Power supply control method and device of photovoltaic energy storage charging pile, medium, equipment and product

Abstract

The invention discloses a power supply control method and device of a photovoltaic energy storage charging pile, a medium, equipment and a product, relates to the technical field of electric power, and is used for improving the operation safety of a power distribution network. The method comprises the following steps: determining a state transition matrix Pt of the new energy vehicle; according to the state transition matrix, a Monte Carlo method is used for sampling and calculating an electrical load curve of the target automobile charging pile; the electrical load curve is used for representing electrical loads at different moments, the high-load time period of the target automobile charging pile is determined according to the electrical load curve of the target automobile charging pile, and the energy storage equipment is used for carrying out auxiliary power supply on the automobile charging pile machine in the high-load time period.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of power technologies, and in particular, to a power supply control method, device, medium, equipment and product for a photovoltaic energy storage charging pile. Background Art

[0002] With the continuous increase in the number of new energy vehicles, the charging demand for new energy vehicles has gradually increased. The time, location, and power of new energy vehicles to choose charging are uncertain, resulting in strong intermittency and randomness of the generated charging load. In particular, the instantaneous power of the charging load generated by the fast charging mode is greater, and the choice of charging time and location is more random, and the power supply of the charging pile cannot be adjusted according to the load state of the charging pile, which brings risks and challenges to the safe operation of the distribution network. Summary of the Invention

[0003] The present application provides a power supply control method, device, medium, equipment and product for a photovoltaic energy storage charging pile, which is used to improve the safety of the operation of the distribution network.

[0004] To achieve the above object, the present application adopts the following technical solutions: In a first aspect, a power supply control method for a photovoltaic energy storage charging pile is provided, and the method includes: determining a state transition matrix P of a new energy vehicle t ; the state transition matrix P t = ; a11 represents the probability that a new energy vehicle in this area stays in the coverage area of the target vehicle charging pile at time t, represents the probability that a new energy vehicle in other areas drives into the coverage area of the target vehicle charging pile at time t; according to the state transition matrix, sampling is performed by the Monte Carlo method and the power consumption load curve of the target vehicle charging pile is calculated; the power consumption load curve is used to characterize the power consumption load at different times; according to the power consumption load curve of the target vehicle charging pile, a high load period of the target vehicle charging pile is determined, and during the high load period, an energy storage device is used to assist in power supply for the target vehicle charging pile; the high load period is a period when the load value is greater than the load threshold.

[0005] Optionally, determining the state transition matrix P of the new energy vehicle t , includes: determining according to the driving-in probability formula ; the driving-in probability formula satisfies the following relationship: =w*y; w represents the driving direction coefficient of the new energy vehicle; y represents the relevant distance coefficient; y is determined according to the relevant distance P and the first mapping relationship; P= ;Q represents the state of charge of the battery of the new energy vehicle; H represents the driving distance per unit state of charge; L represents the distance between the new energy vehicle and the target vehicle charging pile; the first mapping relationship includes the mapping relationship between different relevant distances and different relevant distance coefficients; it is determined according to the state of charge of the new energy vehicle and the second mapping relationship ; the second mapping relationship includes the mapping relationship between different states of charge of the battery and different state of charge coefficients; according to and determine the state transition matrix P t .

[0006] Optionally, according to the state transition matrix, use the Monte Carlo method to sample and calculate the power consumption load curve of the target vehicle charging pile, including: randomly select the initial state of the new energy vehicle; the initial state is the first initial state or the second initial state, the first initial state is used to indicate that the new energy vehicle is within the coverage area of the target vehicle charging pile; the second initial state is used to indicate that the new energy vehicle is outside the coverage area of the target vehicle charging pile; according to the initial state, determine the number of new energy vehicles within the coverage area of the target vehicle charging pile in the next time period according to the state transition matrix; according to the product of the number of new energy vehicles within the coverage area of the target vehicle charging pile in the next time period, the charging probability and the preset charging power, determine the initial power consumption load of the target vehicle charging pile in the next time period; repeat the above steps to obtain multiple initial power consumption loads of the target vehicle charging pile in the next time period, and determine the average value of the multiple initial power consumption loads as the predicted power consumption load of the target vehicle charging pile in the next time period to obtain the power consumption load curve.

[0007] Optionally, according to the power consumption load curve of the target vehicle charging pile, determine the high load period of the target vehicle charging pile, including: determine the health index of the power supply equipment according to the health index formula; the power supply equipment is the equipment used to supply power to the target vehicle charging pile; the health index formula satisfies the following relationship: ; wherein, represents the failure rate of the power supply equipment, HI represents the health index of the power supply equipment; K represents the preset proportional coefficient; C represents the preset curvature coefficient; in the case that the health index of the power supply equipment is greater than or equal to the health index threshold, determine the high load period of the target vehicle charging pile according to the power consumption load curve of the target vehicle charging pile.

[0008] Optionally, the method further includes: when the state of charge of the energy storage device is greater than or equal to the lower limit of the state of charge, use the energy storage device to assist in power supply for the target vehicle charging pile; when the state of charge of the energy storage device is less than the lower limit of the state of charge, stop using the energy storage device to assist in power supply for the target vehicle charging pile, and use the photovoltaic device or the power distribution network to charge the energy storage device.

[0009] Optionally, an energy storage device is used to assist in powering the target vehicle charging pile machine, including: sending an auxiliary power supply instruction to the energy storage device using a preset communication technology to use the energy storage device to assist in powering the target vehicle charging pile; the preset communication technology is a high-speed power line carrier communication HPLC technology, a high-speed wireless communication HRF technology, or a 5G technology.

[0010] Based on the technical solution provided in this application, by determining the state transition matrix P of the new energy vehicle t , the Monte Carlo method is used to sample and calculate the power consumption load curve of the target vehicle charging pile to determine the high-load period of the target vehicle charging pile, and during the high-load period, the energy storage device is used to assist in powering the vehicle charging pile machine. In this way, each charging pile can obtain an appropriate amount of power supply according to its actual demand, which can improve the use efficiency of power resources, reduce the random characteristics of the charging pile load, and improve the safety of the distribution network operation.

[0011] In a second aspect, a power supply control device is provided. The device includes: a determination unit and a processing unit; the determination unit is used to determine the state transition matrix P of the new energy vehicle t ; the state transition matrix P t = ; a11 represents the probability that the new energy vehicle in this area stays in the coverage area of the target vehicle charging pile at time t, represents the probability that the new energy vehicle in other areas drives into the coverage area of the target vehicle charging pile at time t; the processing unit is used to sample and calculate the power consumption load curve of the target vehicle charging pile using the Monte Carlo method according to the state transition matrix; the power consumption load curve is used to characterize the power consumption load at different times; the determination unit is further used to determine the high-load period of the target vehicle charging pile according to the power consumption load curve of the target vehicle charging pile, and during the high-load period, use the energy storage device to assist in powering the target vehicle charging pile machine; the high-load period is the period when the load value is greater than the load threshold.

[0012] Optionally, the determination unit is specifically used to: determine according to the driving-in probability formula; the driving-in probability formula satisfies the following relationship: = w * y; w represents the driving direction coefficient of the new energy vehicle; y represents the relevant distance coefficient; y is determined according to the relevant distance P and the first mapping relationship; P = ; Q represents the state of charge of the battery of the new energy vehicle; H represents the driving distance per unit charge; L represents the distance between the new energy vehicle and the target vehicle charging pile; the first mapping relationship includes the mapping relationship between different relevant distances and different relevant distance coefficients; determine ; The second mapping relationship includes the mapping relationship between different states of charge of the battery and different state-of-charge coefficients; according to and determine the state transition matrix P t .

[0013] Optionally, the processing unit is specifically configured to: randomly select the initial state of the new energy vehicle; the initial state is the first initial state or the second initial state, the first initial state is used to indicate that the new energy vehicle is within the coverage area of the target vehicle charging pile; the second initial state is used to indicate that the new energy vehicle is outside the coverage area of the target vehicle charging pile; according to the initial state, and in accordance with the state transition matrix, determine the number of new energy vehicles within the coverage area of the target vehicle charging pile in the next time period; according to the product of the number of new energy vehicles within the coverage area of the target vehicle charging pile in the next time period, the charging probability and the preset charging power, determine the initial power consumption load of the target vehicle charging pile in the next time period; repeat the above steps to obtain multiple initial power consumption loads of the target vehicle charging pile in the next time period, and determine the average value of the multiple initial power consumption loads as the predicted power consumption load of the target vehicle charging pile in the next time period, to obtain the power consumption load curve.

[0014] Optionally, the determining unit is specifically configured to: determine the health index of the power supply device according to the health index formula; the power supply device is the device used to supply power to the target vehicle charging pile; the health index formula satisfies the following relationship: ; wherein, represents the failure rate of the power supply device, HI represents the health index of the power supply device; K represents the preset proportionality coefficient; C represents the preset curvature coefficient; in the case where the health index of the power supply device is greater than or equal to the health index threshold, determine the high load period of the target vehicle charging pile according to the power consumption load curve of the target vehicle charging pile.

[0015] Optionally, the processing unit is further configured to, when the state of charge of the energy storage device is greater than or equal to the state-of-charge lower limit, use the energy storage device to assist in power supply for the target vehicle charging pile; when the state of charge of the energy storage device is less than the state-of-charge lower limit, stop using the energy storage device to assist in power supply for the target vehicle charging pile, and use the photovoltaic device or the power distribution network to charge the energy storage device.

[0016] Optionally, the determining unit is specifically further configured to: send an auxiliary power supply instruction to the energy storage device by using a preset communication technology, so as to use the energy storage device to assist in power supply for the target vehicle charging pile; the preset communication technology is the high-speed power line carrier communication HPLC technology, the high-speed wireless communication HRF technology, or the 5G technology.

[0017] In a third aspect, a power supply control device is provided. The power supply control device can implement the functions performed by the power supply control device in the above aspects or each possible design. The functions can be implemented by hardware. For example, in a possible design, the power supply control device may include a processor and a communication interface. The processor can be used to support the power supply control device to implement the functions involved in the above first aspect or any possible design of the first aspect.

[0018] In another possible design, the power supply control device may further include a memory for storing necessary computer execution instructions and data of the power supply control device. When the power supply control device runs, the processor executes the computer execution instructions stored in the memory, so that the power supply control device executes the above first aspect or any possible power supply control method of the first aspect.

[0019] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium can be a readable non-volatile storage medium. The computer-readable storage medium stores computer instructions or programs. When it runs on a computer, it enables the computer to execute the above first aspect or any possible power supply control method of the above aspect.

[0020] In a fifth aspect, a computer program product containing instructions is provided. When it runs on a computer, it enables the computer to execute the power supply control method of the above first aspect or any possible design of the above aspect.

[0021] In a sixth aspect, an electronic device is provided. The electronic device includes one or more processors and one or more memories. One or more memories are coupled to one or more processors. One or more memories are used to store computer program code. The computer program code includes computer instructions. When one or more processors execute the computer instructions, the electronic device executes the power supply control method of the above first aspect or any possible design of the first aspect.

[0022] In a seventh aspect, a chip system is provided. The chip system includes a processor and a communication interface. The chip system can be used to implement the functions performed by the power supply control device in the above first aspect or any possible design of the first aspect. In a possible design, the chip system further includes a memory for storing program instructions and / or data. The chip system can be composed of chips or can include chips and other discrete devices, without limitation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic flowchart of a power supply control method provided by an embodiment of the present application; Figure 2Schematic flowchart of another power supply control method provided by an embodiment of the present application; Figure 3 Schematic structural diagram of a power supply control device provided by an embodiment of the present application. Detailed implementation manners

[0024] To enable those of ordinary skill in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0026] It should also be understood that the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, and / or components.

[0027] With the continuous increase in the number of new energy vehicles, the charging demand for new energy vehicles has gradually increased. The time, location, and power of new energy vehicles to choose for charging are uncertain, resulting in the charging load being highly intermittent and random. In particular, the instantaneous power of the charging load generated by the fast charging mode is greater, and the selection of charging time and location is more random, bringing risks and challenges to the safe operation of the distribution network.

[0028] In view of this, an embodiment of the present application provides a power supply control method, including: determining the state transition matrix P of a new energy vehicle t ; according to the state transition matrix, sampling by the Monte Carlo method and calculating the power consumption load curve of the target vehicle charging pile; the power consumption load curve is used to characterize the power consumption load at different times, and according to the power consumption load curve of the target vehicle charging pile, determining the high load period of the target vehicle charging pile, and during the high load period, using the energy storage device to assist in power supply for the vehicle charging pile.

[0029] The method provided by the embodiment of the present application will be described in detail below with reference to the accompanying drawings of the specification.

[0030] Figure 1 Schematic flowchart of a power supply control method provided by an embodiment of the present application, as Figure 1As shown, the method includes the following S301 - S303: S301. Determine the state transition matrix P of the new energy vehicle t .

[0031] Among them, the state transition matrix P t = .

[0032] a11 represents the probability that the new energy vehicle in this area at time t stays in the coverage area of the target vehicle charging pile, represents the probability that the new energy vehicle in other areas at time t drives into the coverage area of the target vehicle charging pile.

[0033] As a possible implementation manner, the power supply control device can determine according to the driving - in probability formula, determine according to the state of charge of the new energy vehicle and the second mapping relationship, and then determine the state transition matrix P according to and . t .

[0034] It should be noted that, = w * y.

[0035] w represents the driving - direction coefficient of the new energy vehicle; y represents the relevant - distance coefficient; y is determined according to the relevant distance P and the first mapping relationship; P = ; Q represents the state of charge of the new energy vehicle; H represents the driving distance per unit charge; L represents the distance between the new energy vehicle and the target vehicle charging pile; the first mapping relationship includes the mapping relationship between different relevant distances and different relevant - distance coefficients.

[0036] For example, the first mapping relationship can be represented by Table 1 below: Table 1 First mapping relationship

[0037] It should be noted that Table 1 is only an exemplary illustration, and the first mapping relationship may also include other data, without limitation.

[0038] Furthermore, the power supply control device can determine according to the state of charge of the new energy vehicle and the second mapping relationship.

[0039] Among them, the second mapping relationship includes the mapping relationship between different states of charge and different charge - state coefficients.

[0040] For example, the second mapping relationship can be represented by Table 2 below: Table 2 Second mapping relationship

[0041] It should be noted that Table 2 is only for illustrative purposes, and the second mapping relationship may also include other data, without limitation.

[0042] S302. According to the state transition matrix, use the Monte Carlo method to sample and calculate the power consumption load curve of the target electric vehicle charging pile.

[0043] Among them, the power consumption load curve is used to characterize the power consumption load at different times.

[0044] As a possible implementation, the power supply control device can determine the power consumption load curve of the target electric vehicle charging pile according to the following S1 - S4.

[0045] S1. Randomly select the initial state of the new energy vehicle.

[0046] Among them, the initial state is the first initial state or the second initial state. The first initial state is used to indicate that the new energy vehicle is within the coverage area of the target electric vehicle charging pile; the second initial state is used to indicate that the new energy vehicle is outside the coverage area of the target electric vehicle charging pile.

[0047] S2. According to the initial state, and in accordance with the state transition matrix, determine the number of new energy vehicles within the coverage area of the target electric vehicle charging pile in the next time period.

[0048] In one example, the power supply control device can determine the number of new energy vehicles within the coverage area of the target electric vehicle charging pile in the next time period according to the quantity determination formula.

[0049] The quantity determination formula satisfies the following relationship: S = S1 * a11 + S2 * a21.

[0050] Among them, S represents the number of new energy vehicles within the coverage area of the target electric vehicle charging pile in the next time period. S1 represents the number of new energy vehicles in the current area (i.e., the coverage area of the target electric vehicle charging pile); S2 represents the number of new energy vehicles in other areas in the current time period (i.e., outside the coverage area of the target electric vehicle charging pile).

[0051] S3. According to the product of the number of new energy vehicles within the coverage area of the target electric vehicle charging pile in the next time period, the charging probability, and the preset charging power, determine the initial power consumption load of the target electric vehicle charging pile in the next time period.

[0052] Among them, the preset charging power can be set in advance. The charging probability within a day is obtained by pre - statistics, and the charging probability satisfies the normal distribution at different times within a day. The power supply control device can determine the time period of the day at time t and determine the charging probability.

[0053] S4. Repeat the above steps to obtain multiple initial power consumption loads of the target electric vehicle charging pile in the next time period, and determine the average value of the multiple initial power consumption loads as the predicted power consumption load of the target electric vehicle charging pile in the next time period, thereby obtaining the power consumption load curve.

[0054] For example, the power supply control device can repeat the above steps until the convergence condition of the Monte Carlo method is met. Obtain multiple initial power consumption loads of the target electric vehicle charging pile in the next time period, and determine the average value of the multiple initial power consumption loads as the predicted power consumption load of the target electric vehicle charging pile in the next time period, thereby obtaining the power consumption load curve.

[0055] As another possible implementation, the power supply control device can discretize the vehicle's daily driving into a Markov random process to statistically obtain the vehicle's transition matrix, realize the travel chain of the vehicle during a day's journey, perform probability sampling on the distributions of various relevant data that have been statistically obtained, and establish a model of the charging load based on the charging hypothesis to determine the power consumption load curve of the target electric vehicle charging pile.

[0056] Suppose there are n vehicles, all starting from home, and the initial state of charge (SOC) of the vehicles 0 obeys a uniform distribution U(0.91, 1), the departure time T 0 , the end time T e , the driving time T ij and the driving distance S ij are independent of each other, where i represents the vehicle number and j represents the jth section of the journey. The entire driving process satisfies the Markov random process hypothesis. Obtain the driving direction determined based on the transition matrix, randomly select a journey and record the power consumption through fuzzy calculation, perform charging calculation according to the next journey, superimpose and accumulate the loads of the entire process in terms of time and location, and finally complete the vehicle i's full-day travel according to the journey end time rule. After n vehicles are completed, perform N times of Monte Carlo repeated sampling to establish a charging load model to determine the power consumption load curve of the target electric vehicle charging pile.

[0057] S303. According to the power consumption load curve of the target electric vehicle charging pile, determine the high-load time period of the target electric vehicle charging pile, and use the energy storage device to assist in power supply for the target electric vehicle charging pile during the high-load time period.

[0058] Among them, the high-load time period is the time period when the load value is greater than the load threshold. The load threshold can be set as needed.

[0059] As a possible implementation, the power supply control device can use a preset communication technology to send an auxiliary power supply instruction to the energy storage device to use the energy storage device to assist in power supply for the target electric vehicle charging pile.

[0060] The preset communication technologies are high-speed power line carrier communication (HPLC) technology, high-speed radio frequency (HRF) communication technology, and 5G technology.

[0061] In some embodiments, the power supply control device can use the energy storage device to assist in power supply for the target vehicle charging pile when the state of charge (SOC) of the energy storage device is greater than or equal to the lower limit of the SOC.

[0062] In addition, when the SOC of the energy storage device is less than the lower limit of the SOC, the power supply control device can stop using the energy storage device to assist in power supply for the target vehicle charging pile and use the photovoltaic device or the power distribution network to charge the energy storage device.

[0063] The lower limit of the SOC can be set as needed. For example, it can be 20% or the like.

[0064] In some embodiments, the power supply control device can determine the active / reactive power scheduling scheme of the photovoltaic device and the energy storage device by establishing a stochastic-robust hybrid optimization scheduling model.

[0065] Based on the technical solution provided in this application, by determining the state transition matrix P of the new energy vehicle t , the Monte Carlo method is used for sampling and calculating the power consumption load curve of the target vehicle charging pile to determine the high-load period of the target vehicle charging pile, and during the high-load period, the energy storage device is used to assist in power supply for the vehicle charging pile. In this way, each charging pile can obtain an appropriate amount of power supply according to its actual demand, which can improve the utilization efficiency of power resources, reduce the random characteristics of the charging pile load, and improve the safety of the power distribution network operation.

[0066] A possible embodiment Figure 2 is a schematic flowchart of another power supply control method provided in the embodiments of this application. As Figure 2 shown, this application may further include the following S401 - S402.

[0067] S401. Determine the health index of the power supply device according to the health index formula.

[0068] Wherein, the power supply device is the device used to supply power to the target vehicle charging pile.

[0069] The health index formula satisfies the following relationship: ;

[0070] Wherein, represents the failure rate of the power supply device, HI represents the health index of the power supply device; K represents a preset proportionality coefficient; C represents a preset curvature coefficient.

[0071] S402. When the health index of the power supply device is greater than or equal to the health index threshold, determine the high-load period of the target electric vehicle charging pile according to the power consumption load curve of the target electric vehicle charging pile.

[0072] Among them, the health index threshold can be set as needed and is not limited here.

[0073] The embodiments of the present application can divide the power supply control device into function modules or functional units according to the above method examples. For example, each function can correspond to the division of each function module or functional unit, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of a software function module or functional unit. Among them, the division of modules or units in the embodiments of the present application is schematic, only a logical function division, and there can be other division methods in actual implementation.

[0074] In the case of dividing each function module according to each function, Figure 3 FIG. shows a schematic structural diagram of another power supply control device 500. The power supply control device 500 can also be a chip, a processor, etc. applied to the power supply control device. The power supply control device 500 can be used to execute the functions of the power supply control device involved in the above embodiments. Figure 3 The shown power supply control device 500 may include: a determination unit 501 and a processing unit 502; the determination unit 501 is used to determine the state transition matrix P of the new energy vehicle t ; the state transition matrix P t = ; a11 represents the probability that the new energy vehicle in this area stays in the coverage area of the target electric vehicle charging pile at time t, represents the probability that the new energy vehicle in other areas drives into the coverage area of the target electric vehicle charging pile at time t; the processing unit 502 is used to sample and calculate the power consumption load curve of the target electric vehicle charging pile according to the state transition matrix by using the Monte Carlo method; the power consumption load curve is used to characterize the power consumption load at different times; the determination unit 501 is further used to determine the high-load period of the target electric vehicle charging pile according to the power consumption load curve of the target electric vehicle charging pile, and during the high-load period, use the energy storage device to assist in power supply for the target electric vehicle charging pile machine; the high-load period is the period when the load value is greater than the load threshold.

[0075] Optionally, the determination unit 501 is specifically used to: determine according to the driving-in probability formula ; the driving-in probability formula satisfies the following relationship: =w*y; w represents the driving direction coefficient of the new energy vehicle; y represents the relevant distance coefficient; y is determined according to the relevant distance P and the first mapping relationship; P= ;Q represents the state of charge of the new energy vehicle's battery; H represents the driving distance per unit of charge; L represents the distance between the new energy vehicle and the target vehicle charging pile; the first mapping relationship includes the mapping relationship between different relevant distances and different relevant distance coefficients; determine according to the state of charge of the new energy vehicle and the second mapping relationship ; the second mapping relationship includes the mapping relationship between different states of charge and different state-of-charge coefficients; according to and determine the state transition matrix P t .

[0076] Optionally, the processing unit 502 is specifically configured to: randomly select the initial state of the new energy vehicle; the initial state is the first initial state or the second initial state, the first initial state is used to indicate that the new energy vehicle is within the coverage area of the target vehicle charging pile; the second initial state is used to indicate that the new energy vehicle is outside the coverage area of the target vehicle charging pile; according to the initial state, determine the number of new energy vehicles within the coverage area of the target vehicle charging pile in the next time period according to the state transition matrix; according to the product of the number of new energy vehicles within the coverage area of the target vehicle charging pile in the next time period, the charging probability and the preset charging power, determine the initial power consumption load of the target vehicle charging pile in the next time period; repeat the above steps to obtain multiple initial power consumption loads of the target vehicle charging pile in the next time period, and determine the average value of the multiple initial power consumption loads as the predicted power consumption load of the target vehicle charging pile in the next time period, and obtain the power consumption load curve.

[0077] Optionally, the determining unit 501 is specifically configured to: determine the health index of the power supply device according to the health index formula; the power supply device is a device used to supply power to the target vehicle charging pile; the health index formula satisfies the following relationship: ;

[0078] wherein, represents the failure rate of the power supply device, HI represents the health index of the power supply device; K represents a preset proportionality coefficient; C represents a preset curvature coefficient; in the case that the health index of the power supply device is greater than or equal to the health index threshold, determine the high load period of the target vehicle charging pile according to the power consumption load curve of the target vehicle charging pile.

[0079] Optionally, the processing unit 502 is further configured to, when the state of charge of the energy storage device is greater than or equal to the lower limit of the state of charge, use the energy storage device to assist in power supply for the target vehicle charging pile; when the state of charge of the energy storage device is less than the lower limit of the state of charge, stop using the energy storage device to assist in power supply for the target vehicle charging pile, and use the photovoltaic device or the power distribution network to charge the energy storage device.

[0080] Optionally, the determination unit 501 is further configured to: send an auxiliary power supply instruction to the energy storage device by using a preset communication technology, so as to use the energy storage device to perform auxiliary power supply for the target vehicle charging pile; the preset communication technology is a high-speed power line carrier communication HPLC technology, a high-speed wireless communication HRF technology, or a 5G technology.

[0081] The embodiment of the present application further provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be completed by a computer program instructing relevant hardware. The program can be stored in the above computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be an internal storage unit of any one of the foregoing power supply control devices (including a data sending end and / or a data receiving end), such as a hard disk or a memory of the power supply control device. The above computer-readable storage medium can also be an external storage device of the above terminal device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the above terminal device. Further, the above computer-readable storage medium can also include both the internal storage unit of the above power supply control device and the external storage device. The above computer-readable storage medium is used to store the above computer program and other programs and data required by the above power supply control device. The above computer-readable storage medium can also be used to temporarily store data that has been output or is to be output.

[0082] It should be noted that the terms "first" and "second" in the specification, claims and drawings of the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0083] It should be understood that in this application, "at least one (item)" means one or more, "a plurality" means two or more, "at least two (items)" means two, three or more, and "and / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (individual) of the following" or its similar expression means any combination of these items, including any combination of single item (individual) or plural items (individuals). For example, at least one (individual) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a, b, and c", where a, b, and c can be single or multiple.

[0084] Through the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be allocated to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0085] In several embodiments provided in this application, it should be understood that the disclosed device and method can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical or other forms.

[0086] The unit described as a separated component may or may not be physically separated. The component displayed as a unit may be a physical unit or multiple physical units, that is, it may be located in one place, or it may be distributed to multiple different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional unit in various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0088] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods of the embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0089] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A power supply control method for a photovoltaic energy storage charging pile, characterized in that: The method comprises: Determine the state transfer matrix P of the new energy vehicle t ; The state transfer matrix P t = ; a11 represents the probability that the new energy vehicles in this area stay in the coverage area of ​​the target vehicle charging pile at time t, The probability that new energy vehicles in other areas enter the coverage area of ​​the target vehicle charging pile at time t; According to the state transfer matrix, a Monte Carlo method is used to sample and calculate the power load curve of the target vehicle charging pile; the power load curve is used to characterize the power load at different times; According to the power load curve of the target automobile charging pile, the high load period of the target automobile charging pile is determined, and during the high load period, the energy storage device is used to provide auxiliary power supply for the target automobile charging pile; the high load period is a period when the load value is greater than the load threshold.

2. The method according to claim 1, characterized in that: Determine the state transfer matrix P of the new energy vehicle t ,include: Determined by the driving probability formula ; The entry probability formula satisfies the following relationship: =w*y; w represents the driving direction coefficient of the new energy vehicle; y represents the relevant distance coefficient; y is determined according to the relevant distance P and the first mapping relationship; P= ;Q represents the battery charge state of the new energy vehicle; H represents the driving distance per unit charge; L represents the distance between the new energy vehicle and the target vehicle charging pile; the first mapping relationship includes the mapping relationship between different related distances and different related distance coefficients; Determine according to the battery charge state of the new energy vehicle and the second mapping relationship ; The second mapping relationship includes a mapping relationship between different battery states of charge and different state of charge coefficients; according to and Determine the state transfer matrix P t .

3. The method according to claim 1, characterized in that The method of sampling and calculating the power load curve of the target vehicle charging pile by using the Monte Carlo method according to the state transfer matrix includes: Randomly select the initial state of the new energy vehicle; the initial state is a first initial state or a second initial state, the first initial state is used to indicate that the new energy vehicle is within the coverage area of ​​the target vehicle charging pile; the second initial state is used to indicate that the new energy vehicle is outside the coverage area of ​​the target vehicle charging pile; According to the initial state and the state transfer matrix, determining the number of new energy vehicles within the coverage area of ​​the target vehicle charging pile in the next period; Determine the initial power load of the target vehicle charging pile in the next period according to the number of new energy vehicles within the coverage area of ​​the target vehicle charging pile in the next period, the product of the charging probability and the preset charging power; Repeat the above steps to obtain multiple initial power loads of the target vehicle charging pile in the next time period, and determine the average of the multiple initial power loads as the predicted power load of the target vehicle charging pile in the next time period to obtain the power load curve.

4. The method according to claim 1, characterized in that: The step of determining the high load period of the target vehicle charging pile according to the power load curve of the target vehicle charging pile comprises: Determine the health index of the power supply equipment according to the health index formula; the power supply equipment is a device used to supply power to the target vehicle charging pile; The health index formula satisfies the following relationship: ； in, represents the failure rate of the power supply device, HI represents the health index of the power supply device; K represents the preset proportional coefficient; C represents the preset curvature coefficient; When the health index of the power supply equipment is greater than or equal to a health index threshold, a high-load period of the target vehicle charging pile is determined according to the power load curve of the target vehicle charging pile.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: When the state of charge of the battery of the energy storage device is greater than or equal to the lower limit of the state of charge, using the energy storage device to provide auxiliary power supply for the target vehicle charging pile machine; When the battery state of charge of the energy storage device is less than the lower limit of the state of charge, stop using the energy storage device to provide auxiliary power supply to the target vehicle charging pile machine, and use photovoltaic equipment or distribution network to charge the energy storage device.

6. The method according to claim 1, characterized in that The method of using the energy storage device to provide auxiliary power supply for the target vehicle charging pile machine includes: An auxiliary power supply instruction is sent to the energy storage device using a preset communication technology, so as to use the energy storage device to provide auxiliary power supply for the target vehicle charging pile; the preset communication technology is high-speed power line carrier communication HPLC technology, high-speed wireless communication HRF technology, and 5G technology.

7. A power supply control device, characterized in that: The device comprises: a determination unit and a processing unit; The determining unit is used to determine the state transfer matrix P of the new energy vehicle. t ; The state transfer matrix P t = ; a11 represents the probability that the new energy vehicles in this area stay in the coverage area of ​​the target vehicle charging pile at time t, The probability that new energy vehicles in other areas enter the coverage area of ​​the target vehicle charging pile at time t; The processing unit is used to sample and calculate the power load curve of the target vehicle charging pile using the Monte Carlo method according to the state transfer matrix; the power load curve is used to characterize the power load at different times; The determination unit is further used to determine the high-load period of the target vehicle charging pile according to the power load curve of the target vehicle charging pile, and to use the energy storage device to provide auxiliary power supply for the target vehicle charging pile during the high-load period; the high-load period is a period when the load value is greater than the load threshold.

8. A computer-readable storage medium, characterized in that: The readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 6 is implemented.

9. An electronic device, characterized in that: include: A processor, a memory and a communication interface; wherein the communication interface is used for the electronic device to communicate with other devices or networks; The memory is used to store one or more programs, which include computer-executable instructions. When the electronic device is running, the processor executes the computer-executable instructions stored in the memory to enable the electronic device to perform the method described in any one of claims 1-6.

10. A computer program product, comprising computer instructions, characterized in that: When the computer instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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