Virtual Power Plant Power Coordination Method and System Based on Data Mining

Abstract

The present invention discloses a virtual power plant power coordination method and system based on data mining, which relates to the technical field of virtual power plants, and includes: obtaining assignable devices corresponding to energy storage devices based on the virtual power plant; using an energy storage power consumption analysis method to obtain energy storage distribution devices; optimizing the energy storage distribution devices based on real-time updates; analyzing the real-time distribution devices of electrical equipment and performing power coordination; The present invention is used to solve the problem that in the existing virtual power plant power coordination method, when the electrical equipment in the virtual power plant is not allocated power by the most effective energy storage device, the energy storage device supplying power to the electrical equipment cannot be flexibly replaced, resulting in the electrical equipment not being able to be allocated power by the most effective energy storage device, causing a low power distribution efficiency in the virtual power plant.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plants, and specifically to a virtual power plant power coordination method and system based on data mining. Background Art

[0002] Existing methods for virtual power plant power coordination usually establish a virtual power plant model and obtain the supply data and demand data among various units within the virtual power plant to establish a scheduling plan with the minimum operating cost and the lowest voltage fluctuation of the virtual power plant, so as to achieve the coordinated optimization of the virtual power plant. Although this improved method can ensure that the virtual power plant after coordinated optimization can operate in a stable and low-cost state, when the electrical equipment in the virtual power plant is not allocated power by the most effective energy storage device for it, only by establishing a stable and low-cost power plant operation plan, it is impossible to flexibly replace the energy storage device that supplies power to the electrical equipment, resulting in the electrical equipment in the virtual power plant not being able to be allocated power by the most effective energy storage device in real time when receiving power, causing the problem of low power distribution efficiency due to unreasonable power coordination in the virtual power plant. For example, in the patent application with the publication number CN116505591A, a virtual power plant participating in distribution network coordinated optimization scheduling method and device are disclosed. This solution constructs an upper-layer day-ahead optimization scheduling plan with the minimum comprehensive operating cost as the objective function based on supply-side data and demand-side data to improve the operation economy and reliability of the distribution network. Other improvements in virtual power plant power coordination usually focus on reducing losses and improving stability, and still cannot solve the problem that when the electrical equipment in the virtual power plant is not allocated power by the most effective energy storage device for it, it is impossible to flexibly replace the energy storage device that supplies power to the electrical equipment, resulting in the electrical equipment in the virtual power plant not being able to be allocated power by the most effective energy storage device in real time when receiving power, causing the problem of low power distribution efficiency due to unreasonable power coordination in the virtual power plant. In view of this, it is necessary to improve the existing virtual power plant power coordination method. Summary of the Invention

[0003] The present invention aims to solve at least one of the technical problems in the prior art to some extent. By proposing a virtual power plant power coordination method and system based on data mining, it is used to solve the problem in the existing virtual power plant power coordination method that when the electrical equipment in the virtual power plant is not allocated power by the most effective energy storage device for it, it is impossible to flexibly replace the energy storage device that supplies power to the electrical equipment, resulting in the electrical equipment in the virtual power plant not being able to be allocated power by the most effective energy storage device in real time when receiving power, causing the problem of low power distribution efficiency due to unreasonable power coordination in the virtual power plant.

[0004] To achieve the above object, in the first aspect, the present application provides a virtual power plant power coordination method based on data mining, including the following steps:

[0005] Obtain a plurality of energy storage devices and a plurality of power-consuming devices based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the plurality of power-consuming devices; analyze the power consumption data of the allocable devices of each energy storage device using the energy storage power consumption analysis method, and obtain the energy storage allocation device of each power-consuming device based on the analysis result.

[0006] Optimize the energy storage allocation device of each power-consuming device based on the power consumption data of the energy storage devices and power-consuming devices that are updated in real time in the virtual power plant, and obtain the latest energy storage allocation device of each power-consuming device based on the optimization result.

[0007] Analyze the real-time allocation device of the power-consuming device based on the energy storage allocation device of each power-consuming device, and perform power coordination within the virtual power plant based on the analysis result.

[0008] Further, obtaining a plurality of energy storage devices and a plurality of power-consuming devices based on the composition of the virtual power plant, and obtaining the allocable devices corresponding to each energy storage device from the plurality of power-consuming devices includes:

[0009] Obtain a plurality of energy storage devices within the virtual power plant and a plurality of power-consuming devices that are allocated power by the energy storage devices; for any one energy storage device, record the power-consuming devices that the energy storage device can allocate power to as the allocable devices of the energy storage device; obtain the allocable devices of all energy storage devices.

[0010] Obtain the power consumption data of the allocable devices of all energy storage devices, and analyze all the power consumption data using the energy storage power consumption analysis method, and obtain the energy storage allocation device of each power-consuming device based on the analysis result.

[0011] Further, the energy storage power consumption analysis method includes:

[0012] For any one energy storage device, record the power-consuming devices that are allocated power by the energy storage device as the allocable devices of the energy storage device; record the power consumption data of all the allocable devices of the energy storage device as allocation data FS1 to allocation data FS n , where the power consumption data includes the power amount allocated each time when the energy storage device allocates power to the allocable device.

[0013] For any one allocation data FS c , establish a plane rectangular coordinate system, and denote it as the energy storage allocation coordinate system, where the unit of the X-axis of the energy storage allocation coordinate system is the number axis, and the unit of the Y-axis is kwh; record the number of times when the energy storage device allocates power to the allocable device in the allocation data FS c as t, and record the power amounts allocated by the energy storage device to the allocable device from the first time to the t-th time in the allocation data FS c as C1 to C t, plot the first distribution point to the t-th distribution point in the energy storage distribution coordinate system, where the abscissas of the first distribution point to the t-th distribution point are from 1 to t, and the ordinates are from C1 to C t , where c is a positive integer less than or equal to n and greater than or equal to 1.

[0014] Furthermore, the energy storage power consumption analysis method further includes:

[0015] Fit the first distribution point to the t-th distribution point into a curve, denoted as the energy storage distribution curve, mark the point with the largest absolute value of the slope in the energy storage distribution curve as the distribution fluctuation point, and mark the ordinate of the distribution fluctuation point as the fluctuation power;

[0016] Obtain the distribution fluctuation points and fluctuation powers corresponding to all distribution data FS of the energy storage device, and use the distribution fluctuation algorithm to obtain the distribution division value of the energy storage device. The distribution fluctuation algorithm is: , where F is the distribution division value, k i is the absolute value of the slope of the distribution fluctuation point of the i-th distribution data FS of the energy storage device, j i is the fluctuation power of the distribution fluctuation point of the i-th distribution data FS of the energy storage device, k min is the minimum value of the absolute values of all distribution fluctuation points of the energy storage device, k max is the maximum value of the absolute values of all distribution fluctuation points of the energy storage device, j min is the minimum value of all fluctuation powers of the energy storage device, j max is the maximum value of all fluctuation powers of the energy storage device, and n is the number of distribution data FS.

[0017] Furthermore, the energy storage power consumption analysis method further includes:

[0018] Record the value obtained by dividing the fluctuation power of the distribution data FS by the absolute value of the distribution fluctuation point as the distribution parameter of the distribution data FS; mark the allocable device of the distribution data FS with a distribution parameter greater than the distribution division value as the preferred allocable device of the energy storage device, and mark the allocable device corresponding to the distribution data FS with a distribution parameter less than or equal to the distribution division value as the alternative allocable device of the energy storage device;

[0019] Obtain the preferred allocable devices and alternative allocable devices of all energy storage devices.

[0020] Furthermore, the energy storage power consumption analysis method further includes:

[0021] For any allocable device α of all energy storage devices, mark the energy storage devices in which the allocable device α is marked as the preferred allocable device among all energy storage devices as the two-way preferred devices of the allocable device α, and mark the energy storage devices in which the allocable device α is marked as the alternative allocable device among all energy storage devices as the two-way alternative devices of the allocable device α;

[0022] Obtain all the allocated power of the allocable device α, and record them in turn as the first allocated power to the mth allocated power; establish a plane rectangular coordinate system, denoted as the allocation analysis coordinate system, where the X-axis of the allocation analysis coordinate system is the number axis and the Y-axis is kwh; based on the first allocated power to the mth allocated power, punctuate between the straight line x = 1 and the straight line x = m, and record the straight line obtained by fitting all the punctuations as the device allocation straight line; denote the midpoint of the line segment between x = 1 and x = m on the device allocation straight line as the allocation reference point, and denote the ordinate of the allocation reference point as the allocation reference power.

[0023] Furthermore, the energy storage power consumption analysis method further includes:

[0024] Denote the energy storage devices corresponding to the allocated powers greater than the allocation reference power among the first allocated power to the mth allocated power as the preferred energy storage devices of the allocable device α; denote the energy storage devices corresponding to the allocated powers less than or equal to the allocation reference power among the first allocated power to the mth allocated power as the alternative energy storage devices of the allocable device α;

[0025] Denote the energy storage devices that are simultaneously recorded as the two-way preferred devices and the preferred energy storage devices of the allocable device α as the energy storage allocation devices of the allocable device α;

[0026] Obtain the energy storage allocation devices of all allocable devices.

[0027] Furthermore, analyze the real-time allocation devices of the electrical equipment based on the energy storage allocation devices of each electrical equipment, and perform power coordination in the virtual power plant based on the analysis results, including:

[0028] For any electrical equipment, obtain in real time the device that allocates power to the electrical equipment, and record it as the real-time allocation device; when the real-time allocation device is not the energy storage allocation device of the electrical equipment, record all the energy storage allocation devices of the real-time allocation device as the alternative usage devices;

[0029] When the real-time allocation device is the energy storage allocation device of the electrical equipment, record the allocation parameter of the electrical equipment in the real-time allocation device as the scheduling measurement parameter; record the energy storage allocation devices of the electrical equipment whose allocation parameters of the electrical equipment are greater than the scheduling measurement parameter as the alternative usage devices of the electrical equipment.

[0030] Furthermore, analyze the real-time allocation devices of the electrical equipment based on the energy storage allocation devices of each electrical equipment, and perform power coordination in the virtual power plant based on the analysis results also includes: when any one of the alternative usage devices of the electrical equipment is in an idle state, adjust the device that allocates power to the electrical equipment to the alternative usage device in the idle state.

[0031] In a second aspect, the present application also provides a virtual power plant power coordination system based on data mining, including an energy storage allocation analysis module, a parameter optimization analysis module, and an equilibrium regulation module;

[0032] The energy storage allocation analysis module is used to obtain a plurality of energy storage devices and a plurality of power-consuming devices based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the plurality of power-consuming devices; analyze the power consumption data of the allocable devices of each energy storage device using the energy storage power consumption analysis method, and obtain the energy storage allocation devices of each power-consuming device based on the analysis results;

[0033] The parameter optimization analysis module is used to optimize the energy storage allocation devices of each power-consuming device based on the power consumption data of the energy storage devices and power-consuming devices that are updated in real time in the virtual power plant, and obtain the latest energy storage allocation devices of each power-consuming device based on the optimization results;

[0034] The equilibrium regulation module is used to analyze the real-time allocation devices of the power-consuming devices based on the equilibrium parameter intervals of each power-consuming device, and perform power coordination within the virtual power plant based on the analysis results.

[0035] Advantages of the present invention: The present application first obtains a plurality of energy storage devices and a plurality of power-consuming devices based on the composition of the virtual power plant, and obtains the allocable devices corresponding to each energy storage device from the plurality of power-consuming devices; analyzes the power consumption data of the allocable devices of each energy storage device using the energy storage power consumption analysis method, and obtains the energy storage allocation devices of each power-consuming device based on the analysis results. The advantage of this is that by analyzing the power consumption data using the energy storage power consumption analysis method and obtaining the energy storage allocation devices of each power-consuming device, it is possible to obtain the most effective and stable energy storage device among the energy storage devices that supply power to the power-consuming devices, which helps to ensure that the replaced energy storage device can improve the power allocation efficiency of the virtual power plant when replacing the energy storage device of the power-consuming device subsequently;

[0036] This application also optimizes the energy storage distribution device of each electrical device based on the real-time updated energy storage devices and the electricity consumption data of electrical devices in the virtual power plant, and obtains the latest energy storage distribution device of each electrical device based on the optimization results; finally, analyzes the real-time distribution device of the electrical device based on the energy storage distribution device of each electrical device, and coordinates the power within the virtual power plant based on the analysis results. The advantage of this is that by optimizing the energy storage distribution device of the electrical device, it can ensure that the energy storage distribution device of the electrical device is an energy storage distribution device that conforms to the actual power supply state, so as to ensure the timeliness of subsequent analysis; by coordinating the power of the virtual power plant based on the energy storage distribution device, when the electrical device is not allocated power by the most effective energy storage device for it, the energy storage device supplying power to the electrical device can be flexibly replaced, so that the electrical device can be allocated power by the most effective energy storage device in real time when receiving power, improving the power distribution efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a schematic block diagram of the system of the present invention;

[0038] Figure 2 is a flowchart of the steps of the method of the present invention;

[0039] Figure 3 is a schematic diagram of the distribution analysis coordinate system of the present invention;

[0040] Figure 4 is a schematic structural diagram of the electronic device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] Example 1, please refer to Figure 1 As shown, this application provides a virtual power plant power coordination system based on data mining, including an energy storage distribution analysis module, a parameter optimization analysis module, and an equilibrium adjustment module;

[0043] The energy storage distribution analysis module is used to obtain a plurality of energy storage devices and a plurality of electrical devices based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the plurality of electrical devices; analyze the electricity consumption data of the allocable devices of each energy storage device using the energy storage electricity analysis method, and obtain the energy storage distribution device of each electrical device based on the analysis results;

[0044] The energy storage distribution analysis module includes an energy storage distribution analysis unit, and the energy storage distribution analysis unit is configured with an energy storage distribution analysis strategy, and the energy storage distribution analysis strategy includes:

[0045] Obtain multiple energy storage devices in the virtual power plant and multiple power-consuming devices that are allocated power by the energy storage devices; for any one energy storage device, record the power-consuming devices that the energy storage device can allocate power to as the allocable devices of the energy storage device; obtain the allocable devices of all energy storage devices;

[0046] Obtain the power consumption data of the allocable devices of all energy storage devices, and use the energy storage power consumption analysis method to analyze all power consumption data, and obtain the energy storage distribution devices of each power-consuming device based on the analysis results;

[0047] In the specific implementation process, in this embodiment, the energy storage device can be an electrochemical energy storage device, a mechanical energy storage device or a thermal energy storage device in the virtual power plant, and the energy storage device can be obtained according to the composition of the energy storage devices in the actually analyzed virtual power plant; the power-consuming device can be a set of multiple devices. For example, all the power-consuming devices in the same factory can be integrated into one power-consuming device, that is, analyze the power supply data of the energy storage device and the factory to simplify the analysis process and improve the analysis efficiency;

[0048] The energy storage power consumption analysis method includes: for any one energy storage device, record the power-consuming devices that are allocated power by the energy storage device as the allocable devices of the energy storage device; record the power consumption data of all the allocable devices of the energy storage device in sequence as allocation data FS1 to allocation data FS n , where the power consumption data includes the power allocated each time when the energy storage device allocates power to the allocable device;

[0049] In the specific implementation process, because in the virtual power plant, the types and quantities of energy storage devices are not fixed, so the same power-consuming device may be allocated power by multiple energy storage devices. By obtaining allocation data FS1 to allocation data FS n , the data when the power-consuming device is allocated power by multiple energy storage devices can be obtained to obtain the energy storage device that is more effective in supplying power to the power-consuming device;

[0050] For any one allocation data FS c , establish a plane rectangular coordinate system and denote it as the energy storage distribution coordinate system. Among them, the unit of the X-axis of the energy storage distribution coordinate system is the number axis, and the unit of the Y-axis is kWh; record the number of times when the energy storage device allocates power to the allocable device in the allocation data FS c as t, and record the power allocated by the energy storage device to the allocable device from the first time to the tth time in the allocation data FS c as C1 to C t, plot the first allocation point to the t-th allocation point in the energy storage allocation coordinate system, where the abscissas of the first allocation point to the t-th allocation point are from 1 to t, and the ordinates are from C1 to C t , where c is a positive integer less than or equal to n and greater than or equal to 1;

[0051] Fit the first allocation point to the t-th allocation point into a curve, denoted as the energy storage allocation curve. Denote the point with the largest absolute value of the slope in the energy storage allocation curve as the allocation fluctuation point, and denote the ordinate of the allocation fluctuation point as the fluctuation power.

[0052] Obtain the allocation fluctuation points and the fluctuation power corresponding to all the allocation data FS of the energy storage device, and use the allocation fluctuation algorithm to obtain the allocation division value of the energy storage device. The allocation fluctuation algorithm is: , where F is the allocation division value, k i is the absolute value of the slope of the allocation fluctuation point of the i-th allocation data FS of the energy storage device, j i is the fluctuation power of the allocation fluctuation point of the i-th allocation data FS of the energy storage device, k min is the minimum value of the absolute values of all the allocation fluctuation points of the energy storage device, k max is the maximum value of the absolute values of all the allocation fluctuation points of the energy storage device, j min is the minimum value of all the fluctuation powers of the energy storage device, j max is the maximum value of all the fluctuation powers of the energy storage device, and n is the number of the allocation data FS;

[0053] In the specific implementation process, for example, in a data processing, the slopes of the allocation fluctuation points of all the allocation data FS pairs of the energy storage device are 1, 2, -2, -4, and -1 respectively, and the fluctuation powers are 1000 kwh, 1500 kwh, 2000 kwh, 2000 kwh, and 1000 kwh respectively. Then, through calculation, the allocation division value of the energy storage device is 916.7; in this embodiment, by obtaining the allocation division value, the screening value for the electrical equipment can be obtained based on the allocation status of all the electrical equipment allocated by the energy storage device. The larger the fluctuation power and the smaller the absolute value of the slope of the allocation fluctuation point, the larger the allocated power of the energy storage device to the electrical equipment and the smaller the fluctuation during power allocation, that is, the energy storage device is more suitable for power allocation to the electrical equipment; while the smaller the fluctuation power and the larger the absolute value of the slope of the allocation fluctuation point, the smaller the allocated power of the energy storage device to the electrical equipment and the larger the fluctuation during power allocation, that is, the energy storage device is not suitable for power allocation to the electrical equipment; by obtaining the allocation parameters and comparing them with the allocation division value subsequently, all the electrical equipment allocated by the energy storage device can be divided more intuitively;

[0054] The value obtained by dividing the fluctuating power of the allocated data FS by the absolute value of the allocation fluctuation point is denoted as the allocation parameter of the allocated data FS; the allocable devices of the allocated data FS with an allocation parameter greater than the allocation division value are denoted as the preferred allocation devices of the energy storage device, and the allocable devices corresponding to the allocated data FS with an allocation parameter less than or equal to the allocation division value are denoted as the alternative allocation devices of the energy storage device;

[0055] In a specific process, for example, in a single data processing, the obtained allocation division value is 916.7, the allocated power of the allocated data FS is 1000 kwh, and the absolute value of the allocation fluctuation point is 1. Then, the allocation parameter of the allocated data FS can be obtained as 1000, and the allocable devices of the allocated data FS can be denoted as the preferred allocation devices of the energy storage device;

[0056] Obtain the preferred allocation devices and alternative allocation devices of all energy storage devices;

[0057] For any allocable device α of all energy storage devices, the energy storage devices in which the allocable device α is denoted as the preferred allocation device among all energy storage devices are denoted as the two-way preferred devices of the allocable device α, and the energy storage devices in which the allocable device α is denoted as the alternative allocation device among all energy storage devices are denoted as the two-way alternative devices of the allocable device α;

[0058] Obtain all the allocated powers of the allocable device α, and denote them as the first allocated power to the mth allocated power in sequence; establish a plane rectangular coordinate system, denoted as the allocation analysis coordinate system. Among them, the X-axis of the allocation analysis coordinate system is a number axis, representing the serial numbers of the first allocated power to the mth allocated power, and the Y-axis is in kwh, representing the power magnitudes corresponding to the first allocated power to the mth allocated power; based on the first allocated power to the mth allocated power, punctuate between the straight line x = 1 and the straight line x = m, and denote the straight line obtained by fitting all the punctuations as the device allocation straight line; denote the midpoint of the line segment between x = 1 and x = m on the device allocation straight line as the allocation reference point, and denote the ordinate of the allocation reference point as the allocation reference power;

[0059] In a specific implementation process, for example, in a single data processing, the obtained allocation analysis coordinate system is as Figure 3 shown. Among them, m is 4, ○ is the punctuation in the allocation analysis coordinate system, the straight line where the point ZZ1 and the point ZZ2 are located is the device allocation straight line, and the point CK is the allocation reference point. Through analysis, it can be obtained that the second allocated power corresponding to the abscissa of 2 is greater than the allocation reference power. Then, the energy storage device corresponding to the second allocated power can be denoted as the preferred energy storage device of the allocable device;

[0060] The energy storage devices corresponding to the allocated power greater than the allocation reference power among the first allocated power to the mth allocated power are denoted as the preferred energy storage devices of the allocable device α; the energy storage devices corresponding to the allocated power less than or equal to the allocation reference power among the first allocated power to the mth allocated power are denoted as the alternative energy storage devices of the allocable device α.

[0061] The energy storage devices that are simultaneously denoted as the two-way preferred devices and the preferred energy storage devices of the allocable device α are denoted as the energy storage allocation devices of the allocable device α.

[0062] In the specific implementation process, by obtaining the energy storage allocation devices of the allocable device based on the two-way preferred devices and the preferred energy storage devices, it can be ensured that the obtained energy storage allocation devices are the most effective and stable energy storage devices for the electrical equipment, which helps to ensure that the replaced energy storage devices can improve the power allocation efficiency of the virtual power plant when replacing the energy storage devices of the electrical equipment subsequently.

[0063] Obtain the energy storage allocation devices of all allocable devices.

[0064] The parameter optimization analysis module is used to optimize the energy storage allocation devices of each electrical equipment based on the real-time updated energy storage devices and the electricity consumption data of the electrical equipment in the virtual power plant, and obtain the latest energy storage allocation devices of each electrical equipment based on the optimization results.

[0065] In the specific implementation process, the optimization process of the energy storage allocation devices of each electrical equipment in this embodiment is to obtain the energy storage devices and the electricity consumption data of the electrical equipment through real-time updates, and then use the energy storage electricity analysis method to obtain the energy storage allocation devices of each electrical equipment to realize the real-time update of the energy storage allocation devices of the electrical equipment, so that the energy storage allocation devices of the electrical equipment can better conform to the real-time situation, thereby realizing the optimization.

[0066] The balance adjustment module is used to analyze the real-time allocation devices of the electrical equipment based on the balance parameter intervals of each electrical equipment, and perform power coordination within the virtual power plant based on the analysis results; the balance adjustment module includes a power balance adjustment unit, and the power balance adjustment unit is configured with a power balance adjustment strategy, and the power balance adjustment strategy includes:

[0067] For any electrical equipment, the device for allocating power to the electrical equipment is obtained in real time and denoted as the real-time allocation device; when the real-time allocation device is not the energy storage allocation device of the electrical equipment, all the energy storage allocation devices of the real-time allocation device are denoted as alternative devices for use.

[0068] When the real-time allocation device is the energy storage allocation device for the electrical device, the allocation parameter of the electrical device in the real-time allocation device is denoted as the scheduling measurement parameter; the energy storage allocation device in which the allocation parameter of the electrical device in the energy storage allocation device of the electrical device is greater than the scheduling measurement parameter is denoted as the alternative usage device of the electrical device;

[0069] In the specific implementation process, for example, in a data processing, the allocation parameter of the electrical device in the real-time allocation device is 916.7, and there is an energy storage allocation device with an allocation parameter of 1000 for the electrical device. Since the larger the allocation parameter, the greater the allocated power of the energy storage device to the electrical device and the smaller the fluctuation during power allocation, that is, the energy storage device is more suitable for power allocation to the electrical device. Then, the energy storage allocation device with an allocation parameter of 1000 for the electrical device can be denoted as the alternative usage device for subsequent replacement, so as to realize the flexible replacement of the energy storage device supplying power to the electrical device when the electrical device is not allocated power by the most effective energy storage device for it, thereby improving the power allocation efficiency;

[0070] When any one of the alternative usage devices of the electrical device is in an idle state, the device for power allocation to the electrical device is adjusted to the alternative usage device in the idle state.

[0071] Example 2, please refer to Figure 2 As shown, the present application also provides a virtual power plant power coordination method based on data mining, including the following steps:

[0072] Step S1, obtain multiple energy storage devices and multiple electrical devices based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the multiple electrical devices; analyze the power consumption data of the allocable devices of each energy storage device using the energy storage power consumption analysis method, and obtain the energy storage allocation device of each electrical device based on the analysis result;

[0073] Step S1 includes: Step S101, obtain multiple energy storage devices in the virtual power plant and multiple electrical devices powered by the energy storage devices; for any one energy storage device, denote the electrical devices that the energy storage device can allocate power to as the allocable devices of the energy storage device; obtain the allocable devices of all energy storage devices;

[0074] Step S102, obtain the power consumption data of the allocable devices of all energy storage devices, and analyze all the power consumption data using the energy storage power consumption analysis method, and obtain the energy storage allocation device of each electrical device based on the analysis result; the energy storage power consumption analysis method includes: Step S1021, for any one energy storage device, denote the electrical devices powered by the energy storage device as the allocable devices of the energy storage device; denote the power consumption data of all the allocable devices of the energy storage device as allocation data FS1 to allocation data FS n, where the power consumption data includes the power amount allocated each time when the energy storage device allocates power to the allocable device;

[0075] Step S1022, for any allocation data FS c , establish a plane rectangular coordinate system, denoted as the energy storage allocation coordinate system. Among them, the unit of the X-axis of the energy storage allocation coordinate system is the number axis, and the unit of the Y-axis is kWh; record the number of times the energy storage device allocates power to the allocable device in the allocation data FS c as t, and record the power amounts allocated by the energy storage device to the allocable device from the first to the t-th time in the allocation data FS c as C1 to C t , and plot the first allocation point to the t-th allocation point in the energy storage allocation coordinate system. Among them, the abscissas of the first allocation point to the t-th allocation point are 1 to t, and the ordinates are C1 to C t , where c is a positive integer less than or equal to n and greater than or equal to 1;

[0076] Step S1023, fit the first allocation point to the t-th allocation point into a curve, denoted as the energy storage allocation curve. Denote the point with the largest absolute value of the slope in the energy storage allocation curve as the allocation fluctuation point, and denote the ordinate of the allocation fluctuation point as the fluctuation power amount;

[0077] Step S1024, obtain the allocation fluctuation points and the fluctuation power amounts corresponding to all the allocation data FS of the energy storage device, and use the allocation fluctuation algorithm to obtain the allocation division value of the energy storage device. The allocation fluctuation algorithm is: , where F is the allocation division value, k i is the absolute value of the slope of the allocation fluctuation point of the i-th allocation data FS of the energy storage device, j i is the fluctuation power amount of the allocation fluctuation point of the i-th allocation data FS of the energy storage device, k min is the minimum value of the absolute values of all the allocation fluctuation points of the energy storage device, k max is the maximum value of the absolute values of all the allocation fluctuation points of the energy storage device, j min is the minimum value of all the fluctuation power amounts of the energy storage device, j max is the maximum value of all the fluctuation power amounts of the energy storage device, and n is the number of the allocation data FS;

[0078] Step S1024, record the value obtained by dividing the fluctuation power amount of the allocation data FS by the absolute value of the allocation fluctuation point as the allocation parameter of the allocation data FS; denote the allocable device corresponding to the allocation data FS with the allocation parameter greater than the allocation division value as the preferred allocation device of the energy storage device, and denote the allocable device corresponding to the allocation data FS with the allocation parameter less than or equal to the allocation division value as the alternative allocation device of the energy storage device;

[0079] Step S1025: Obtain the preferred allocation devices and alternative allocation devices of all energy storage devices;

[0080] Step S1026: For any allocable device α of all energy storage devices, the energy storage devices in which allocable device α is recorded as the preferred allocation device among all energy storage devices are denoted as the two-way preferred devices of allocable device α, and the energy storage devices in which allocable device α is recorded as the alternative allocation device among all energy storage devices are denoted as the two-way alternative devices of allocable device α;

[0081] Step S1027: Obtain all the allocated electricity of allocable device α, and denote them as the first allocated electricity to the m-th allocated electricity in sequence; Establish a plane rectangular coordinate system, denoted as the allocation analysis coordinate system, where the X-axis of the allocation analysis coordinate system is a number axis and the Y-axis is kWh; Based on the first allocated electricity to the m-th allocated electricity, punctuate between the straight line x = 1 and the straight line x = m, and denote the straight line obtained by fitting all the punctuations as the device allocation line; Denote the midpoint of the line segment between x = 1 and x = m on the device allocation line as the allocation reference point, and denote the ordinate of the allocation reference point as the allocation reference electricity;

[0082] Step S1028: Denote the energy storage devices corresponding to the allocated electricity greater than the allocation reference electricity among the first allocated electricity to the m-th allocated electricity as the preferred energy storage devices of allocable device α; Denote the energy storage devices corresponding to the allocated electricity less than or equal to the allocation reference electricity among the first allocated electricity to the m-th allocated electricity as the alternative energy storage devices of allocable device α;

[0083] Step S1029: Denote the energy storage devices that are simultaneously recorded as the two-way preferred devices and the preferred energy storage devices of allocable device α as the energy storage allocation devices of allocable device α;

[0084] Obtain the energy storage allocation devices of all allocable devices.

[0085] Step S2: Optimize the energy storage allocation devices of each electrical equipment based on the real-time updated energy storage devices and electrical consumption data of electrical equipment in the virtual power plant, and obtain the latest energy storage allocation devices of each electrical equipment based on the optimization results.

[0086] Step S3: Analyze the real-time allocation devices of electrical equipment based on the energy storage allocation devices of each electrical equipment, and conduct power coordination in the virtual power plant based on the analysis results;

[0087] Step S3 includes: Step S301: For any electrical equipment, obtain in real time the device for allocating electricity to the electrical equipment, and denote it as the real-time allocation device; When the real-time allocation device is not the energy storage allocation device of the electrical equipment, denote all the energy storage allocation devices of the real-time allocation device as alternative usage devices;

[0088] Step S302, when the real-time allocation device is the energy storage allocation device of the power-consuming device, record the allocation parameter of the power-consuming device in the real-time allocation device as the scheduling measurement parameter; record the energy storage allocation device in which the allocation parameter of the power-consuming device in the energy storage allocation device of the power-consuming device is greater than the scheduling measurement parameter as the alternative device for the power-consuming device.

[0089] Step S303, when any alternative device of the power-consuming device is in an idle state, adjust the device for power allocation to the power-consuming device to the alternative device in the idle state.

[0090] Embodiment 3, please refer to Figure 4 as shown in Figure 4 illustrates a schematic structural diagram of an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, it runs the steps in the virtual power plant power coordination method based on data mining to achieve the following functions: First, obtain multiple energy storage devices and multiple power-consuming devices based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the multiple power-consuming devices; use the energy storage power consumption analysis method to analyze the power consumption data of the allocable devices of each energy storage device, and obtain the energy storage allocation device of each power-consuming device based on the analysis results; then optimize the energy storage allocation device of each power-consuming device based on the real-time updated energy storage devices and power consumption data of the power-consuming devices in the virtual power plant, and obtain the latest energy storage allocation device of each power-consuming device based on the optimization results; finally, analyze the real-time allocation device of the power-consuming device based on the energy storage allocation device of each power-consuming device, and perform power coordination within the virtual power plant based on the analysis results.

[0091] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software function units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0092] Embodiment 4. The present application further provides a computer-readable storage medium. The present application provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above virtual power plant power coordination method based on data mining are run to implement the following functions: First, based on the composition of the virtual power plant, a plurality of energy storage devices and a plurality of power-consuming devices are obtained, and the assignable devices corresponding to each energy storage device are obtained from the plurality of power-consuming devices; The energy storage power consumption analysis method is used to analyze the power consumption data of the assignable devices of each energy storage device, and the energy storage allocation devices of each power-consuming device are obtained based on the analysis results; Then, based on the real-time updated power consumption data of the energy storage devices and power-consuming devices in the virtual power plant, the energy storage allocation devices of each power-consuming device are optimized, and the latest energy storage allocation devices of each power-consuming device are obtained based on the optimization results; Finally, based on the energy storage allocation devices of each power-consuming device, the real-time allocation devices of the power-consuming devices are analyzed, and power coordination is performed within the virtual power plant based on the analysis results.

[0093] Through the description of the above embodiments, the embodiments of the present invention can be provided as a method, a system or a computer program product. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0094] In the embodiments provided by the present application, it should be understood that the disclosed system or method can be implemented in other ways. The above-described embodiments are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For another example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces. The indirect coupling or communication connection of the system, module, and unit can be in an electrical, mechanical, or other form.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A virtual power plant power coordination method based on data mining, characterized in that, Including the following steps: Obtain a plurality of energy storage devices and a plurality of power-consuming devices based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the plurality of power-consuming devices; Analyze the power consumption data of the allocable devices of each energy storage device using the energy storage power consumption analysis method, and obtain the energy storage allocation devices of each power-consuming device based on the analysis results; For any energy storage device, the electrical equipment that receives the power allocated by the energy storage device is denoted as the allocable device of the energy storage device; the electrical consumption data of all the allocable devices of the energy storage device are sequentially denoted as allocation data FS1 to allocation data FS n , where the electrical consumption data includes the amount of power allocated each time when the energy storage device allocates power to the allocable device; For any allocated data FS c , establish a rectangular coordinate system in the plane and denote it as the energy storage allocation coordinate system. Among them, the unit of the X-axis of the energy storage allocation coordinate system is the number axis, and the unit of the Y-axis is kWh; the allocated data FS c The number of times the energy storage device allocates electricity to the allocable device is denoted as t, and the allocated data FS c The electricity allocated by the energy storage device to the allocable device from the first to the t-th time is denoted as C1 to C t , plot the first allocation point to the t-th allocation point in the energy storage allocation coordinate system. Among them, the abscissas of the first allocation point to the t-th allocation point are 1 to t, and the ordinates are C1 to C t , where c is a positive integer less than or equal to n and greater than or equal to 1; Fit the first distribution point to the t-th distribution point into a curve, denoted as the energy storage allocation curve, denote the point with the largest absolute value of the slope in the energy storage allocation curve as the distribution fluctuation point, and denote the ordinate of the distribution fluctuation point as the fluctuation power; Obtain the allocation fluctuation points and the fluctuating power corresponding to all the allocation data FS of the energy storage device, and use the allocation fluctuation algorithm to obtain the allocation division value of the energy storage device. The allocation fluctuation algorithm is as follows: , where F is the allocation division value, and k i is the absolute value of the slope of the allocation fluctuation point of the i-th allocation data FS of the energy storage device, and j i is the fluctuating power of the allocation fluctuation point of the i-th allocation data FS of the energy storage device, and k min is the minimum value of the absolute values of all the allocation fluctuation points of the energy storage device, and k max is the maximum value of the absolute values of all the allocation fluctuation points of the energy storage device, and j min is the minimum value of all the fluctuating powers of the energy storage device, and j max is the maximum value of all the fluctuating powers of the energy storage device, and n is the number of the allocation data FS; Optimize the energy storage allocation devices of each power-consuming device based on the power consumption data of the energy storage devices and power-consuming devices that are updated in real time in the virtual power plant, and obtain the latest energy storage allocation devices of each power-consuming device based on the optimization results; Analyze the real-time allocation devices of the power-consuming devices based on the energy storage allocation devices of each power-consuming device, and perform power coordination in the virtual power plant based on the analysis results.

2. The virtual power plant power coordination method based on data mining according to claim 1, wherein, Obtaining a plurality of energy storage devices and a plurality of power-consuming devices based on the composition of the virtual power plant, and obtaining the allocable devices corresponding to each energy storage device from the plurality of power-consuming devices includes: Obtain a plurality of energy storage devices in the virtual power plant and a plurality of power-consuming devices that are powered by the energy storage devices; for any one energy storage device, denote the power-consuming devices that the energy storage device can allocate power to as the allocable devices of the energy storage device; obtain the allocable devices of all energy storage devices; Obtain the power consumption data of the allocable devices of all energy storage devices, analyze all the power consumption data using the energy storage power consumption analysis method, and obtain the energy storage allocation devices of each power-consuming device based on the analysis results.

3. The virtual power plant power coordination method based on data mining according to claim 2, characterized in that, The energy storage power consumption analysis method also includes: Denote the value obtained by dividing the fluctuation power of the distribution data FS by the absolute value of the distribution fluctuation point as the distribution parameter of the distribution data FS; denote the allocable devices of the distribution data FS with the distribution parameter greater than the distribution division value as the preferred allocation devices of the energy storage device, and denote the allocable devices corresponding to the distribution data FS with the distribution parameter less than or equal to the distribution division value as the alternative allocation devices of the energy storage device; Obtain the preferred allocation devices and alternative allocation devices of all energy storage devices.

4. The virtual power plant power coordination method based on data mining according to claim 3, characterized in that The energy storage power consumption analysis method also includes: For any one allocable device α of all energy storage devices, denote the energy storage devices in which the allocable device α is denoted as the preferred allocation device among all energy storage devices as the two-way preferred devices of the allocable device α, and denote the energy storage devices in which the allocable device α is denoted as the alternative allocation device among all energy storage devices as the two-way alternative devices of the allocable device α; Obtain all the allocated powers of the allocable device α, and denote them as the first allocated power to the m-th allocated power in sequence; establish a plane rectangular coordinate system, denoted as the distribution analysis coordinate system, where the X-axis of the distribution analysis coordinate system is a number axis and the Y-axis is kWh; based on the first allocated power to the m-th allocated power, punctuate between the straight line x = 1 and the straight line x = m, and denote the straight line obtained by fitting all the punctuations as the device allocation straight line; denote the midpoint of the line segment between x = 1 and x = m in the device allocation straight line as the distribution reference point, and denote the ordinate of the distribution reference point as the distribution reference power.

5. The virtual power plant power coordination method based on data mining according to claim 4, wherein, The energy storage power consumption analysis method also includes: The energy storage devices corresponding to the allocated power greater than the allocation reference power among the first allocated power to the mth allocated power are recorded as the preferred energy storage devices of the allocable device α; the energy storage devices corresponding to the allocated power less than or equal to the allocation reference power among the first allocated power to the mth allocated power are recorded as the alternative energy storage devices of the allocable device α. The energy storage devices that are simultaneously recorded as the two-way preferred devices and the preferred energy storage devices of the allocable device α are recorded as the energy storage allocation devices of the allocable device α. Obtain the energy storage allocation devices of all allocable devices.

6. The virtual power plant power coordination method based on data mining according to claim 5, wherein Analyze the real-time allocation devices of the electrical equipment based on the energy storage allocation devices of each electrical equipment, and conduct power coordination within the virtual power plant based on the analysis results, including: For any electrical equipment, obtain the device that allocates power to the electrical equipment in real time, and record it as the real-time allocation device; when the real-time allocation device is not the energy storage allocation device of the electrical equipment, record all the energy storage allocation devices of the real-time allocation device as the alternative usage devices. When the real-time allocation device is the energy storage allocation device of the electrical equipment, record the allocation parameter of the electrical equipment in the real-time allocation device as the scheduling measurement parameter; record the energy storage allocation devices of the electrical equipment whose allocation parameters of the electrical equipment are greater than the scheduling measurement parameter as the alternative usage devices of the electrical equipment.

7. The virtual power plant power coordination method based on data mining according to claim 6, characterized in that Analyze the real-time allocation devices of the electrical equipment based on the energy storage allocation devices of each electrical equipment, and conduct power coordination within the virtual power plant based on the analysis results also includes: when any one of the alternative usage devices of the electrical equipment is in an idle state, adjust the device that allocates power to the electrical equipment to the alternative usage device in the idle state.

8. A virtual power plant power coordination system based on data mining, which is used to implement the virtual power plant power coordination method based on data mining according to any one of claims 1-7, characterized in that, It includes an energy storage allocation analysis module, a parameter optimization analysis module, and an equilibrium adjustment module; The energy storage allocation analysis module is used to obtain multiple energy storage devices and multiple electrical equipment based on the composition of the virtual power plant, and obtain the allocable devices corresponding to each energy storage device from the multiple electrical equipment; Use the energy storage power consumption analysis method to analyze the power consumption data of the allocable devices of each energy storage device, and obtain the energy storage allocation devices of each electrical equipment based on the analysis results; The parameter optimization analysis module is used to optimize the energy storage allocation devices of each electrical equipment based on the power consumption data of the energy storage devices and electrical equipment that are updated in real time in the virtual power plant, and obtain the latest energy storage allocation devices of each electrical equipment based on the optimization results; The equilibrium adjustment module is used to analyze the real-time allocation devices of the electrical equipment based on the equilibrium parameter interval of each electrical equipment, and conduct power coordination within the virtual power plant based on the analysis results.

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