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

Abstract

The invention discloses a multi-source energy storage station information and energy interaction cooperative control method and system, and relates to the field of energy management and energy storage control, and the method comprises the steps: collecting the operation state of energy storage equipment, the total electric power of a station, and the power generation of renewable energy sources, and carrying out the preprocessing of the collected data; establishing an information interaction mechanism between the energy storage devices, and sharing between the energy storage devices and in the station according to the information interaction mechanism based on the preprocessed data; constructing an energy interaction mathematical model by adopting a power balance equation based on the preprocessed data, and inputting the preprocessed data into the energy interaction mathematical model to obtain the total output power of the energy storage equipment group; according to the method, the operation state of the energy storage equipment, the total electric power of the station and the renewable energy generating capacity are collected, and the standardized matrix is constructed by using a cleaning and normalization method, so that the data accuracy is ensured, high-quality data input is provided for subsequent calculation, and calculation errors caused by data noise are avoided.

Description

Technical Field

[0001] The present invention relates to the field of energy management and energy storage control, and in particular to a method and system for interactive collaborative control of multi-source energy storage station information and energy. Background Art

[0002] With the rapid development of renewable energy power generation, its penetration rate in the power system continues to increase. However, due to the significant intermittency and volatility of renewable energy, the power system faces challenges in energy balance and stability. Energy storage technology, as a means to solve this problem, can achieve energy storage and release through various forms of energy storage equipment, 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 forms of energy storage and renewable energy and building multi-source energy storage sites, 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 coordinated control, and no systematic solution has yet been formed.

[0003] The existing technology mainly adopts centralized and decentralized control methods to distribute and control power for multi-source energy storage devices, but has the following shortcomings: lack of a unified information interaction mechanism, the operating status and energy information between energy storage devices cannot be fully shared, affecting the overall operating efficiency, insufficient construction of the energy interaction model, failure to dynamically consider changes in the status of energy storage devices, renewable energy generation and total power consumption of the site, and difficulty in adapting to complex fluctuating scenarios. The power allocation algorithm is mostly a static allocation strategy and lacks real-time optimization capabilities, resulting in insufficient economy and stability of the system. In contrast, the present invention significantly improves the collaborative control capability and dynamic response efficiency of the multi-source energy storage system by constructing an information interaction mechanism and an energy interaction mathematical model between energy storage devices, and combining it with a real-time optimization algorithm. Summary of the invention

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

[0005] Therefore, the present invention provides a multi-source energy storage station information and energy interactive collaborative control method to solve the problem of lack of a unified information interaction mechanism, inability to fully share the operating status and energy information between energy storage devices, affecting the overall operating efficiency, and insufficient construction of an energy interaction model.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for interactive coordinated control of multi-source energy storage station information and energy, which comprises:

[0008] Collect the operating status of energy storage equipment, total power consumption of the site and renewable energy generation, and pre-process the collected data;

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

[0010] Based on the preprocessed data, a power balance equation is used to construct an energy interaction mathematical model, and the preprocessed data is input into the energy interaction mathematical model to obtain the total output power of the energy storage device group;

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

[0012] Based on the real-time prediction results, the power allocation value of each energy storage device is calculated through the target optimization algorithm, and a power allocation plan is generated. The optimal power allocation plan is obtained by dynamic adjustment according to the power allocation plan;

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

[0014] In a second aspect, the present invention provides a file encryption system, including a collection module, an information interaction module, an energy interaction module, a prediction module, a distribution module, and an instruction module:

[0015] The acquisition module is used to collect the operating status of the energy storage equipment, the total power consumption of the station and the power generation of renewable energy, and 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 state based on real-time data and mathematical models;

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

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

[0021] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the multi-source energy storage station information and energy interactive collaborative control method as described in the first aspect of the present invention is implemented.

[0022] In a fourth aspect, 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, any step of the multi-source energy storage station information and energy interactive collaborative control method as described in the first aspect of the present invention is implemented.

[0023] The beneficial effects of the present invention are as follows: the present invention collects the operating status of energy storage equipment, the total power consumption of the station and the power generation of renewable energy, and uses cleaning and normalization methods to construct a standardized matrix to ensure data accuracy, provide high-quality data input for subsequent calculations, avoid calculation errors caused by data noise, and improve system analysis efficiency and reliability. The information interaction matrix is ​​constructed based on the matrix to realize data sharing between energy storage devices, quantify the influence weights between devices, form a collaborative relationship, enhance the coordination and overall operation efficiency of energy storage devices, calculate the total output power of the energy storage device group based on the power balance equation, dynamically balance the total power consumption of the station and the power generation fluctuation, improve the system response capability, ensure the operation stability of the station, input real-time data into the mathematical model, dynamically adjust the power distribution in combination with the optimization algorithm, generate a global optimal power distribution plan, improve resource utilization, optimize the economy and safety of the system, send the optimization command to the energy storage device and verify the execution, close the loop to control the power output of the energy storage device, ensure the operation accuracy, and avoid equipment overload or abnormal operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0025] Figure 1 This is a flow chart of the multi-source energy storage station information and energy interactive collaborative control method in Example 1.

[0026] Figure 2 Schematic diagram of the multi-source energy storage station information and energy interactive collaborative control system in Example 1. DETAILED DESCRIPTION

[0027] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0028] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a method for interactive collaborative control of multi-source energy storage station information and energy, comprising the following steps:

[0029] S1 collects the operating status of energy storage equipment, total power consumption of the site and renewable energy generation, and pre-processes the collected data;

[0030] The operating status of energy storage equipment, total power consumption of the station and renewable energy generation are collected through sensors and measuring instruments;

[0031] The data were cleaned by linear interpolation and triple standard deviation method, and the data dimensions were unified by normalization method based on the cleaned data;

[0032] The missing data was repaired by linear interpolation, and the abnormal data was eliminated by triple standard deviation method, which effectively improved the accuracy of the data and avoided the model calculation deviation caused by data noise or sensor abnormality. The data cleaning process eliminated the unreliable factors caused by data collection errors in the energy storage system and provided high-quality data for subsequent calculations.

[0033] The normalization method is used to unify the dimensional differences between multi-source data of energy storage equipment, avoiding the interference of different data dimensions on model calculation. After data normalization, the weights of various parameters are balanced, which is convenient for subsequent calculation of energy interaction mathematical models.

[0034] Integrate the normalized data into a standardized matrix X, expressed as:

[0035] X=[S,P min ,P max ,N,O1,O2];

[0036] Among them, S represents the remaining power of the energy storage device, P min and P max They represent the upper and lower power limits of the energy storage equipment, respectively; N represents the total power consumption of the site; O1 and O2 represent the power generation of renewable energy (including photovoltaic power and wind power);

[0037] The standardized matrix X generated by data preprocessing provides high-quality input data for the energy interaction mathematical model, significantly reducing the model calculation error. The improvement of data quality enhances the stability of the model and avoids model non-convergence or distortion of calculation results caused by abnormal data or inconsistent dimensions.

[0038] S2 establishes an information interaction mechanism between energy storage devices, and shares the pre-processed data between energy storage devices and within the station according to the information interaction mechanism;

[0039] Based on the standardized matrix X, the information interaction matrix M between energy storage devices is constructed to quantify the information interaction weight of energy storage device j to energy storage device i. The expression is:

[0040]

[0041] Among them, M ij represents the information interaction weight of the j-th energy storage device to the i-th energy storage device, S j represents the remaining power of the jth energy storage device, S k represents the remaining power of the kth energy storage device, P min,j and P max,j They represent the minimum discharge power of the j-th energy storage device and the maximum discharge power of the i-th energy storage device, respectively. min,k and P max,k They represent the upper and lower limits of the power of the kth energy storage device respectively; α, β, γ represent adjustment coefficients, ∈ represents a constant, i, k and j represent index variables of the energy storage device, and n represents the total number of energy storage devices;

[0042] Each energy storage device distributes the standardized matrix X to other energy storage devices through broadcasting according to the row vector weight distribution of the information interaction matrix M;

[0043] Each energy storage device receives the standardized matrix X of other energy storage devices according to the column vector weight distribution of the matrix M;

[0044] The station control center distributes the information interaction matrix M to all energy storage devices. During the process of broadcasting and receiving the standardized matrix X, each energy storage device uploads the collaborative control data to the station control center.

[0045] The information interaction matrix M clearly quantifies the collaborative relationship between energy storage devices, enabling the energy storage devices to dynamically adjust their collaborative strategies according to their respective states. Each energy storage device can determine its own operating mode from a global perspective by sharing and receiving information from the matrix M, thereby optimizing global power allocation.

[0046] In traditional methods, energy storage devices are mostly operated in isolation and lack collaborative control, resulting in low resource utilization. The information interaction mechanism effectively improves the collaborative efficiency between energy storage devices by quantifying the collaborative relationship between devices, solving the problem of information asymmetry between devices in existing energy storage systems and avoiding global optimization failures caused by isolated individual device data.

[0047] S3 constructs an energy interaction mathematical model based on the preprocessed data using a power balance equation, inputs the preprocessed data into the energy interaction mathematical model, and obtains the total output power of the energy storage device group;

[0048] Based on the preprocessed standardized matrix X and the information interaction matrix M, the energy interaction mathematical model is constructed through the power balance equation, and the expression is:

[0049]

[0050] Where P(t) represents the total output power of the energy storage device group at time t, and N(t) represents the total power consumption of the station at time t. 1 (t)+O 2 (t) represents the total power generated by renewable energy at time t, M ij represents the influence weight of the j-th energy storage device on the i-th energy storage device in the information interaction matrix, P j (t) represents the output power of the jth energy storage device;

[0051] The power allocation of traditional energy storage systems mostly adopts static rules, which are difficult to adapt to the total power consumption of dynamic sites. The mathematical model combines the collaborative relationship between devices with the site needs to form a globally optimized power allocation strategy, which solves the problem that the power allocation model in the existing technology lacks collaborative consideration of energy storage devices, improves the overall responsiveness 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 the energy storage equipment, the real-time total power consumption of the site and the real-time renewable energy power generation;

[0054] The data were cleaned by linear interpolation and triple standard deviation method, and the data dimensions were unified by normalization method based on the cleaned data;

[0055] The cleaned and normalized data are integrated into a standardized matrix X, and based on the standardized matrix X, an information interaction matrix M between energy storage devices is constructed;

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

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

[0058] When P(t)<0, the energy storage device needs to be charged to absorb excess renewable energy power;

[0059] According to the real-time prediction results, when P(t)≥0, the energy storage device group can provide output power that meets the total power demand of the site. When P(t)<0, the energy storage device group absorbs excess renewable energy power for charging, achieving dynamic matching between the energy storage device and the total load demand of the site and renewable energy power generation, thereby improving energy utilization efficiency.

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

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

[0062] Based on the real-time prediction results, the power allocation value of each energy storage device is calculated through the target optimization algorithm, and the expression is:

[0063]

[0064] Among them, A j (t) represents the power allocation value of the jth energy storage device at time t, S j (t) represents the current remaining power of the jth energy storage device at time t, C j represents the rated capacity of the jth energy storage device, N(t) represents the total power consumption of the station at time t, θ, ψ and ω represent the regulation coefficients;

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

[0066]

[0067] in, represents the power allocation scheme of the energy storage device group at time t, which is composed 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 A j (t)>P max,j , A j (t) is limited to P max,j , where P max,j is the maximum discharge power of the jth energy storage device;

[0070] When Aj (t)<P min,j , A j (t) is limited to P min,j , where P min,j is the minimum discharge power of the jth energy storage device;

[0071] When the remaining power of the energy storage device exceeds the safe range (S min,j ≤S j (t)≤S max,j ), give priority to adjusting the power allocation value of other energy storage devices;

[0072] The optimal power allocation scheme is obtained by dynamic adjustment according to the power allocation scheme, and the expression is:

[0073]

[0074] in, represents the global optimal power allocation scheme, the optimal power output vector of the energy storage device group after dynamic adjustment at time t;

[0075] Dynamic power allocation ensures that the system always operates in the optimal state according to the real-time changes in equipment status and total power consumption of the site. Traditional power allocation methods mostly use fixed allocation ratios and cannot adapt to real-time changes.

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

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

[0078] Using Modbus TCP communication protocol, the station control center will convert the best power allocation plan into power allocation instructions;

[0079] Generate a power allocation instruction for each energy storage device separately and send it to the corresponding energy storage device via Ethernet;

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

[0081] Extract the power allocation value in the power allocation instruction and obtain the power range P allowed by the energy storage device min,j ≤A j * (t)≤P max,j ;

[0082] When P min,j ≤A j * (t)≤Pmax,j , the power allocation value is within the power range allowed by the energy storage device, and the energy storage device executes the instruction 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 the abnormality and refuse to execute the instruction;

[0084] Through Modbus TCP communication protocol and Ethernet transmission, the station control center can efficiently convert the optimal power allocation plan 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 to ensure the accurate execution of the power allocation plan.

[0085] After receiving the power allocation instruction, the energy storage device will automatically check whether the power allocation value in the instruction is within the power range allowed by the device. If the power allocation value exceeds the allowable range or is higher, the energy storage device will mark it as abnormal and refuse to execute the instruction to avoid overload or damage to the device due to out-of-range operation;

[0086] Through the command verification and device range verification mechanism, it is ensured that the energy storage device only receives and executes legal power allocation instructions, and the execution accuracy of the power allocation plan is greatly improved, thereby optimizing the overall efficiency of the energy storage system.

[0087] This embodiment also provides a multi-source energy storage station information and energy interactive collaborative control system, including a collection module, an information interaction module, an energy interaction module, a prediction module, a distribution module, and an instruction module:

[0088] The 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 perform data cleaning and normalization processing;

[0089] Information interaction module, used to construct information interaction matrix, quantify data interaction weights between energy storage devices, and support data broadcasting and reception;

[0090] Energy interaction module, used to build energy interaction mathematical model and calculate the total output power of 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 state based on real-time data and mathematical models;

[0092] An allocation module is used to calculate the power allocation value through a target optimization algorithm and generate a global optimal power allocation solution;

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

[0094] The synergy of each module can realize information sharing and energy interaction between energy storage devices and within the station, comprehensively improving the collaborative optimization capability of the energy storage system;

[0095] The system dynamically adjusts the charging and discharging modes of energy storage devices through the cooperation of information interaction modules and allocation modules to achieve the global optimal power allocation solution.

[0096] This embodiment also provides a computer device, which is applicable to the case of a multi-source energy storage station information and energy interactive collaborative control method, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the multi-source energy storage station information and energy interactive collaborative control method proposed in the above embodiment.

[0097] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0098] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by a processor, the method for realizing the information and energy interactive coordinated control of a multi-source energy storage station as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (Static Random Access Memory, referred to as SRAM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), an erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), a programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), a read-only memory (Read-Only Memory, referred to as ROM), a magnetic memory, a flash memory, a disk or an optical disk.

[0099] In summary, the present invention collects the operating status of energy storage equipment, the total power consumption of the station and the power generation of renewable energy, uses cleaning and normalization methods to construct a standardized matrix to ensure data accuracy, provides high-quality data input for subsequent calculations, avoids calculation errors caused by data noise, and improves system analysis efficiency and reliability; constructs an information interaction matrix based on the matrix to realize data sharing between energy storage devices, quantifies the influence weights between devices, forms a synergistic relationship, enhances the coordination and overall operation efficiency of energy storage devices, calculates the total output power of the energy storage device group based on the power balance equation, dynamically balances the total power consumption of the station and the power generation fluctuation, improves the system response capability, ensures the operation stability of the station, inputs real-time data into the mathematical model, dynamically adjusts the power distribution in combination with the optimization algorithm, generates a global optimal power distribution plan, improves resource utilization, optimizes the economy and safety of the system, sends the optimization command to the energy storage device and verifies the execution, controls the power output of the energy storage device in a closed loop, ensures the operation accuracy, and avoids equipment 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 rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for interactive and coordinated control of multi-source energy storage station information and energy, characterized in that: include: Collect the operating status of energy storage equipment, total power consumption of the site and renewable energy generation, and pre-process the collected data; Establish an information interaction mechanism between energy storage devices and within the station, and use the information interaction mechanism to share pre-processed data between energy storage devices and within the station; Based on the preprocessed data, a power balance equation is used to construct an energy interaction mathematical model, and the preprocessed data is input into the energy interaction mathematical model to obtain the total output power of the energy storage device group; Collect real-time data and input it into the energy interaction mathematical model to obtain real-time prediction results; Based on the real-time prediction results, the power allocation value of each energy storage device is calculated through the target optimization algorithm, a power allocation plan is generated, and the power allocation plan is dynamically adjusted to obtain the optimal power allocation plan; The optimal power allocation plan is sent to each energy storage device.

2. The method for interactive coordinated control of multi-source energy storage station information and energy according to claim 1, characterized in that: The operation status of the energy storage device, the total power consumption of the station and the power generation of renewable energy are collected, and the collected data are pre-processed. The specific steps are as follows: Collect the operating status of energy storage equipment, total power consumption of the site and renewable energy generation through sensors and measuring instruments; The collected data were cleaned by linear interpolation and triple standard deviation method, and the data dimensions were unified by normalization method based on the cleaned data; Integrate the normalized data into a standardized matrix X.

3. The method for interactive coordinated control of multi-source energy storage station information and energy according to claim 2, characterized in that: The information interaction mechanism between energy storage devices is established, and the pre-processed data is shared between energy storage devices and within the station according to the information interaction mechanism. The specific steps are: Based on the standardized matrix X, an information interaction matrix M between energy storage devices is constructed; each energy storage device distributes the standardized matrix X to other energy storage devices through broadcasting according to the row vector weight distribution of the information interaction matrix M; Each energy storage device receives the standardized matrix X of other energy storage devices according to the column vector weight distribution of the information interaction matrix M; The station control center distributes the information interaction matrix M to all energy storage devices. During the process of broadcasting and receiving the standardized matrix X, each energy storage device uploads the collaborative control data to the station control center.

4. The method for interactive coordinated control of multi-source energy storage station information and energy according to claim 3, characterized in that: The energy interaction mathematical model is constructed based on the preprocessed data using the power balance equation, and the preprocessed data is input into the energy interaction mathematical model to obtain the total output power of the energy storage device group. The specific steps are: Based on the preprocessed standardized matrix X and the information interaction matrix M, the energy interaction mathematical model is constructed through the power balance equation.

5. The method for interactive coordinated control of multi-source energy storage station information and energy according to claim 4, characterized in that: The real-time data is collected and input into the energy interaction mathematical model to obtain the real-time prediction result. The specific steps are as follows: Collect the real-time operating status of energy storage equipment, total power consumption of the site and power generation of renewable energy through sensors and measuring instruments; The data were cleaned by linear interpolation and triple standard deviation method, and the data dimensions were unified by normalization method based on the cleaned data; Integrate the normalized data into a standardized matrix X, and construct the information interaction matrix M between energy storage devices based on the standardized matrix X; The preprocessed standardized matrix X and information interaction matrix M are input into the energy interaction mathematical model to obtain the real-time predicted total output power of the energy storage device group; 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.

6. The method for interactive and coordinated control of multi-source energy storage station information and energy according to claim 5, characterized in that: The power allocation value of each energy storage device is calculated based on the real-time prediction result through the target optimization algorithm, a power allocation plan is generated, and the power allocation plan is dynamically adjusted to obtain the optimal power allocation plan. The specific steps are: Based on the real-time prediction results, the power allocation value of each energy storage device is calculated by the target optimization algorithm; based on the power allocation value of each energy storage device obtained by calculation, a power allocation plan for the energy storage device group is obtained; According to the power allocation scheme Dynamically adjust the power output of energy storage equipment; When A j (t)>P max,j , A j (t) is limited to P max,j , where P max,j is the maximum discharge power of the jth energy storage device; When A j (t)<P min,j , A j (t) is limited to P min,j , where P min,j is the minimum discharge power of the jth energy storage device; When the remaining power of the energy storage device exceeds the safe range (S min,j ≤S j (t)≤S max,j ), give priority to adjusting the power allocation value of other energy storage devices; The power allocation scheme is dynamically adjusted to obtain the optimal power allocation scheme.

7. The method for interactive coordinated control of multi-source energy storage station information and energy according to claim 6, characterized in that: The specific steps of sending the optimal power allocation scheme to each energy storage device are as follows: Using Modbus TCP communication protocol, the station control center converts the best power allocation plan into power allocation instructions; Generate a power allocation instruction for each energy storage device separately and send it to the corresponding energy storage device via Ethernet; After receiving the power allocation instruction, the energy storage device verifies whether the power allocation value is within the allowable range of the device; Extract the power allocation value in the power allocation instruction and obtain the power range P allowed by the energy storage device min,j ≤A j * (t)≤P max,j ; When P min,j ≤A j * (t)≤P max,j , the power allocation value is within the power range allowed by the energy storage device, and the energy storage device executes the instruction normally; when or If the power allocation value exceeds the power range allowed by the energy storage device, the energy storage device will mark the abnormality and refuse to execute the instruction.

8. A multi-source energy storage station information and energy interactive collaborative control system, based on the multi-source energy storage station information and energy interactive collaborative control method according to any one of claims 1 to 7, characterized in that: Including acquisition module, information interaction module, energy interaction module, prediction module, allocation module and instruction module: The acquisition module is used to collect the operating status of the energy storage equipment, the total power consumption of the station and the power generation of renewable energy, and 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 state based on real-time data and mathematical models; The allocation module is used to calculate the power allocation value through the target optimization algorithm to generate a global optimal power allocation solution; The instruction module is used to send the optimal power allocation plan to the energy storage device, verify and execute the power allocation instruction, and feedback the execution status.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the multi-source energy storage station information and energy interactive collaborative control method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the multi-source energy storage station information and energy interactive collaborative control method described in any one of claims 1 to 7 are implemented.

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