Multi-source energy storage station information and energy interaction collaborative control method and system

Abstract

The application discloses a kind of multi-source energy storage station information and energy interaction coordination control method and system, it is related to energy management and energy storage control field, including, the operating state of energy storage equipment is collected, station total power consumption power and renewable energy power generation, the data collected is preprocessed;Establish the information interaction mechanism between energy storage equipment, based on the data after preprocessing is shared between energy storage equipment and station according to information interaction mechanism;Based on the data after preprocessing is constructed energy interaction mathematical model using power balance equation, the data after preprocessing is input into energy interaction mathematical model, and the total output power of energy storage equipment group is obtained;The application collects the operating state of energy storage equipment, station total power consumption power and renewable energy power generation, constructs standardized matrix using cleaning and normalization method, guarantees data accuracy, provides high-quality data input for subsequent calculation, avoids the calculation error caused by data noise.

Description

Technical Field

[0001] This invention relates to the fields of energy management and energy storage control, and in particular to a method and system for information and energy interaction and collaborative control of multi-source energy storage stations. Background Technology

[0002] With the rapid development of renewable energy power generation, its penetration rate in the power system is constantly increasing. However, due to the significant intermittency and volatility of renewable energy, the power system faces challenges in terms of energy balance and stability. Energy storage technology, as a means to solve this problem, realizes the storage and release of energy through various forms of energy storage devices, which can improve the utilization rate of renewable energy and achieve peak shaving and valley filling. In recent years, multi-source energy storage systems have become a research hotspot. By integrating various energy storage forms with renewable energy and constructing multi-source energy storage stations, coordinated energy management can be achieved. However, existing technologies still have shortcomings in the control and optimization of multi-source energy storage systems, especially in information interaction and energy collaborative control, where a systematic solution has not yet been formed.

[0003] Existing technologies mainly employ centralized and decentralized control methods for power allocation and control of multi-source energy storage devices. However, these technologies suffer from the following shortcomings: a lack of a unified information exchange mechanism, resulting in insufficient sharing of operating status and energy information among energy storage devices, impacting overall operating efficiency; inadequate construction of energy interaction models, failing to dynamically consider changes in energy storage device status, renewable energy generation, and total power consumption of the power station, making it difficult to adapt to complex fluctuation scenarios; and the fact that most power allocation algorithms are static allocation strategies lacking real-time optimization capabilities, leading to insufficient system economy and stability. In contrast, this invention significantly improves the collaborative control capability and dynamic response efficiency of multi-source energy storage systems by constructing an information exchange mechanism and energy interaction mathematical model among energy storage devices, combined with real-time optimization algorithms. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a method for coordinated control of information and energy interaction in multi-source energy storage stations to address the problems of lack of a unified information interaction mechanism, insufficient sharing of operating status and energy information among energy storage devices, impacting overall operating efficiency, and inadequate construction of energy interaction models.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a method for coordinated control of information and energy interaction in multi-source energy storage stations, comprising,

[0008] Collect the operating status of energy storage devices, the total power consumption of the site and the power generation of renewable energy, and preprocess the collected data;

[0009] Establish an information exchange mechanism between energy storage devices, and share the pre-processed data between energy storage devices and within the site according to the information exchange mechanism;

[0010] Based on the preprocessed data, an energy interaction mathematical model is constructed using a power balance equation. The preprocessed data is then input into the energy interaction mathematical model to obtain the total output power of the energy storage device group.

[0011] Collect real-time data, input the real-time data into the energy interaction mathematical model, and obtain real-time prediction results;

[0012] Based on real-time prediction results, the power allocation value of each energy storage device is calculated through a target optimization algorithm to generate a power allocation scheme. The optimal power allocation scheme is obtained by dynamically adjusting the power allocation scheme.

[0013] The optimal power allocation scheme is sent to each energy storage device.

[0014] Secondly, this invention provides a file encryption system, including a data acquisition module, an information interaction module, an energy interaction module, a prediction module, an allocation module, and an instruction module:

[0015] The data acquisition module is used to collect the operating status of energy storage equipment, the total power consumption of the station and the power generation of renewable energy, and to perform data cleaning and normalization processing.

[0016] The information interaction module is used to construct an information interaction matrix, quantify the data interaction weights between energy storage devices, and support data broadcasting and reception.

[0017] The energy interaction module is used to construct an energy interaction mathematical model and calculate the total output power of the energy storage device group;

[0018] The prediction module is used to predict the power output demand of the energy storage device group and determine the power balance status based on real-time data and mathematical models.

[0019] The allocation module is used to calculate the power allocation value through a target optimization algorithm and generate a globally optimal power allocation scheme;

[0020] The instruction module is used to send the optimal power allocation scheme to the energy storage device, verify and execute the power allocation instruction, and provide feedback on the execution status.

[0021] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the multi-source energy storage station information and energy interaction collaborative control method as described in the first aspect of the present invention.

[0022] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the multi-source energy storage station information and energy interaction collaborative control method as described in the first aspect of the present invention.

[0023] The beneficial effects of this invention are as follows: By collecting data on the operating status of energy storage devices, the total power consumption of the power station, and the power generation of renewable energy, and constructing a standardized matrix using cleaning and normalization methods, this invention ensures data accuracy, provides high-quality data input for subsequent calculations, avoids calculation errors caused by data noise, and improves the efficiency and reliability of system analysis. Based on the matrix, an information interaction matrix is ​​constructed to achieve data sharing among energy storage devices, quantifies the influence weights between devices, forms a collaborative relationship, and enhances the coordination and overall operating efficiency of energy storage devices. Based on the power balance equation, the total output power of the energy storage device group is calculated, dynamically balancing the total power consumption of the power station and power generation fluctuations, improving system response capabilities, and ensuring the stability of power station operation. Real-time data is input into the mathematical model, and power allocation is dynamically adjusted in combination with optimization algorithms to generate a globally optimal power allocation scheme, improving resource utilization, optimizing system economy and safety, and sending optimization instructions to energy storage devices for verification and execution. Closed-loop control of the power output of energy storage devices ensures operational accuracy and avoids equipment overload or abnormal operation. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of the information and energy interaction collaborative control method for multi-source energy storage stations in Example 1.

[0026] Figure 2 This is a schematic diagram of the information and energy interaction collaborative control system for multi-source energy storage stations in Example 1. Detailed Implementation

[0027] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0028] Example 1, referring to Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method for coordinated control of information and energy interaction in multi-source energy storage stations, including the following steps:

[0029] S1 collects the operating status of energy storage devices, the total power consumption of the site, and the power generation of renewable energy, and preprocesses the collected data;

[0030] The system collects data on the operating status of energy storage devices, the total power consumption of the power station, and the amount of renewable energy generated through sensors and measuring instruments.

[0031] The data was cleaned using linear interpolation and three-standard-deviation methods, and the data units were standardized using normalization based on the cleaned data.

[0032] By repairing missing data using linear interpolation and removing outliers using the three-standard-deviation method, the accuracy of the data was effectively improved, avoiding model calculation deviations caused by data noise or sensor anomalies. The data cleaning process eliminated unreliable factors caused by data acquisition errors in the energy storage system, providing high-quality data for subsequent calculations.

[0033] The normalization method unifies the dimensional differences between multi-source data of energy storage devices, avoids the interference of different data dimensions on model calculation, and the data normalization process makes the weight of each parameter balanced, which is convenient for subsequent energy interaction mathematical model calculation.

[0034] The normalized data are integrated into a standardized matrix X, expressed as:

[0035] ;

[0036] in, Indicates the remaining power of the energy storage device. and These represent the upper and lower power limits of the energy storage device, respectively. This indicates the total power consumption of the station. and This indicates the amount of renewable energy generated (including photovoltaic power and wind power).

[0037] Normalized matrix generated by data preprocessing It provides high-quality input data for the energy interaction mathematical model, significantly reducing the model's calculation error. The improved data quality enhances the model's stability and avoids model non-convergence or distorted calculation results caused by abnormal data or inconsistent dimensions.

[0038] S2 establishes an information exchange mechanism between energy storage devices, and shares the pre-processed data between energy storage devices and within the site according to the information exchange mechanism.

[0039] Based on the normalized matrix Construct an information interaction matrix among energy storage devices Used for quantitative energy storage devices For energy storage devices The information interaction weight is expressed as:

[0040] = ;

[0041] in, Indicates the first The energy storage device for the first Information interaction weight of each energy storage device Indicates the first The remaining power of each energy storage device Indicates the first The remaining power of each energy storage device and They represent the first The minimum discharge power of the energy storage device and the first The maximum discharge power of each energy storage device and They represent the first The upper and lower limits of the power of each energy storage device; This represents the adjustment coefficient. Indicates a constant. , and This represents the index variable for energy storage devices. Indicates the total number of energy storage devices;

[0042] Each energy storage device is based on the information interaction matrix The row vector weight distribution will be used to standardize the matrix. Distribute energy to other energy storage devices via broadcast;

[0043] Each energy storage device is based on the matrix The column vector weight distribution receives the standardized matrix from other energy storage devices. ;

[0044] The station control center will use the information exchange matrix Distributed to all energy storage devices, each energy storage device broadcasts and receives from a standardized matrix. During the process, collaborative control data will be uploaded to the station control center;

[0045] Information interaction matrix The collaborative relationships between energy storage devices are clearly quantified, enabling the devices to dynamically adjust their collaboration strategies based on their respective states. Each energy storage device achieves this through sharing and receiving matrices. The information can determine its own operating mode from a global perspective, thereby optimizing global power allocation;

[0046] In traditional methods, energy storage devices often operate in isolation, lacking coordinated control, resulting in low resource utilization. Information interaction mechanisms, by quantifying the collaborative relationships between devices, effectively improve the collaboration efficiency between energy storage devices, solve the problem of information asymmetry between devices in existing energy storage systems, and avoid global optimization failures caused by isolated data from individual devices.

[0047] S3 uses the power balance equation to construct an energy interaction mathematical model based on the preprocessed data. The preprocessed data is then input into the energy interaction mathematical model to obtain the total output power of the energy storage device group.

[0048] Based on the preprocessed normalized matrix and information interaction matrix Based on the power balance equation, an energy interaction mathematical model is constructed, expressed as follows:

[0049] ;

[0050] in, Indicates the energy storage device group at any time Total output power Indicates time Total power consumption of the station Indicates time Total renewable energy power generation capacity Represents the first element in the information interaction matrix. The energy storage device for the first The influence weight of each energy storage device Indicates the first The output power of an energy storage device;

[0051] Traditional energy storage systems often use static rules for power allocation, which are difficult to adapt to the dynamic total power consumption of the site. The mathematical model combines the coordination relationship between devices with the site demand to form a globally optimized power allocation strategy. This solves the problem that the power allocation model in the existing technology lacks consideration of the coordination of energy storage devices, improves the overall response and balance capabilities of the system, solves the dynamic power balance problem in complex scenarios, and avoids energy waste or insufficient power supply.

[0052] S4 collects real-time data and inputs the real-time data into the energy interaction mathematical model to obtain real-time prediction results;

[0053] The collected real-time data includes the real-time operating status of energy storage devices, the real-time total power consumption of the power station, and the real-time renewable energy generation.

[0054] The data was cleaned using linear interpolation and three-standard-deviation methods, and the data units were standardized using normalization based on the cleaned data.

[0055] The cleaned and normalized data are integrated into a standardized matrix. Based on standardized matrix Construct an information interaction matrix among energy storage devices ;

[0056] Through the preprocessed standardized matrix and information interaction matrix The data is input into the energy interaction mathematical model to obtain the real-time predicted total output power of the energy storage device group;

[0057] when When ≥0, the output power of the energy storage equipment group meets the total power consumption of the station;

[0058] when When the value is less than 0, the energy storage device needs to be charged to absorb excess renewable energy power generation.

[0059] Based on real-time prediction results, when When ≥0, the energy storage device group can provide the output power to meet the total power demand of the site. When the load is less than 0, the energy storage equipment group absorbs excess renewable energy power generation for charging, realizing dynamic matching between energy storage equipment and the total load demand of the station and renewable energy power generation, thus improving energy utilization efficiency.

[0060] By using real-time prediction results and power balance judgment, energy storage devices can accurately perform charging or discharging operations, avoiding overcharging or over-discharging. The operating status of energy storage devices is dynamically optimized through prediction and adjustment, reducing unnecessary losses during device operation and extending the service life of energy storage devices.

[0061] Based on real-time prediction results, S5 calculates the power allocation value of each energy storage device through a target optimization algorithm, generates a power allocation scheme, and dynamically adjusts the power allocation scheme to obtain the optimal power allocation scheme.

[0062] Based on real-time prediction results, the power allocation value for each energy storage device is calculated using a target optimization algorithm, expressed as follows:

[0063] ;

[0064] in, Indicates the first An energy storage device at any time The power allocation value, Indicates the first An energy storage device at any time The current remaining battery power, Indicates the first The rated capacity of each energy storage device Represented as the time of the station Total power consumption , and Indicates the adjustment coefficient;

[0065] Based on the calculated power allocation value for each energy storage device, a power allocation scheme for the energy storage device group is obtained, expressed as:

[0066] ;

[0067] in, Indicates at time The power allocation scheme of the energy storage device group consists of the power allocation value of each energy storage device;

[0068] According to the power allocation scheme Dynamically adjust the power output of energy storage devices;

[0069] when > ,Will Restricted to ,in For the first The maximum discharge power of each energy storage device;

[0070] when < ,Will Restricted to ,in For the first Minimum discharge power of each energy storage device;

[0071] When the remaining power of the energy storage device exceeds the safe range ( ≤ ≤ ), prioritize adjusting the power allocation values ​​of other energy storage devices;

[0072] The optimal power allocation scheme is obtained by dynamically adjusting the power allocation scheme, and its expression is:

[0073] ;

[0074] in, This represents the globally optimal power allocation scheme, where the energy storage device group is at any given time. The dynamically adjusted optimal power output vector;

[0075] Dynamic power allocation ensures that the system always operates in the optimal state based on the real-time changes in equipment status and total power consumption of the station. Traditional power allocation methods mostly use fixed allocation ratios, which cannot adapt to real-time changing needs.

[0076] By combining real-time prediction results and target optimization algorithms, the power allocation value of energy storage devices is dynamically adjusted. The optimal power allocation scheme is dynamically generated through optimization algorithms to maximize the utilization of energy storage resources and reduce operating costs.

[0077] S6 sends the optimal power allocation scheme to each energy storage device;

[0078] Using the Modbus TCP communication protocol, the site control center will translate the optimal power allocation scheme into power allocation commands;

[0079] A power allocation command is generated individually for each energy storage device and sent to the corresponding energy storage device via Ethernet;

[0080] After receiving the power allocation command, the energy storage device verifies whether the power allocation value is within the device's allowable range;

[0081] Extract the power allocation value from the power allocation command and obtain the allowable power range of the energy storage device. ≤ ≤ ;

[0082] when ≤ ≤ If the power allocation value is within the allowable power range of the energy storage device, the energy storage device will execute the command normally.

[0083] when or If the power allocation value exceeds the power range allowed by the energy storage device, the energy storage device will mark it as abnormal and refuse to execute the command.

[0084] Through Modbus TCP communication protocol and Ethernet transmission, the station control center can efficiently convert the optimal power allocation scheme into specific power allocation instructions and accurately send them to the corresponding energy storage devices. Each energy storage device receives a customized power allocation instruction individually, ensuring the accurate execution of the power allocation scheme.

[0085] After receiving a power allocation command, the energy storage device will automatically check whether the power allocation value in the command is within the device's allowed power range. If the power allocation value exceeds the allowed range or is higher, the energy storage device will mark it as abnormal and refuse to execute the command to avoid overload or damage to the device due to operation outside the range.

[0086] By employing command verification and device range verification mechanisms, it is ensured that energy storage devices only receive and execute legitimate power allocation commands, thereby significantly improving the accuracy of power allocation scheme execution and optimizing the overall performance of the energy storage system.

[0087] This embodiment also provides a multi-source energy storage station information and energy interaction collaborative control system, including a data acquisition module, an information interaction module, an energy interaction module, a prediction module, an allocation module, and an instruction module.

[0088] The data acquisition module is used to collect data on the operating status of energy storage equipment, the total power consumption of the station, and the power generation of renewable energy, and to perform data cleaning and normalization.

[0089] The information interaction module is used to construct an information interaction matrix, quantify the data interaction weights between energy storage devices, and support data broadcasting and reception.

[0090] The energy interaction module is used to construct a mathematical model of energy interaction and calculate the total output power of the energy storage device group;

[0091] The prediction module is used to predict the power output demand of the energy storage device group and determine the power balance status based on real-time data and mathematical models.

[0092] The allocation module is used to calculate the power allocation value through a target optimization algorithm and generate the globally optimal power allocation scheme.

[0093] The instruction module is used to send the optimal power allocation scheme to the energy storage device, verify and execute the power allocation instruction, and provide feedback on the execution status.

[0094] The modules work together to enable information sharing and energy interaction between energy storage devices and within the site, comprehensively improving the collaborative optimization capabilities of the energy storage system.

[0095] The system dynamically adjusts the charging and discharging modes of energy storage devices through the cooperation of the information interaction module and the distribution module, thereby achieving the globally optimal power distribution scheme.

[0096] This embodiment also provides a computer device applicable to the information and energy interaction collaborative control method for multi-source energy storage stations, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the information and energy interaction collaborative control method for multi-source energy storage stations as proposed in the above embodiment.

[0097] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0098] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the method for information and energy interaction and coordinated control of multi-source energy storage stations as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0099] In summary, this invention achieves the following: First, it collects data on the operating status of energy storage devices, the total power consumption of the power station, and the power generation of renewable energy. Second, it constructs a standardized matrix using cleaning and normalization methods to ensure data accuracy, providing high-quality data input for subsequent calculations and avoiding calculation errors caused by data noise. This improves the efficiency and reliability of system analysis. Third, it constructs an information interaction matrix based on the matrix to achieve data sharing among energy storage devices, quantifies the influence weights between devices, forms a collaborative relationship, and enhances the coordination and overall operating efficiency of energy storage devices. Fourth, it calculates the total output power of the energy storage device group based on the power balance equation, dynamically balancing the total power consumption of the power station with power generation fluctuations, improving system responsiveness, and ensuring the stability of power station operation. Fifth, it inputs real-time data into a mathematical model, dynamically adjusts power allocation using optimization algorithms, generates a globally optimal power allocation scheme, improves resource utilization, and optimizes system economy and safety. Sixth, it sends optimization commands to the energy storage devices and verifies their execution, controlling the power output of the energy storage devices in a closed loop to ensure operational accuracy and avoid device overload or abnormal operation.

[0100] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for information and energy interaction and collaborative control of multi-source energy storage stations, characterized in that, include: Collect the operating status of energy storage devices, the total power consumption of the site, and the power generation of renewable energy, and preprocess the collected data; Establish an information exchange mechanism between energy storage devices and within the site, and use the information exchange mechanism to share pre-processed data between energy storage devices and within the site; Based on the preprocessed data, an energy interaction mathematical model is constructed using a power balance equation. The preprocessed data is then input into the energy interaction mathematical model to obtain the total output power of the energy storage device group. Collect real-time data, input the real-time data into the energy interaction mathematical model, and obtain real-time prediction results. The specific steps are as follows: The system collects real-time operating status of energy storage devices, real-time total power consumption of the power station, and real-time renewable energy generation through sensors and measuring instruments. The data were cleaned using linear interpolation and three-standard-deviation methods, and the data units were standardized using normalization based on the cleaned data. The normalized data is integrated into a standardized matrix X, and based on the standardized matrix X, an information interaction matrix M between energy storage devices is constructed. By inputting the preprocessed standardized matrix X and information interaction matrix M into the energy interaction mathematical model, the total output power of the energy storage device group can be predicted in real time. When P(t)≥0, the output power of the energy storage equipment group meets the total power consumption of the station; When P(t) < 0, the energy storage device needs to be charged to absorb excess renewable energy power generation. The normalized data are integrated into a standardized matrix X, expressed as: ； in, Indicates the remaining power of the energy storage device. and These represent the upper and lower power limits of the energy storage device, respectively. This indicates the total power consumption of the station. and Indicates the amount of electricity generated from renewable energy sources; Based on the normalized matrix Construct an information interaction matrix among energy storage devices Used for quantitative energy storage devices For energy storage devices The information interaction weight is expressed as: = ； in, Indicates the first The energy storage device for the first Information interaction weight of each energy storage device Indicates the first The remaining power of each energy storage device Indicates the first The remaining power of each energy storage device and They represent the first The minimum discharge power of the energy storage device and the first The maximum discharge power of each energy storage device and They represent the first The upper and lower limits of the power of each energy storage device; This represents the adjustment coefficient. Indicates a constant. , and This represents the index variable for energy storage devices. Indicates the total number of energy storage devices; Based on real-time prediction results, the power allocation value of each energy storage device is calculated through a target optimization algorithm to generate a power allocation scheme. The power allocation scheme is then dynamically adjusted to obtain the optimal power allocation scheme. The optimal power allocation scheme is sent to each energy storage device.

2. The method for information and energy interaction and coordinated control of multi-source energy storage stations as described in claim 1, characterized in that: The data collection process includes the operating status of the energy storage equipment, the total power consumption of the power station, and the renewable energy generation. The collected data is preprocessed, specifically through the following steps: The system collects data on the operating status of energy storage devices, total power consumption of the site, and renewable energy generation through sensors and measuring instruments. The collected data were cleaned using linear interpolation and three-standard-deviation methods, and the data units were unified using normalization methods based on the cleaned data. The normalized data are integrated into a standardized matrix X.

3. The method for information and energy interaction and coordinated control of multi-source energy storage stations as described in claim 2, characterized in that: The establishment of an information exchange mechanism between energy storage devices involves sharing pre-processed data between energy storage devices and within the site according to the information exchange mechanism. The specific steps are as follows: Based on the normalized matrix Construct an information interaction matrix among energy storage devices Each energy storage device is based on the information exchange matrix. The row vector weight distribution will be used to standardize the matrix. Distribute energy to other energy storage devices via broadcast; Each energy storage device is based on the information interaction matrix The column vector weight distribution receives the standardized matrix from other energy storage devices. ; The station control center will use the information exchange matrix Distributed to all energy storage devices, each energy storage device broadcasts and receives from a standardized matrix. During the process, collaborative control data is uploaded to the station control center.

4. The multi-source energy storage station information and energy interaction collaborative control method as described in claim 3, characterized in that: The energy interaction mathematical model is constructed based on the preprocessed data using a power balance equation. The preprocessed data is then input into the energy interaction mathematical model to obtain the total output power of the energy storage device group. The specific steps are as follows: Based on the preprocessed normalized matrix and information interaction matrix A mathematical model of energy interaction is constructed using the power balance equation.

5. The multi-source energy storage station information and energy interaction collaborative control method as described in claim 4, characterized in that: The process involves calculating the power allocation value for each energy storage device based on real-time prediction results using a target optimization algorithm, generating a power allocation scheme, and dynamically adjusting the power allocation scheme to obtain the optimal power allocation scheme. The specific steps are as follows: Based on real-time prediction results, the power allocation value of each energy storage device is calculated using a target optimization algorithm; Based on the calculated power allocation value of each energy storage device, a power allocation scheme for the energy storage device group is obtained; According to the power allocation scheme Dynamically adjust the power output of energy storage devices; when > ,Will Restricted to ,in For the first The maximum discharge power of each energy storage device; when < ,Will Restricted to ,in For the first Minimum discharge power of each energy storage device; When the remaining power of an energy storage device exceeds the safe range, the power allocation value of other energy storage devices should be adjusted first. The optimal power allocation scheme is obtained by dynamically adjusting the power allocation scheme.

6. The method for information and energy interaction and coordinated control of multi-source energy storage stations as described in claim 5, characterized in that: The specific steps for sending the optimal power allocation scheme to each energy storage device are as follows: Using the Modbus TCP communication protocol, the site control center translates the optimal power allocation scheme into power allocation commands; A power allocation command is generated individually for each energy storage device and sent to the corresponding energy storage device via Ethernet; After receiving the power allocation command, the energy storage device verifies whether the power allocation value is within the device's allowable range; Extract the power allocation value from the power allocation command and obtain the allowable power range of the energy storage device. ≤ ≤ ; when ≤ ≤ If the power allocation value is within the allowable power range of the energy storage device, the energy storage device will execute the command normally. when or If the power allocation value exceeds the power range allowed by the energy storage device, the energy storage device will mark it as abnormal and refuse to execute the command.

7. A multi-source energy storage station information and energy interaction collaborative control system, based on the multi-source energy storage station information and energy interaction collaborative control method according to any one of claims 1 to 6, characterized in that: It includes a data acquisition module, an information interaction module, an energy interaction module, a prediction module, an allocation module, and an instruction module. The data acquisition module is used to collect the operating status of energy storage equipment, the total power consumption of the station and the power generation of renewable energy, and to perform data cleaning and normalization processing. The information interaction module is used to construct an information interaction matrix, quantify the data interaction weights between energy storage devices, and support data broadcasting and reception. The energy interaction module is used to construct an energy interaction mathematical model and calculate the total output power of the energy storage device group; The prediction module is used to predict the power output demand of the energy storage device group and determine the power balance status based on real-time data and mathematical models. The allocation module is used to calculate the power allocation value through a target optimization algorithm and generate a globally optimal power allocation scheme; The instruction module is used to send the optimal power allocation scheme to the energy storage device, verify and execute the power allocation instruction, and provide feedback on the execution status.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the multi-source energy storage station information and energy interaction collaborative control method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the multi-source energy storage station information and energy interaction collaborative control method as described in any one of claims 1 to 6.

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