize the actual power consumption of load devices within the controlled area and the power adjustment range of the load devices. Load-side data also includes the power adjustment currently performed by the load devices. The load devices can include ordinary power loads and adjustable loads, where adjustable loads can include charging piles, air conditioning systems, and other load devices whose power can be adjusted within a preset range. The actual load power reflects the current power demand in the controlled area; the power adjustment range characterizes the range of power that the load devices can increase or decrease within the current control cycle, and can be expressed by the adjustable power value, adjustable power value, or maximum adjustable ratio of the load devices. Energy storage-side data is used to characterize the actual charging and discharging power and state of charge of energy storage devices within the controlled area. The energy storage devices can be electrochemical energy storage systems. The actual charging and discharging power reflects the power change of the energy storage devices in charging, discharging, or standby states; the state of charge characterizes the proportion of the energy storage device's current remaining power to its available capacity, used to determine whether the energy storage device still has the ability to continue charging or discharging within the current control cycle. When the state of charge of an energy storage device approaches the preset upper limit of charge, its ability to continue charging decreases; when the state of charge of an energy storage device approaches the preset lower limit of charge, its ability to continue discharging decreases.

[0050] In S20, based on a preset keyword library, the source-grid-load-storage data is identified using a preset large language model, and output according to a preset data format to obtain second source-grid-load-storage data, including:

[0051] S21 uses the preset large language model to extract semantic information from the source network load storage data, the semantic information including field names and units of measurement;

[0052] S22 determines the mapping relationship between the field names of the semantic information and the keywords of the preset keyword library through the preset large language model. The preset keyword library is a pre-constructed mapping library that uses power generation, grid, load and storage terms as keywords.

[0053] S23 uses the preset large language model to output the field names with the determined mapping relationship and the corresponding units of measurement according to the preset data format to obtain the second source-grid-load-storage data. The preset data format includes preset field names and preset units of measurement.

[0054] In S21, field names can include field names from databases such as the acquisition system or edge gateway, such as "PV Output," "PV_Output," "Grid Connection Point Power," "SOC," and "Load_Power," reflecting the business meaning of the data in the original system. Units of measurement can include kW, W, MW, kWh, %, A, and V. When source-grid-load-storage data is obtained from communication messages, the semantic information can be extracted from the aforementioned data. When different systems use different naming methods for the same type of data, a pre-defined large language model can be used to perform preliminary parsing of field names based on a pre-defined keyword library, such as a proper noun dictionary and equipment type table. For example, for data with field names such as "PV_Output," "PV Active Power," and "Inverter Output Power," both the field name and unit of measurement can be extracted.

[0055] In S22, the preset large language model can be a large language model pre-deployed in the power grid cloud control platform or its associated servers. The large language model can adopt general models such as DeepSeek and Tongyi Qianwen, etc., without limitation. The preset large language model can identify the physical meaning corresponding to different source-grid-load-storage data based on field names and units of measurement. The preset large language model performs semantic understanding on field names and matches these field names with power field terms in a preset keyword library. The preset keyword library can pre-include keywords or standard terms such as "actual output power of generating equipment," "real-time exchange power at grid connection point," "actual load power," "adjustable power of load equipment," "actual charging and discharging power of energy storage equipment," and "state of charge of energy storage equipment." For example, when the field name is "PV_Output," "photovoltaic active power," or "inverter output power," the preset large language model can map it to the keyword "actual output power of generating equipment"; when the field name is "SOC" or "remaining battery percentage," the preset large language model can map it to the keyword "state of charge of energy storage equipment." This mapping relationship clarifies the actual electrical physical meaning of different field names.

[0056] In step S23, after determining the standard keyword corresponding to a certain field name, the field name is converted into a preset field name, and its unit of measurement is also converted to a preset unit of measurement, thereby obtaining the second source-grid-load-storage data. The preset data format can include unified field names, unified units of measurement, and corresponding data categories. For example, fields such as "PV_Output" and "Photovoltaic Active Power" are uniformly output as the preset field name "Actual Output Power of Power Generation Equipment," and uniformly use kW as the unit of measurement; fields such as "SOC" and "Battery Remaining Capacity Percentage" are uniformly output as the preset field name "State of Charge of Energy Storage Equipment," and uniformly use percentage as the unit of measurement. Thus, source-grid-load-storage data from different sources, with different naming methods, and different units of measurement can be converted into second source-grid-load-storage data with a consistent format and clear physical meaning. The second source-grid-load-storage data includes standardized power source side data, standardized grid side data, standardized load side data, and standardized energy storage side data.

[0057] After obtaining the second source-grid-load-storage data, and before determining the first adjustment range based on the second source-grid-load-storage data, the process also includes:

[0058] Numerical boundary checks are performed based on the rated parameters and operating thresholds of the terminal power equipment. These checks determine whether the actual output power of the power generation equipment, the actual charging and discharging power of the energy storage equipment, and the state of charge are within acceptable limits. Data from the second power generation, grid, load, and storage system that fails the numerical boundary check is identified as abnormal data. Historical data from the terminal power equipment corresponding to the abnormal data is used as replacement data to replace the abnormal data. The historical data refers to the data from the time when the second power generation, grid, load, and storage data of the terminal power equipment most recently passed the numerical boundary check.

[0059] Numerical boundary checks are performed based on the rated parameters and operating thresholds of the terminal power equipment. Rated parameters and operating thresholds may include the rated output range of the power generation equipment, the maximum charging power, maximum discharging power, upper limit of state of charge (SOC), and lower limit of SOC of the energy storage equipment. Through verification, it can be determined whether the actual output power of the power generation equipment, the actual charging and discharging power of the energy storage equipment, and the SOC of the energy storage equipment are within the allowable operating range for the corresponding equipment. For example, if the SOC of a certain energy storage equipment exceeds the preset upper limit of SOC, or the actual discharging power exceeds the maximum allowable discharging power, the data can be considered not to meet the numerical boundary requirements.

[0060] When a second-generation grid-load-storage data point fails the numerical boundary verification, that data point is identified as abnormal. For abnormal data, historical data from the most recent numerical boundary verification of the corresponding terminal power equipment can be used as substitute data. This avoids the current control cycle being unable to continue due to data anomalies from a single device. For example, when the energy storage state of charge data is abnormal, the most recent numerical boundary verification data for that energy storage device, or data from the previous cycle that passed the numerical boundary verification, can be used as substitute data.

[0061] Secondary source-grid-load-storage data cannot guarantee that the data will necessarily meet actual operating conditions. Therefore, verification improves the reliability of subsequent grid-connected power regulation and prevents the grid cloud control platform from generating control parameters that do not conform to the actual capabilities of equipment or the physical laws of the grid based on erroneous data. It also avoids the need for staff to repeatedly compare data, thus improving the stability of source-grid-load-storage coordination.

[0062] In S30, determining the first adjustment range based on the second source-grid-load-storage data includes:

[0063] S31 determines the charging and discharging power range of the energy storage device based on the state of charge, preset charge limit range, maximum charging and discharging power and actual charging and discharging power of the energy storage device in the second energy storage side data;

[0064] S32 determines the power adjustment range of the load equipment based on the actual power and preset power range of the load equipment in the second load-side data;

[0065] S33 determines the power limit range of the power generation equipment based on the actual output power and preset minimum allowable output power of the power generation equipment in the second power supply side data;

[0066] S34 determines the charging and discharging power range of the energy storage device, the power adjustment range of the load device, and the power limiting range of the power generation device as the first adjustment range.

[0067] In step S31, the charging and discharging power range of the energy storage device is determined based on its state of charge (SBC), preset charge limit range, maximum charging and discharging power, and actual charging and discharging power. If the SBC of the energy storage device is within the preset charge limit range, it indicates that the energy storage device still has the ability to participate in charging or discharging regulation. Based on this, the range of charging or discharging power that the energy storage device can further increase within the current regulation cycle is determined according to the maximum charging power, maximum discharging power, and current actual charging and discharging power. If the SBC of the energy storage device reaches or approaches the preset upper charge limit, further increases in charging power are restricted or prohibited; if the SBC of the energy storage device reaches or approaches the preset lower charge limit, further increases in discharging power are restricted or prohibited.

[0068] In one implementation, suppose an energy storage device has a preset charge limit range of 20% to 90%, a maximum charging power of 500kW, a maximum discharging power of 500kW, a current state of charge (SOC) of 85%, and a current actual charging power of 300kW. Since the current SOC of 85% has not yet reached the preset SOC limit of 90%, the energy storage device can continue charging. Simultaneously, because its maximum charging power is 500kW and its current actual charging power is 300kW, the energy storage device's maximum increase in charging power during the current control cycle cannot exceed 200kW. If the current SOC has already reached 90%, the maximum increase in charging power can be set to 0 to prevent the energy storage device from continuing to charge and exceeding the SOC limit. Correspondingly, if the current SOC is close to 20%, further increases in discharging power are limited or prohibited to prevent the energy storage device from over-discharging.

[0069] In step S32, the power adjustment range of the load device is determined based on its actual power and a preset power range. The preset power range characterizes the upper and lower limits of the power allowed for the load device to operate. By comparing the current actual power of the load device with this preset power range, it can be determined how much power consumption the load device can increase or decrease within the current control cycle. In one embodiment, assuming a charging pile is an adjustable load device with a preset power range of 50kW to 150kW and a current actual power of 100kW, since the current actual power of 100kW is lower than the preset upper power limit of 150kW, the charging pile can increase its power consumption by a maximum of 50kW within the current control cycle. Simultaneously, since the current actual power of 100kW is higher than the preset lower power limit of 50kW, the charging pile can decrease its power consumption by a maximum of 50kW within the current control cycle. Therefore, the power adjustment range of the load device can be determined to include: an upward power adjustment range of 0 to 50kW and a downward power adjustment range of 0 to 50kW.

[0070] In S33, the power limitation range of the power generation equipment is determined based on its actual output power and the preset minimum allowable output power. The actual output power represents the power currently being output by the power generation equipment, while the preset minimum allowable output power represents the minimum output power that the power generation equipment is allowed to maintain under current operating conditions. Comparing the two allows us to determine the maximum power output that the power generation equipment can reduce within the current control cycle, which is the power limitation range of the power generation equipment. If the actual output power of the power generation equipment is already equal to or close to the preset minimum allowable output power, it indicates that the power generation equipment has essentially no room for further power limitation.

[0071] In S40, the step of generating a first parameter set through the power grid cloud control platform based on the first adjustment range and the preset grid-connected power range includes:

[0072] S41 calculates the theoretical grid-connected power based on the actual charging and discharging power in the second energy storage side data, the actual power in the second load side data, and the actual output power in the second power supply side data;

[0073] S42 corrects the theoretical grid-connected power based on the second grid-side data to obtain the corrected grid-connected power;

[0074] S43 When the corrected grid-connected power is not within the preset grid-connected power range, the adjustment amount is obtained based on the difference between the corrected grid-connected power and the limit of the preset grid-connected power range;

[0075] S44 Based on the adjustment amount and the first adjustment range, S44 allocates the adjustment amount according to the preset adjustment priority through the power grid cloud control platform to obtain the reference adjustment value of the terminal power equipment;

[0076] S45 generates the first parameter set based on the reference adjustment value.

[0077] In S41, the theoretical grid-connected power can be understood as the power that the controlled area still needs to exchange with the external power grid during the current control cycle. In one calculation method, the actual power generation capacity that the generating equipment can provide to the controlled area is first obtained by subtracting the actual power limitation of the generating equipment from its actual output power. Then, the actual power of the load equipment is added to obtain the effective power consumption of the load equipment. Simultaneously, the impact of energy storage equipment on grid-connected power is determined based on the actual charging and discharging power of the energy storage equipment. Charging the energy storage equipment is equivalent to increasing the power consumption of the controlled area, and discharging the energy storage equipment is equivalent to increasing the power supply to the controlled area. The theoretical grid-connected power is obtained according to the formula: "Effective power consumption + Energy storage charging power - Energy storage discharging power - Effective power generation." If the calculation result is positive, it indicates that the controlled area needs to purchase electricity from the external power grid; if the calculation result is negative, it indicates that the controlled area is supplying electricity to the external power grid.

[0078] Assuming the data for a certain regulated area during the current regulation cycle is as follows: the actual output power of the generating equipment is 800kW, and the actual power limitation of the generating equipment is 100kW, then the current effective generating power is: 800kW - 100kW = 700kW. The actual power of the load equipment is 900kW, and the actual power of the load equipment is 50kW. If this actual regulation power represents an increase of 50kW in load power, then the current effective power consumption is: 900kW + 50kW = 950kW. The energy storage device is currently charging, with an actual charging power of 200kW. This 200kW is equivalent to an additional increase in the power demand of the regulated area. Therefore, the theoretical grid-connected power is 950kW + 200kW - 700kW = 450kW. The calculation result is positive, indicating that the regulated area currently needs to purchase 450kW of electricity from the external grid. If other conditions remain unchanged, but the energy storage device discharges at 200kW instead of charging at 200kW, then the energy storage discharge is equivalent to increasing the local power supply capacity. In this case, the theoretical grid-connected power is: 950kW - 200kW - 700kW = 50kW. The calculation result is still positive, indicating that 50kW still needs to be purchased from the external grid, but compared to 450kW under the energy storage charging state, the purchased power is significantly reduced.

[0079] In S42, the corrected grid-connected power can be obtained as follows: calculate the difference ΔP between the theoretical grid-connected power and the grid-connected power provided by the grid-side data, then the corrected grid-connected power = ΔP × α + theoretical grid-connected power, where α is the correction coefficient. The correction coefficient α can be obtained by fitting historical theoretical grid-connected data with historical grid-side data, and is used to characterize the degree of error correction between the theoretical calculated value and the actual grid-connected power. Due to potential acquisition delays, line losses, equipment metering errors, communication synchronization errors, and some small load changes not included in the calculation during actual operation, there will usually be a certain difference between the theoretical grid-connected power and the measured grid-connected power. This reduces the bias in grid-connected power judgment, thereby improving the accuracy of subsequent adjustment calculations and control parameter generation.

[0080] In S43, when the corrected grid-connected power is not within the preset grid-connected power range, the power grid cloud control platform determines the adjustment amount of the grid-connected power based on the difference between the corrected grid-connected power and the limit of the preset grid-connected power range. If the corrected grid-connected power is less than the lower limit of the preset grid-connected power range, it indicates that there is excessive reverse power transmission in the area to be regulated. In this case, the difference between the corrected grid-connected power and the lower limit of the preset grid-connected power range is used as the adjustment amount that needs to be adjusted upwards. If the corrected grid-connected power is greater than the upper limit of the preset grid-connected power range, it indicates that there is excessive power purchase in the area to be regulated. In this case, the difference between the corrected grid-connected power and the upper limit of the preset grid-connected power range is used as the adjustment amount that needs to be adjusted downwards.

[0081] In S43, another implementation method can obtain the reference adjustment value as follows: Obtain the current grid-connected power from the second grid-side data in the second source-grid-load-storage data. If the current grid-connected power is less than the lower limit of a preset grid-connected power range, the difference between the lower limit of the preset grid-connected power range and the current grid-connected power is used as the adjustment amount. This reference adjustment value represents the target power amount that needs to be adjusted upwards. If the current grid-connected power is greater than the upper limit of the preset grid-connected power range, the difference between the current grid-connected power and the upper limit of the preset grid-connected power range is used as the adjustment amount. This reference adjustment value represents the target power amount that needs to be adjusted downwards. Then, the adjustment amount is evenly distributed to the corresponding terminal power equipment to obtain the reference adjustment value.

[0082] In S44, based on the adjustment amount and the first adjustment range, the adjustment amount is allocated according to a preset adjustment priority through the power grid cloud control platform to obtain a reference adjustment value for the terminal power equipment, including:

[0083] S441 If the corrected grid-connected power is less than the lower limit of the preset grid-connected power range, the preset adjustment priority is determined to sequentially increase the actual charging power of the second energy storage side data, the actual power of the second load side data, and decrease the actual output power of the second power supply side data. The adjustment amount is allocated to the corresponding terminal power equipment through the grid cloud control platform, and the reference adjustment value of the terminal power equipment is determined within the corresponding first adjustment range.

[0084] S442 If the corrected grid-connected power is greater than the upper limit of the preset grid-connected power range, the preset adjustment priority is determined as follows: increase the actual output power of the second power source data, increase the actual discharge power of the second energy storage data, and decrease the actual power of the second load data in sequence. The adjustment amount is allocated to the corresponding terminal power equipment through the power grid cloud control platform, and the reference adjustment value of the terminal power equipment is determined within the corresponding first adjustment range.

[0085] S443 If the adjustment amount to be allocated to the current terminal power device does not fall within the first adjustment range in the current preset adjustment priority, the unallocated adjustment amount is allocated to the terminal power device corresponding to the next priority.

[0086] In S441, if the corrected grid-connected power is less than the lower limit of the preset grid-connected power range, it indicates that the grid-connected power in the area to be regulated is too low, possibly indicating that local power generation exceeds local absorption capacity and excessive reverse power transmission to the external grid. In this case, it is necessary to increase the regional electricity demand or reduce local power generation output to bring the corrected grid-connected power back into the preset grid-connected power range. This involves sequentially increasing the actual charging power of the second energy storage side data, the actual power of the second load side data, and decreasing the actual output power of the second power source side data. It can be understood that the grid cloud control platform prioritizes allocating regulation to energy storage devices, enabling them to increase their actual charging power to absorb excess energy. If the energy storage device is still not within its first regulation range (i.e., the allocated regulation is still not within its first regulation range), the remaining regulation is allocated to the load device, enabling it to increase its actual power. If the remaining regulation for the load device is still not within the range, the remaining regulation is then allocated to the power generation device, causing it to decrease its actual output power. This allocation method balances grid-connected power control and power generation utilization.

[0087] In S442, if the corrected grid-connected power exceeds the upper limit of the preset grid-connected power range, it indicates that the grid-connected power in the area to be regulated is too high, suggesting excessive power purchase from the external grid. It is necessary to reduce the corrected grid-connected power by increasing local power supply capacity or reducing regional electricity demand. This is achieved by sequentially increasing the actual output power of the second power source data, increasing the actual discharge power of the second energy storage data, and decreasing the actual power of the second load data. It is understood that the grid cloud control platform prioritizes allocating regulation to generating equipment, increasing its actual output power and thus increasing local power generation. If the regulation of the generating equipment still falls within its first regulation range, the remaining regulation is allocated to energy storage equipment to increase its actual discharge power. If the energy storage equipment still falls within the range, the remaining regulation continues to be allocated to load equipment, reducing its actual power. Alternatively, existing power generation output and energy storage discharge capacity can be prioritized to reduce external power purchase demand, and the actual power of load equipment can be reduced when necessary, thereby mitigating the risk of excessive grid-connected power. The power grid cloud control platform allocates regulation quantities according to preset regulation priorities, making the equipment regulation sequence clearer under different grid-connected power deviations. This allocation method enables energy storage, load, and power generation equipment to work synergistically under the same grid-connected power regulation target, reducing disordered and redundant regulation among various resources.

[0088] In S443, if the first adjustment range of the terminal power equipment corresponding to the current preset adjustment priority is insufficient to cover the current adjustment amount to be allocated, i.e., the adjustment amount to be allocated does not fall within the first adjustment range, then the grid cloud control platform allocates the portion of the adjustment amount it can handle, and continues to allocate the remaining unallocated adjustment amount to the terminal power equipment corresponding to the next priority. For example, when an increase of 300kW of grid-connected power is required, but the energy storage device can currently only increase its charging power by a maximum of 200kW, the grid cloud control platform first uses 200kW as the reference adjustment value for the energy storage device, and continues to allocate the remaining 100kW to the load equipment of the next priority. This avoids allocating adjustment tasks exceeding the actual adjustable capacity of a single terminal power equipment, making the generated reference adjustment value and adjustment range more consistent with the current operating capacity of the equipment, improving the rationality of source-grid-load-storage coordinated regulation, fully utilizing the remaining adjustment capacity of different types of power resources, avoiding regulation interruptions due to insufficient adjustment capacity of a single device, and contributing to the efficiency of rational power resource scheduling.

[0089] In S45, the power grid cloud control platform generates a first parameter set based on the reference adjustment values ​​of each terminal power device. This first parameter set may include the reference adjustment values ​​corresponding to energy storage devices, load devices, and generation devices, and may also include the corresponding adjustment directions. After receiving the first parameter set, the terminal power devices can adjust their power according to the reference adjustment values ​​within the corresponding adjustment range, so that the corrected grid-connected power gradually returns to the preset grid-connected power range.

[0090] The power grid cloud control platform does not limit itself to issuing control commands to individual devices. Based on a first adjustment range, it determines the actual adjustable capacity of energy storage devices, load devices, and power generation devices within the current control cycle. Then, based on a preset grid-connected power range, it determines the degree of deviation of the corrected grid-connected power from the target grid-connected power range, thereby establishing a relationship between the amount of grid-connected power that needs to be dispatched and the amount that each terminal power device can actually dispatch. As a result, the generated first parameter set is simultaneously constrained by the grid-connected power target and the device power boundaries, avoiding situations where the adjustment amount exceeds the working capacity of the terminal power devices and improving the executability of the control parameters.

[0091] This application provides an electronic device that may include a processing module and a memory. The memory stores a computer program, which, when executed by the processor, enables the electronic device to perform the corresponding steps in the aforementioned source-grid-load-storage coordinated control method.

[0092] In this embodiment, the processor can be an integrated circuit chip with signal processing capabilities. For example, the processor can be a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0093] The memory can be, but is not limited to, random access memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, etc.

[0094] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the electronic device described above can be referred to the corresponding steps in the aforementioned method, and will not be elaborated further here.

[0095] This application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when run on a computer, causes the computer to execute the source-grid-load-storage coordinated control method as described in the above embodiments.

[0096] Computer-readable storage media may be magnetic disks, optical disks, read-only memory, random access memory, flash memory, USB flash drives, hard disks, or solid-state drives, etc., and may also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implement the methods shown in the above embodiments.

[0097] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the aforementioned source-grid-load-storage coordinated control method. The computer program product may exist in a computer-readable storage medium in forms including, but not limited to, source files, executable files, and installation package files.

[0098] Based on the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by hardware or by using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, electronic device, or network device, etc.) to execute the methods described in the various implementation scenarios of this application.

[0099] In the embodiments provided in this application, it should be understood that the disclosed methods can also be implemented in other ways. The method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or part of code, which includes one or more executable instructions for implementing a specified logical function. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0100] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for coordinated regulation of power generation, grid, load, and storage, characterized in that, The method is used in a power grid cloud control platform, and the method includes: The source-grid-load-storage data of the area to be regulated is obtained. The source-grid-load-storage data includes power source data, grid-side data, load-side data, and energy storage-side data. The power source data is used to characterize the actual output power of the power generation equipment. The grid-side data is used to characterize the real-time exchange power of the grid connection point. The load-side data is used to characterize the actual load power and the power adjustment range of the load equipment. The energy storage-side data is used to characterize the actual charging and discharging power and state of charge of the energy storage equipment. The source-grid-load-storage data is input into a preset large language model. Based on a preset keyword library, the source-grid-load-storage data is identified by keywords through the preset large language model and output according to a preset data format to obtain second source-grid-load-storage data. The second source-grid-load-storage data includes second power source side data, second grid side data, second load side data, and second energy storage side data. Based on the second source-grid-load-storage data, a first adjustment range is determined. The first adjustment range is used to characterize the power boundary of the terminal power equipment. The first adjustment range includes the charging and discharging power range of the energy storage equipment, the power adjustment range of the load equipment, and the power limiting range of the power generation equipment. The terminal power equipment includes energy storage equipment, load equipment, and power generation equipment. Based on the first adjustment range and the preset grid-connected power range, a first parameter set of the power grid cloud control platform is generated. The first parameter set is a reference adjustment value for the terminal power equipment. The reference adjustment value is obtained based on the second source-grid-load-storage data and the preset grid-connected power range. Based on the first set of parameters, the grid-connected power of the terminal power equipment is adjusted to a preset grid-connected power range through the power grid cloud control platform. The preset grid-connected power range is used to characterize the target control range of the grid-connected power by the power grid cloud control platform.

2. The method according to claim 1, characterized in that, The second source-grid-load-storage data is obtained by identifying keywords in the source-grid-load-storage data based on a preset keyword library and using the preset large language model, and outputting the data according to a preset data format, including: The semantic information of the source network load storage data is extracted using the preset large language model. The semantic information includes field names and units of measurement. The mapping relationship between the field names of the semantic information and the keywords of the preset keyword library is determined by the preset large language model. The preset keyword library is a pre-constructed mapping library that uses power generation, grid, load and storage terms as keywords. Using the preset large language model, the field names with determined mapping relationships and the corresponding units of measurement are output according to a preset data format to obtain the second source-grid-load-storage data. The preset data format includes preset field names and preset units of measurement.

3. The method according to claim 1, characterized in that, Between obtaining the second source-grid-load-storage data and determining the first adjustment range based on the second source-grid-load-storage data, the method further includes: Numerical boundary verification is performed based on the rated parameters and operating thresholds of the terminal power equipment. The numerical boundary verification is used to determine whether the actual output power of the power generation equipment, the actual charging and discharging power of the energy storage equipment, and the state of charge are within the allowable range. The second source-grid-load-storage data that fails the numerical boundary verification is identified as abnormal data; The historical data of the terminal power equipment corresponding to the abnormal data is used as the replacement data to replace the abnormal data. The historical data is the data of the second source-grid-load-storage data of the terminal power equipment when it most recently passed the numerical boundary check.

4. The method according to claim 1, characterized in that, The step of determining the first adjustment range based on the second source-grid-load-storage data includes: Based on the state of charge, preset charge limit range, maximum charge and discharge power and actual charge and discharge power of the energy storage device in the second energy storage side data, the charge and discharge power range of the energy storage device is determined. Based on the actual power and preset power range of the load equipment in the second load-side data, the power adjustment range of the load equipment is determined; Based on the actual output power and preset minimum allowable output power of the power generation equipment in the second power supply side data, the power limit range of the power generation equipment is determined. The charging and discharging power range of the energy storage device, the power adjustment range of the load device, and the power limiting range of the power generation device are defined as the first adjustment range.

5. The method according to claim 4, characterized in that, The step of generating a first parameter set through the power grid cloud control platform based on the first adjustment range and the preset grid-connected power range includes: The theoretical grid-connected power is calculated based on the actual charging and discharging power in the second energy storage side data, the actual power in the second load side data, and the actual output power in the second power supply side data. Based on the second grid-side data, the theoretical grid-connected power is corrected to obtain the corrected grid-connected power; When the corrected grid-connected power is not within the preset grid-connected power range, the adjustment amount is obtained based on the difference between the corrected grid-connected power and the limit of the preset grid-connected power range; Based on the adjustment amount and the first adjustment range, the adjustment amount is allocated according to a preset adjustment priority through the power grid cloud control platform to obtain the reference adjustment value of the terminal power equipment; The first parameter set is generated based on the reference adjustment value.

6. The method according to claim 5, characterized in that, The step of allocating the adjustment amount according to a preset adjustment priority through the power grid cloud control platform based on the adjustment amount and the first adjustment range to obtain the reference adjustment value of the terminal power equipment includes: If the corrected grid-connected power is less than the lower limit of the preset grid-connected power range, the preset adjustment priority is determined to sequentially increase the actual charging power of the second energy storage side data, the actual power of the second load side data, and decrease the actual output power of the second power supply side data. The adjustment amount is allocated to the corresponding terminal power equipment through the power grid cloud control platform, and the reference adjustment value of the terminal power equipment is determined within the corresponding first adjustment range. If the corrected grid-connected power is greater than the upper limit of the preset grid-connected power range, the preset adjustment priority is determined to sequentially increase the actual output power of the second power source data, increase the actual discharge power of the second energy storage data, and decrease the actual power of the second load data. The adjustment amount is allocated to the corresponding terminal power equipment through the power grid cloud control platform, and the reference adjustment value of the terminal power equipment is determined within the corresponding first adjustment range. If the adjustment amount to be allocated to the current terminal power device does not fall within the first adjustment range in the current preset adjustment priority, the unallocated adjustment amount will be allocated to the terminal power device corresponding to the next priority.

7. An electronic device, characterized in that, The electronic device includes a processor and a memory coupled together, the memory storing a computer program that, when executed by the processor, causes the electronic device to perform the method as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1 to 6.

9. A program product, characterized in that, It includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 6.

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