Photovoltaic energy storage intelligent management method and device

Abstract

The invention relates to the technical field of photovoltaic energy storage charging, and particularly provides a photovoltaic energy storage intelligent management method and device, and the method comprises the steps: querying a pre-constructed mapping relation table about the power grid electricity price and a discharge depth coefficient according to the real-time electricity price information of a power grid, so as to obtain a first discharge depth coefficient, under the condition that the residual electricity storage quantity information is greater than or equal to a preset electricity storage quantity lower limit value, calculating the maximum discharge quantity according to the electricity storage quantity information and a first discharge depth coefficient; controlling the energy storage assembly to supply power to the charging pile according to the charging power demand until the discharge capacity of the energy storage assembly reaches the maximum discharge capacity or the charging power demand is reduced to 0; when the discharge capacity of the energy storage assembly reaches the maximum discharge capacity and the charging power demand is not zero, the commercial power supply adjusting assembly is controlled to supply power to the charging pile according to the charging power demand; according to the method, the discharge capacity of the energy storage assembly in the peak period of electricity price can be increased, and the situation of deep discharge of the energy storage assembly is avoided.

Description

Technical Field

[0001] This application relates to the technical field of photovoltaic energy storage charging, and in particular, to a photovoltaic energy storage intelligent management method and device. Background Art

[0002] In the operation practice of urban electric vehicle charging stations, reducing operation costs is a crucial goal. To achieve this goal, existing electric vehicle charging stations usually are equipped with energy storage batteries to store the electricity generated by photovoltaic power generation systems. In the operation strategy of the charging station, it is usually preferred to use the energy storage battery to supply power to the charging piles, so as to reduce the electricity purchase amount of the charging station from the power grid, thereby directly reducing the electricity bill expenditure. However, there is a significant problem in actual operation, that is, the peak electricity consumption period of the charging station often highly coincides with the peak period of the power grid electricity price (for example, the common 7 pm to 9 pm). Although the existing technical solutions tend to give priority to using the energy storage battery to supply power to the charging piles, in the evening period, especially from 5 pm to 7 pm when the power generation amount of the photovoltaic power generation system is low or even zero, if the charging station faces a large number of electric vehicle charging demands, it is very likely that the stored electricity of the energy storage battery will be completely exhausted before the real arrival of the peak electricity price period. In this case, even during the peak electricity price period, the charging station loses the power support of the energy storage battery and has to turn to purchase high-price electricity from the power grid. Thus, it can be seen that due to the excessive reliance on the priority power supply strategy of the energy storage battery, the existing technical solutions may instead cause the electricity of the energy storage battery to be exhausted before the peak electricity price period, and ultimately still need to purchase electricity from the power grid during the peak electricity price period, which greatly reduces the effect of reducing operation costs by using the energy storage battery and limits the achievement of reducing operation costs. A further problem is that in order to maximize economic benefits, the existing technical solutions may drive the energy storage battery to perform deep discharges frequently. However, the frequent deep discharge operation of the energy storage battery will accelerate the attenuation process of the battery and significantly shorten the service life of the energy storage battery, which not only increases the replacement cost of the energy storage battery but also further restricts the continuous improvement of the operation cost reduction effect in the long term.

[0003] In response to the above problems, there is currently no effective technical solution. It should be noted that the above information disclosed in this part is only used to understand the background of the inventive concept of the present invention, and thus may include information that does not constitute the prior art. Summary of the Invention

[0004] The purpose of this application is to provide a photovoltaic energy storage intelligent management method and device, which can increase the discharge amount of the energy storage component during the peak electricity price period and avoid the occurrence of deep discharge of the energy storage component.

[0005] In a first aspect, the present application provides a photovoltaic energy storage intelligent management method, which is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component, and a mains power supply regulation component. The energy storage component is used to store the electric energy generated by a photovoltaic power generation component. The photovoltaic energy storage intelligent management method includes the following steps: S1. Obtain the stored electricity information of the energy storage component, the charging power demand of the charging pile, and the real-time grid electricity price information; S2. Query a pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain a first discharge depth coefficient, and calculate the maximum discharge amount according to the stored electricity information and the first discharge depth coefficient when the remaining stored electricity information is greater than or equal to a preset lower limit value of stored electricity. The first discharge depth coefficient is positively correlated with the real-time grid electricity price information; S3. Control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand drops to 0; S4. When the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0, control the mains power supply regulation component to supply power to the charging pile according to the charging power demand.

[0006] The photovoltaic energy storage intelligent management method provided by the present application can obtain a first discharge depth coefficient associated with the real-time grid electricity price information, and calculate the maximum discharge amount according to the stored electricity information and the first discharge depth coefficient when the remaining stored electricity information is greater than or equal to a preset lower limit value of stored electricity. Since the first discharge depth coefficient is positively correlated with the real-time grid electricity price information, that is, the present application can effectively retain the available discharge amount of the energy storage component by reducing the discharge amount of the energy storage component during the low electricity price period to increase the discharge amount of the energy storage component during the high electricity price period. Therefore, the present application can effectively solve the problem that the effect of reducing the operating cost by the energy storage system is limited due to the exhaustion of the electricity of the energy storage battery before the high electricity price period, that is, the present application can effectively improve the effect of reducing the operating cost. And since the maximum discharge amount of the present application is calculated when the remaining stored electricity information is greater than or equal to a preset lower limit value of stored electricity, that is, the present application can avoid the situation of deep discharge of the energy storage component. Therefore, the present application can effectively solve the problem that the energy storage battery is accelerated to decay due to frequent deep discharge of the energy storage battery, and the service life of the energy storage battery is significantly shortened, thereby effectively reducing the replacement cost of the energy storage battery and further improving the effect of reducing the operating cost.

[0007] Optionally, step S2 includes: S21. Query a pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain a first discharge depth coefficient; S22. Input the historical charge and discharge data of the energy storage component into a pre-trained health state evaluation model of the energy storage component to obtain a health state score; S23. Query a pre-constructed mapping relation table between the health state score and the discharge depth coefficient according to the health state score to obtain a second discharge depth coefficient; S24. Calculate a preliminary discharge amount based on the stored electricity information, the first discharge depth coefficient, and the second discharge depth coefficient, and then calculate the remaining electricity information based on the stored electricity information and the preliminary discharge amount; S25. Analyze whether the remaining electricity information is greater than or equal to a preset lower limit value of the stored electricity. If so, use the preliminary discharge amount as the maximum discharge amount. If not, reduce the preliminary discharge amount until the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity, and use the reduced preliminary discharge amount as the maximum discharge amount.

[0008] Optionally, step S24 includes: S241. Obtain environmental temperature information, and query a pre-constructed mapping relation table between the environmental temperature and the discharge depth coefficient according to the environmental temperature information to obtain a third discharge depth coefficient; S242. Calculate a preliminary discharge amount based on the stored electricity information, the first discharge depth coefficient, the second discharge depth coefficient, and the third discharge depth coefficient, and then calculate the remaining electricity information based on the stored electricity information and the preliminary discharge amount.

[0009] Optionally, step S25 includes: S251. Query a pre-constructed mapping relation table between the health state score, the environmental temperature, and the lower limit value of the stored electricity according to the health state score and the environmental temperature information to obtain a preset lower limit value of the stored electricity; S252. Analyze whether the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity. If so, use the preliminary discharge amount as the maximum discharge amount. If not, reduce the preliminary discharge amount until the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity, and use the reduced preliminary discharge amount as the maximum discharge amount.

[0010] Optionally, the photovoltaic power generation component is also electrically connected to a charging pile, and step S3 includes: S31. Obtain the power generation power information of the photovoltaic power generation component, and analyze whether the power generation power information is greater than or equal to the charging power demand. If so, control the photovoltaic power generation component to supply power to the charging pile, and when the power generation power information is greater than the charging power demand and the stored electricity information has not reached the preset upper limit value of the stored electricity, control the photovoltaic power generation component to charge the energy storage component with the difference between the power generation power information and the charging power demand. If not, execute step S32 or step S33; S32. When the power generation power information is 0, control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand decreases to 0. S33. When the power generation power information is not 0, control the photovoltaic power generation component to supply power to the charging pile at the power generation power information, and control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand decreases to 0.

[0011] Optionally, step S32 includes: S321. When the power generation power information is 0, analyze whether the real-time grid electricity price information is less than or equal to the first preset threshold. If so, control the mains supply regulation component to supply power to the charging pile according to the charging power demand. If not, control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand decreases to 0. Step S33 includes: S331. When the power generation power information is not 0, analyze whether the real-time grid electricity price information is less than or equal to the first preset threshold. If so, control the photovoltaic power generation component to supply power to the charging pile at the power generation power information, and control the mains supply regulation component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information. If not, control the photovoltaic power generation component to supply power to the charging pile at the power generation power information, and control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand decreases to 0.

[0012] Optionally, the step of controlling the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information includes: A1. Analyze whether the difference between the charging power demand and the power generation power information is greater than the power supply upper limit value of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the power supply upper limit value, and control the mains supply regulation component to supply power to the charging pile according to the difference between the difference between the charging power demand and the power generation power information and the power supply upper limit value. If not, control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information. The step of controlling the energy storage component to supply power to the charging pile according to the charging power demand includes: B1. Analyze whether the charging power demand is greater than the power supply upper limit value of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the power supply upper limit value, and control the mains supply regulation component to supply power to the charging pile according to the difference between the charging power demand and the power supply upper limit value. If not, control the energy storage component to supply power to the charging pile according to the charging power demand.

[0013] Optionally, the upper limit value of the power supply is determined based on the health status score of the energy storage component and the ambient temperature information.

[0014] Optionally, the photovoltaic energy storage intelligent management method further includes the steps of: S5. When the power generation power information is 0, the real-time grid electricity price information is less than or equal to the second preset threshold, and the stored electricity quantity information has not reached the preset upper limit value of the stored electricity quantity, control the mains power supply regulation component to charge the energy storage component.

[0015] In a second aspect, the present application further provides a photovoltaic energy storage intelligent management device, which is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component, and a mains power supply regulation component. The energy storage component is used to store the electric energy generated by the photovoltaic power generation component. The photovoltaic energy storage intelligent management device includes: An information acquisition module, configured to acquire the stored electricity quantity information of the energy storage component, the charging power demand of the charging pile, and the real-time grid electricity price information; A maximum discharge amount acquisition module, configured to query a pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain a first discharge depth coefficient, and calculate the maximum discharge amount according to the stored electricity quantity information and the first discharge depth coefficient when the remaining stored electricity quantity information is greater than or equal to the preset lower limit value of the stored electricity quantity. The first discharge depth coefficient is positively correlated with the real-time grid electricity price information; A first power supply module, configured to control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0; A second power supply module, configured to control the mains power supply regulation component to supply power to the charging pile according to the charging power demand when the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0.

[0016] The present application provides a photovoltaic energy storage intelligent management device, which can obtain a first depth of discharge coefficient associated with the real-time grid electricity price information, and calculate the maximum discharge amount according to the stored electricity amount information and the first depth of discharge coefficient when the remaining stored electricity amount information is greater than or equal to the preset lower limit value of the stored electricity amount. Since the first depth of discharge coefficient is positively correlated with the real-time grid electricity price information, that is, the present application can effectively retain the available discharge amount of the energy storage component by reducing the discharge amount of the energy storage component during the low electricity price period, so as to increase the discharge amount of the energy storage component during the high electricity price period. Therefore, the present application can effectively solve the problem that the effect of reducing the operating cost through the energy storage system is limited due to the exhaustion of the electricity amount of the energy storage battery before the high electricity price period, that is, the present application can effectively improve the effect of reducing the operating cost. And since the maximum discharge amount of the present application is calculated when the remaining stored electricity amount information is greater than or equal to the preset lower limit value of the stored electricity amount, that is, the present application can avoid the situation of deep discharge of the energy storage component. Therefore, the present application can effectively solve the problem that the energy storage battery is accelerated to decay and the service life of the energy storage battery is significantly shortened due to the frequent deep discharge of the energy storage battery, thereby effectively reducing the replacement cost of the energy storage battery and further improving the effect of reducing the operating cost.

[0017] As can be seen from the above, the present application provides a photovoltaic energy storage intelligent management method and device, which can obtain a first depth of discharge coefficient associated with the real-time grid electricity price information, and calculate the maximum discharge amount according to the stored electricity amount information and the first depth of discharge coefficient when the remaining stored electricity amount information is greater than or equal to the preset lower limit value of the stored electricity amount. Since the first depth of discharge coefficient is positively correlated with the real-time grid electricity price information, that is, the present application can effectively retain the available discharge amount of the energy storage component by reducing the discharge amount of the energy storage component during the low electricity price period, so as to increase the discharge amount of the energy storage component during the high electricity price period. Therefore, the present application can effectively solve the problem that the effect of reducing the operating cost through the energy storage system is limited due to the exhaustion of the electricity amount of the energy storage battery before the high electricity price period, that is, the present application can effectively improve the effect of reducing the operating cost. And since the maximum discharge amount of the present application is calculated when the remaining stored electricity amount information is greater than or equal to the preset lower limit value of the stored electricity amount, that is, the present application can avoid the situation of deep discharge of the energy storage component. Therefore, the present application can effectively solve the problem that the energy storage battery is accelerated to decay and the service life of the energy storage battery is significantly shortened due to the frequent deep discharge of the energy storage battery, thereby effectively reducing the replacement cost of the energy storage battery and further improving the effect of reducing the operating cost. Brief Description of the Drawings

[0018] Figure 1 It is a flowchart of a photovoltaic energy storage intelligent management method provided by an embodiment of the present application.

[0019] Figure 2 This is a schematic structural diagram of a photovoltaic energy storage intelligent management device provided by an embodiment of the present application.

[0020] Reference numerals: 1, information acquisition module; 2, maximum discharge amount acquisition module; 3, first power supply module; 4, second power supply module. Specific embodiments

[0021] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Usually, the components of the embodiments of the present application described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0022] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions, and cannot be understood as indicating or implying relative importance.

[0023] In a first aspect, the present application provides a photovoltaic energy storage intelligent management method, which is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component, and a mains power supply regulation component. The energy storage component is used to store the electric energy generated by the photovoltaic power generation component. The photovoltaic energy storage intelligent management method includes the following steps: S1. Obtain the stored electricity information of the energy storage component, the charging power demand of the charging pile, and the real-time grid electricity price information; S2. Query a pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain a first discharge depth coefficient, and calculate the maximum discharge amount according to the stored electricity information and the first discharge depth coefficient when the remaining stored electricity information is greater than or equal to a preset lower limit value of stored electricity. The first discharge depth coefficient is positively correlated with the real-time grid electricity price information; S3. Control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0; S4. When the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0, control the mains power supply regulation component to supply power to the charging pile according to the charging power demand.

[0024] Among them, the photovoltaic energy storage intelligent management method provided by this embodiment is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component, and a mains power supply regulation component. The charging pile can be an existing fast charging pile or slow charging pile, and the number of charging piles is multiple, that is, the electric vehicle charging station of this embodiment can charge multiple electric vehicles simultaneously. The energy storage component of this embodiment is preferably an existing energy storage battery, and the mains power supply regulation component of this embodiment can be existing power electronic devices such as a transformer or an inverter. The mains power supply regulation component is used to convert the mains power into the voltage and current required by the charging pile, and the mains power supply regulation component can also adjust the magnitude of the power supplied to the charging pile.

[0025] The stored electricity amount information in step S1 can be the information output by the energy storage component, and the stored electricity amount information can also be obtained by real-time collection through an electricity sensor or a communication interface. This embodiment can also obtain the stored electricity amount information by multiplying the state of charge of the energy storage component by the maximum capacity of the energy storage component. The state of charge is the percentage of the current available capacity of the energy storage component to the fully charged state capacity, and the state of charge is preferably output by the energy storage component. The charging power demand in step S1 is the sum of the charging powers of all the charging piles in the electric vehicle charging station. The charging power can be output by the charging pile, and the charging power can also be obtained by real-time collection through a power sensor. The real-time grid electricity price information of this embodiment is the electricity price at the current time period. Since the power supply bureau configures different electricity prices for different time periods, that is, the power supply bureau has pre-constructed a mapping relationship table between time and electricity price, this embodiment can obtain the real-time grid electricity price information by querying this mapping relationship table using the current time.

[0026] The pre-constructed mapping relationship table between the grid electricity price and the depth of discharge coefficient in step S2 is configured to be stored in a local database or a cloud server. The mapping relationship table reflects the positive correlation between the grid electricity price and the depth of discharge coefficient. Specifically, the higher the grid electricity price, the larger the depth of discharge coefficient indicated by the mapping relationship table, so as to allow the energy storage component to discharge more electricity. For example, the pre-constructed mapping relationship table between the grid electricity price and the depth of discharge coefficient is set as follows: when the grid electricity price is less than or equal to 0.6 yuan / kWh, the depth of discharge coefficient is set to 0.2; when the grid electricity price is greater than 0.6 yuan / kWh and less than or equal to 0.9 yuan / kWh, the depth of discharge coefficient is set to 0.5; when the grid electricity price is greater than 0.9 yuan / kWh, the depth of discharge coefficient is set to 0.8. Since step S2 needs to calculate the maximum discharge amount according to the stored electricity amount information and the first depth of discharge coefficient when the remaining stored electricity amount information is greater than or equal to the preset lower limit value of the stored electricity amount, this embodiment is equivalent to calculating the maximum discharge amount of the energy storage component while avoiding over-discharge of the energy storage component, so as to avoid the situation that the energy storage component accelerates decay and the service life of the energy storage component is shortened due to over-discharge of the energy storage component.

[0027] Step S3 can control the energy storage component to supply power to the charging pile according to the charging power demand by using the existing power supply method of the energy storage component. During the power supply process, the discharge amount of the energy storage component will be monitored. Since the maximum discharge amount is the maximum amount of electricity that the energy storage component is allowed to discharge under the current real-time electricity price information of the power grid, when the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand drops to 0 (equivalent to all charging piles having completed charging), this embodiment needs to control the energy storage component to stop supplying power to the charging pile to avoid over-discharging of the energy storage component or energy waste caused by continuing to supply power when the discharge amount of the energy storage component reaches the maximum discharge amount.

[0028] When the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0 (equivalent to when the discharge amount of the energy storage component reaches the maximum discharge amount and there are still charging piles that have not completed charging), Step S4 controls the mains power supply regulation component to supply power to the charging pile according to the charging power demand. The control of the mains power supply component to supply power to the charging pile can be realized by the existing mains power supply method, and no detailed discussion will be carried out here. Since when the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0, this embodiment only controls the mains power supply regulation component to supply power to the charging pile and does not control the energy storage component to supply power to the charging pile, this embodiment can effectively avoid the situation that the available power of the energy storage component is too little during the peak electricity price period or the energy storage component is deeply discharged due to over-discharging of the energy storage component.

[0029] A photovoltaic energy storage intelligent management method provided by this application can obtain a first depth of discharge coefficient associated with the real-time electricity price information of the power grid, and calculate the maximum discharge amount according to the stored electricity amount information and the first depth of discharge coefficient when the remaining stored electricity amount information is greater than or equal to the preset lower limit of the stored electricity amount. Since the first depth of discharge coefficient is positively correlated with the real-time electricity price information of the power grid, that is, this application can effectively retain the available discharge amount of the energy storage component by reducing the discharge amount of the energy storage component during the low electricity price period to increase the discharge amount of the energy storage component during the peak electricity price period. Therefore, this application can effectively solve the problem that the electricity amount of the energy storage battery is exhausted before the peak electricity price period, resulting in the need to purchase electricity from the power grid during the peak electricity price period, and the effect of reducing the operating cost through the energy storage system is limited. That is, this application can effectively improve the effect of reducing the operating cost. And since the maximum discharge amount of this application is calculated when the remaining stored electricity amount information is greater than or equal to the preset lower limit of the stored electricity amount, that is, this application can avoid the situation of deep discharge of the energy storage component. Therefore, this application can effectively solve the problem that the energy storage battery is accelerated to decay due to frequent deep discharge of the energy storage battery, and the service life of the energy storage battery is significantly shortened, thereby effectively reducing the replacement cost of the energy storage battery and further improving the effect of reducing the operating cost.

[0030] In some preferred embodiments, step S2 includes: S21. Query the pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain the first discharge depth coefficient; S22. Input the historical charge and discharge data of the energy storage component into the pre-trained health state evaluation model of the energy storage component to obtain the health state score; S23. Query the pre-constructed mapping relation table of health state score and discharge depth coefficient according to the health state score to obtain the second discharge depth coefficient; S24. Calculate the preliminary discharge amount according to the stored electricity information, the first discharge depth coefficient and the second discharge depth coefficient, and then calculate the remaining electricity information according to the stored electricity information and the preliminary discharge amount; S25. Analyze whether the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity. If so, use the preliminary discharge amount as the maximum discharge amount. If not, reduce the preliminary discharge amount until the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity, and use the reduced preliminary discharge amount as the maximum discharge amount.

[0031] The energy storage component health status assessment model of step S22 can be a neural network model, the input of the neural network model is the historical charge and discharge data of the energy storage component, and the output is the health status score. The historical charge and discharge data may include data such as charge and discharge current or charge and discharge voltage temperature. Specifically, the training set used in the present application to train the energy storage component health status assessment model includes multiple groups of discharge data and their corresponding status scores. The pre-constructed mapping relationship table of the health status score and the discharge depth coefficient of step S23 can be a data table, which divides the health status score into multiple intervals, each health status score interval corresponds to a discharge depth coefficient value, and when the actual health status score falls into a certain health status score interval, the discharge depth coefficient value corresponding to the health status score interval is obtained as the second discharge depth coefficient. Specifically, the health status score of this embodiment is positively correlated with the second discharge depth coefficient. Step S24 can calculate the preliminary discharge capacity by multiplying the storage capacity information, the first discharge depth coefficient and the second discharge depth coefficient. Step S24 can calculate the remaining power information by subtracting the preliminary discharge capacity from the storage capacity information. Step S25 can gradually reduce the initial discharge amount according to the preset step length until the condition that the remaining power information is greater than or equal to the preset storage power lower limit is met. Step S25 can also first calculate the difference between the preset storage power lower limit and the remaining power information, and then reduce the initial discharge amount based on the difference. The working principle of this embodiment is: since the storage power of energy storage components in different health states is different, if the health state of the energy storage component is not considered, the remaining power of energy storage components in different health states after discharge will be different. For example, under the same discharge amount, the available power of energy storage components in poor health during the peak electricity price period is less than the available power of energy storage components in good health during the peak electricity price period, resulting in limited effect of reducing operating costs. Therefore, this embodiment can first obtain the health status score, then obtain the second discharge depth coefficient according to the health status score, and finally calculate the initial discharge amount according to the second discharge depth coefficient. The method makes the initial discharge amount conform to the health state of the energy storage component, so as to increase the discharge amount of the energy storage component during the peak electricity price period as much as possible, thereby effectively improving the effect of reducing operating costs.

[0032] In some specific implementations, assuming that the current real-time grid electricity price information is 0.8 yuan / kWh, by querying the pre-constructed mapping relationship table of the grid electricity price and the discharge depth coefficient, the first discharge depth coefficient is obtained to be 0.7; assuming that the historical charge and discharge data of the energy storage component is input into the pre-trained energy storage component health status assessment model, the health status score is 80 points; assuming that by querying the pre-constructed mapping relationship table of the health status score and the discharge depth coefficient, the second discharge depth coefficient is obtained to be 0.8; assuming that the current energy storage component storage capacity information is 100 kWh; then according to step S24, the preliminary discharge capacity Degree of electricity, remaining electricity information = 100 - 56 = 44 degrees of electricity; assume that the preset lower limit value of the stored electricity is 20 degrees of electricity; since the remaining electricity information of 44 degrees of electricity is greater than the preset lower limit value of the stored electricity of 20 degrees of electricity, the initial discharge amount of 56 degrees of electricity is taken as the maximum discharge amount.

[0033] In some preferred embodiments, step S24 includes: S241. Obtain ambient temperature information, and query a pre-constructed mapping relation table of ambient temperature and discharge depth coefficient according to the ambient temperature information to obtain a third discharge depth coefficient; S242. Calculate the initial discharge amount according to the stored electricity information, the first discharge depth coefficient, the second discharge depth coefficient and the third discharge depth coefficient, and then calculate the remaining electricity information according to the stored electricity information and the initial discharge amount.

[0034] The ambient temperature information in step S241 is obtained by real-time monitoring of a temperature sensor, and the temperature sensor is arranged near the energy storage component to accurately obtain the working ambient temperature of the energy storage component. The pre-constructed mapping relation table of ambient temperature and discharge depth coefficient in this embodiment is preferably stored in the memory of the management device or a cloud server. The mapping relation table reflects the corresponding relationship between the ambient temperature and the discharge depth coefficient of the energy storage component. For example, when the ambient temperature is relatively high or low, the discharge depth coefficient can be set to a smaller value. On the contrary, when the ambient temperature is appropriate, the discharge depth coefficient can be set to a larger value. The initial discharge amount in step S242 is calculated by comprehensively considering the stored electricity information, the first discharge depth coefficient, the second discharge depth coefficient and the third discharge depth coefficient. Specifically, the calculation formula of the initial discharge amount in this embodiment can be the initial discharge amount = stored electricity information × first discharge depth coefficient × second discharge depth coefficient × third discharge depth coefficient. The remaining electricity information in this embodiment is obtained by subtracting the initial discharge amount from the stored electricity information. Since the working environment temperature of the energy storage component will affect the discharge efficiency and dischargeable amount of the energy storage component, if the ambient temperature is not considered, it may lead to insufficient power supply stability of the energy storage component. And this embodiment is equivalent to introducing the ambient temperature as a consideration factor for the discharge depth coefficient and the initial discharge amount. Therefore, this embodiment can effectively improve the accuracy of the initial discharge amount and the power supply stability of the energy storage component to more reasonably utilize the energy storage component to supply power to the charging pile under different ambient temperatures.

[0035] In some specific embodiments, assume that the pre-constructed mapping relationship table between the ambient temperature and the discharge depth coefficient is as follows: when the ambient temperature is less than or equal to 15 °C, the third discharge depth coefficient is 0.7; when the ambient temperature is greater than 15 °C and less than or equal to 40 °C, the third discharge depth coefficient is 1.0; when the ambient temperature is greater than 40 °C, the third discharge depth coefficient is 0.65. Taking the ambient temperature information as -10 °C, the first discharge depth coefficient as 0.6, and the second discharge depth coefficient as 0.9 as an example, the third discharge depth coefficient obtained in this embodiment is 0.7. The preliminary discharge amount in this embodiment = 100 kWh × 0.6 × 0.9 × 0.7 = 37.8 kWh.

[0036] In some preferred embodiments, step S25 includes: S251. Query the pre-constructed mapping relationship table of the health status score, ambient temperature, and the lower limit value of the stored electricity according to the health status score and the ambient temperature information to obtain the preset lower limit value of the stored electricity; S252. Analyze whether the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity. If so, take the preliminary discharge amount as the maximum discharge amount. If not, reduce the preliminary discharge amount until the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity, and take the reduced preliminary discharge amount as the maximum discharge amount.

[0037] The pre - constructed mapping relationship table for the health status score, ambient temperature, and lower limit value of the stored electricity in step S251 is used to dynamically determine the preset lower limit value of the stored electricity. Specifically, the mapping relationship table can be implemented as a multi - dimensional lookup table, where the health status score and ambient temperature information serve as input dimensions, and the corresponding preset lower limit value of the stored electricity serves as the output. For example, the mapping relationship table can store the preset lower limit values of the stored electricity under different health status score levels (such as excellent (80 - 100 points), good (60 - 80 points), average (40 - 60 points), poor (0 - 40 points)) and different ambient temperature ranges (such as low temperature (less than 15°C), normal temperature (greater than or equal to 15°C and less than 35°C), high temperature (greater than or equal to 35°C)). After obtaining the health status score and ambient temperature information of the energy storage component, by referring to this mapping relationship table, the preset lower limit value of the stored electricity that matches the current state of the energy storage component can be obtained. In step S252, the remaining electricity information is compared and analyzed with the preset lower limit value of the stored electricity obtained dynamically to determine whether the preliminary discharge amount needs to be adjusted. Specifically, if the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity, it indicates that the preliminary discharge amount is reasonable and can be directly used as the maximum discharge amount. If the remaining electricity information is less than the preset lower limit value of the stored electricity, it indicates that the preliminary discharge amount may cause over - discharge of the energy storage component. At this time, the preliminary discharge amount needs to be reduced until the remaining electricity information is greater than or equal to the preset lower limit value of the stored electricity, and then the adjusted preliminary discharge amount is used as the final maximum discharge amount to ensure that the energy storage component will not be over - discharged. This embodiment is equivalent to adaptively adjusting the preset lower limit value of the stored electricity according to the health status and working ambient temperature of the energy storage component. Therefore, this embodiment can effectively avoid the situation where over - discharge of the energy storage component occurs due to using too low a preset lower limit value of the stored electricity when the health status of the energy storage component deteriorates or the ambient temperature is unfavorable, or the situation where the stored electricity of the energy storage component is not fully utilized due to using too high a preset lower limit value of the stored electricity when the health status of the energy storage component is good or the ambient temperature is suitable, so as to more precisely control the discharge behavior of the energy storage component on the premise of ensuring the safe operation of the energy storage component, thereby effectively extending the service life of the energy storage component and improving the overall economy and reliability of the photovoltaic energy storage intelligent management method.

[0038] In some specific embodiments, it is assumed that the pre-constructed mapping relationship table regarding the health status score, environmental temperature, and the lower limit value of the stored electricity is set as follows: when the health status score is above 90 points and the environmental temperature is between 15 and 35 degrees Celsius, the preset lower limit value of the stored electricity is 10% of the total capacity of the energy storage component; when the health status score is between 70 and 90 points and the environmental temperature is between 0 and 40 degrees Celsius, the preset lower limit value of the stored electricity is 20% of the total capacity of the energy storage component; when the health status score is below 70 points, or the environmental temperature is below 0 degrees Celsius or above 40 degrees Celsius, the preset lower limit value of the stored electricity is 30% of the total capacity of the energy storage component. If the current health status score of the energy storage component is 80 points and the environmental temperature is 25 degrees Celsius, then the preset lower limit value of the stored electricity in this embodiment is 20% of the total capacity of the energy storage component.

[0039] In some preferred embodiments, the photovoltaic power generation component is also electrically connected to the charging pile, and step S3 includes: S31. Obtain the power generation power information of the photovoltaic power generation component, and analyze whether the power generation power information is greater than or equal to the charging power demand. If so, control the photovoltaic power generation component to supply power to the charging pile, and when the power generation power information is greater than the charging power demand and the stored electricity information has not reached the preset upper limit value of the stored electricity, control the photovoltaic power generation component to charge the energy storage component with the difference between the power generation power information and the charging power demand. If not, execute step S32 or step S33; S32. When the power generation power information is 0, control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand decreases to 0; S33. When the power generation power information is not 0, control the photovoltaic power generation component to supply power to the charging pile with the power generation power information, and control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand decreases to 0.

[0040] In step S31, the power generation power information of the photovoltaic power generation module and the charging power demand of the charging pile are acquired in real time, and then it is determined whether the power generation power information can meet the charging power demand. Specifically, if the power generation power information is greater than or equal to the charging power demand, it indicates that the power generation capacity of the photovoltaic power generation module is sufficient. At this time, the photovoltaic power generation module is controlled to directly supply power to the charging pile to realize the priority utilization of photovoltaic power. Further, if the power generation power information not only meets the charging demand but also has a power surplus (the power generation power information is greater than the charging power demand), and the energy storage module still has storage space (the stored power information has not reached the preset upper limit of the stored power), the surplus power is used to charge the energy storage module to maximize the utilization of photovoltaic power. If the power generation power information is less than the charging power demand, it indicates that the power generation capacity of the photovoltaic power generation module cannot fully meet the charging power demand. At this time, the system will select to enter step S32 or step S33 according to whether the power generation power information is 0. Specifically, step S32 is for the case where the photovoltaic power generation module has no power generation power at all (the power generation power information is 0). At this time, the charging pile is completely powered by the energy storage module. Step S33 is for the case where the photovoltaic power generation module has power generation power but the power generation power is insufficient to meet the charging demand (the power generation power information is not 0). At this time, the power of the photovoltaic power generation module is first used to supply power to the charging pile, and the insufficient part is supplemented by the energy storage module. This embodiment is equivalent to directly supplying power to the charging pile by the photovoltaic power generation module when the photovoltaic power generation module can generate power (the power generation power information is greater than 0) and the charging power demand is greater than 0. Since the energy loss of directly supplying power to the charging pile by the photovoltaic power generation module is less than the energy loss of indirectly supplying power to the charging pile by the photovoltaic power generation module (first using the photovoltaic power generation module to charge the energy storage module and then using the energy storage module to supply power to the charging pile), this embodiment can effectively improve the energy utilization efficiency, thereby further reducing the operating cost of the electric vehicle charging station and effectively reducing the charge and discharge times of the energy storage module, and further effectively extending the service life of the energy storage module. Suppose at a certain moment, the detected power generation power of the photovoltaic power generation module is 8 kW, and the charging power demand of the charging pile is 6 kW. Since 8 kW is greater than 6 kW, this embodiment controls the photovoltaic power generation module to directly supply 6 kW of power to the charging pile. When the stored power of the energy storage module has not reached the upper limit, this embodiment uses the surplus 2 kW of power to charge the energy storage module. Suppose at another moment, the detected power generation power of the photovoltaic power generation module is 3 kW, and the charging power demand of the charging pile is 6 kW. Since 3 kW is less than 6 kW and is not 0, this embodiment controls the photovoltaic power generation module to supply 3 kW of power to the charging pile, and at the same time controls the energy storage module to supply 3 kW of power to the charging pile to meet the total 6 kW of power demand of the charging pile.

[0041] In some preferred embodiments, step S32 includes: S321. When the power generation power information is 0, analyze whether the real-time grid electricity price information is less than or equal to the first preset threshold. If so, control the mains supply regulation component to supply power to the charging pile according to the charging power demand. If not, control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0. Step S33 includes: S331. When the power generation power information is not 0, analyze whether the real-time grid electricity price information is less than or equal to the first preset threshold. If so, control the photovoltaic power generation component to supply power to the charging pile at the power generation power information, and control the mains supply regulation component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information. If not, control the photovoltaic power generation component to supply power to the charging pile at the power generation power information, and control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0.

[0042] The first preset threshold of this embodiment is equivalent to the benchmark for judging the high or low grid electricity price. Specifically, if the real-time grid electricity price information is less than or equal to the first preset threshold, it indicates that purchasing electricity from the grid is an economical choice. At this time, the mains supply regulation component supplies power to the charging pile alone or jointly with the photovoltaic power generation component. That is, when the grid electricity price is low, this embodiment does not use the energy storage component to supply power to the charging pile. If the real-time grid electricity price information is greater than the first preset threshold, it indicates that the grid electricity price is relatively high, and it is more economical to use the energy storage component to discharge. At this time, the energy storage component supplies power to the charging pile alone or jointly with the photovoltaic power generation component until the energy storage component reaches the set maximum discharge amount or the power demand of the charging pile is reduced to 0. This embodiment is equivalent to using cheap mains electricity to supply power to the charging pile when the grid electricity price is low. That is, the discharge amount of the energy storage component of this embodiment is 0 when the grid electricity price is low. Therefore, this embodiment can effectively reduce the discharge amount of the energy storage component when the grid electricity price is low and increase the available discharge amount of the energy storage component when the grid electricity price is high, thereby further reducing the operating cost of the electric vehicle charging station.

[0043] In some specific embodiments, the first preset threshold can be adjusted according to actual operation data and electricity price fluctuation rules. For example, this embodiment can obtain the periods with low electricity prices in a day by analyzing historical electricity price data, and set the average electricity price slightly higher than these low electricity price periods as the first preset threshold. Another example is that in areas with obvious seasonal electricity price differences, different first preset thresholds can be set for different seasons to more finely adapt to electricity price changes and achieve better economic operation effects.

[0044] In some preferred embodiments, the step of controlling the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information includes: A1. Analyze whether the difference between the charging power demand and the generated power information is greater than the upper limit value of the power supply of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the upper limit value of the power supply, and control the mains supply regulation component to supply power to the charging pile according to the difference between the difference between the charging power demand and the generated power information and the upper limit value of the power supply. If not, control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the generated power information; The steps of controlling the energy storage component to supply power to the charging pile according to the charging power demand include: B1. Analyze whether the charging power demand is greater than the upper limit value of the power supply of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the upper limit value of the power supply, and control the mains supply regulation component to supply power to the charging pile according to the difference between the charging power demand and the upper limit value of the power supply. If not, control the energy storage component to supply power to the charging pile according to the charging power demand.

[0045] This embodiment is equivalent to controlling the coordinated power supply of the energy storage component and the mains supply regulation component based on the upper limit value of the power supply. The specific control method is as follows: When the photovoltaic power generation is not 0, first calculate the difference between the charging power demand and the generated power information, and then analyze whether this difference is greater than the upper limit value of the power supply of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the upper limit value of the power supply, and at the same time control the mains supply regulation component to supply power to the charging pile to supplement the difference between the difference between the charging power demand and the generated power information and the upper limit value of the power supply. If not, only control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the generated power information; When the photovoltaic power generation is 0, analyze whether the charging power demand is greater than the upper limit value of the power supply of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the upper limit value of the power supply, and control the mains supply regulation component to supply power to the charging pile to supplement the difference between the charging power demand and the upper limit value of the power supply. If not, control the energy storage component to supply power to the charging pile alone according to the charging power demand. This embodiment is equivalent to meeting the power supply demand of the charging pile through the cooperation of the energy storage component, the photovoltaic power generation component and the mains supply regulation component while avoiding the overload operation of the energy storage component, thereby effectively avoiding the situation that the energy storage component is damaged due to overload operation. Taking the case where the photovoltaic power generation is not 0, the charging power demand is 70kW, the photovoltaic power generation information is 20kW, and the upper limit value of the power supply of the energy storage component is set to 40kW as an example, the difference between the charging power demand and the generated power information is 50kW. Since 50kW is greater than 40kW, this embodiment controls the energy storage component to supply power to the charging pile at a power of 40kW, and controls the mains supply regulation component to supply power to the charging pile at a power of 10kW.

[0046] In some preferred embodiments, the upper limit value of the power supply is determined based on the health state score of the energy storage component and the ambient temperature information. In this embodiment, the upper limit value of the power supply can be obtained by querying a pre-constructed mapping relation table of the health state score, ambient temperature and power upper limit value according to the health state score of the energy storage component and the ambient temperature information. Preferably, the mapping relation table of the health state score, ambient temperature and power upper limit value in this embodiment is similar to the mapping relation table of the health state score, ambient temperature and lower limit value of the stored power in the above embodiment, and will not be listed here. This embodiment is equivalent to dynamically adjusting the upper limit value of the power supply based on the health state score of the energy storage component and the ambient temperature information. Therefore, this embodiment can prevent the situation that the energy storage component is overloaded due to using an excessive upper limit value of the power supply when the health state of the energy storage component deteriorates or the ambient temperature is unfavorable, or the discharge performance of the energy storage component is not fully utilized due to using a too low upper limit value of the power supply when the health state of the energy storage component is good or the ambient temperature is suitable, resulting in an increase in the power supply of the mains supply regulation component and an increase in the operating cost of the electric vehicle charging station.

[0047] In some preferred embodiments, the photovoltaic energy storage intelligent management method further includes the steps of: S5. When the power generation power information is 0, the real-time grid electricity price information is less than or equal to the second preset threshold, and the stored power information has not reached the preset upper limit value of the stored power, control the mains supply regulation component to charge the energy storage component.

[0048] In order to enable the mains power supply regulation component to charge the energy storage component, the system needs to monitor multiple pieces of information in real time. First, the power generation information is monitored to determine whether the photovoltaic power generation component is generating electricity. When the monitored power generation information is 0, it indicates that the photovoltaic power generation component has no power output. Second, the real-time grid electricity price information is obtained and compared with a second preset threshold. The second preset threshold in this embodiment is equivalent to the benchmark for judging the high or low grid electricity price. When the real-time grid electricity price information is less than or equal to the second preset threshold, it indicates that the grid electricity price is low at the current time period. Third, the stored electricity amount information of the energy storage component is obtained and compared with a preset upper limit value of the stored electricity amount. The preset upper limit value of the stored electricity amount is the maximum amount of electricity that the energy storage component is allowed to store. Only when the stored electricity amount information does not reach the preset upper limit value of the stored electricity amount is charging allowed to avoid overcharging of the energy storage component. Since the charging of the energy storage component is only controlled by the mains power supply regulation component when the three conditions of power generation information being 0, real-time grid electricity price information being less than or equal to the second preset threshold, and stored electricity amount information not reaching the preset upper limit value of the stored electricity amount are simultaneously met, it should be understood that the charging process of the energy storage component continues until any one of the above three conditions is no longer satisfied, that is, when the stored electricity amount of the energy storage component reaches the preset upper limit value of the stored electricity amount, the real-time grid electricity price information rises to be greater than the second preset threshold, or the photovoltaic power generation component starts to generate electricity (power generation information is greater than 0), the mains power supply regulation component stops charging the energy storage component. Since this embodiment can use the mains power to charge the energy storage component at a low grid electricity price to effectively supplement the stored electricity amount of the energy storage component, this embodiment can enable the energy storage component to release sufficient electricity during the peak electricity price period, thereby effectively reducing the electricity purchase amount of the electric vehicle charging station from the grid during the peak electricity price period, and further effectively reducing the operating cost of electricity charges.

[0049] As can be seen from the above, a photovoltaic energy storage intelligent management method provided by the present application can obtain a first depth of discharge coefficient associated with real-time grid electricity price information, and calculate the maximum discharge amount according to the electricity storage amount information and the first depth of discharge coefficient when the remaining electricity storage amount information is greater than or equal to a preset lower limit value of the electricity storage amount. Since the first depth of discharge coefficient is positively correlated with the real-time grid electricity price information, that is, the present application can effectively retain the available discharge amount of the energy storage component by reducing the discharge amount of the energy storage component during the low electricity price period, so as to increase the discharge amount of the energy storage component during the high electricity price period. Therefore, the present application can effectively solve the problem that the electricity of the energy storage battery is exhausted before the high electricity price period, resulting in the need to purchase electricity from the grid during the high electricity price period, and the effect of reducing the operating cost through the energy storage system is limited. That is, the present application can effectively improve the effect of reducing the operating cost. And since the maximum discharge amount of the present application is calculated when the remaining electricity storage amount information is greater than or equal to the preset lower limit value of the electricity storage amount, that is, the present application can avoid the situation of deep discharge of the energy storage component. Therefore, the present application can effectively solve the problem that the energy storage battery is accelerated to decay due to frequent deep discharge of the energy storage battery, and the service life of the energy storage battery is significantly shortened, thereby effectively reducing the replacement cost of the energy storage battery and further improving the effect of reducing the operating cost.

[0050] In a second aspect, as Figure 2 shown, the present application further provides a photovoltaic energy storage intelligent management device, which is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component and a mains supply regulation component. The energy storage component is used to store the electric energy generated by the photovoltaic power generation component. The photovoltaic energy storage intelligent management device includes: An information acquisition module 1, configured to acquire the electricity storage amount information of the energy storage component, the charging power demand of the charging pile, and the real-time grid electricity price information; A maximum discharge amount acquisition module 2, configured to query a pre-constructed mapping relationship table of grid electricity price and depth of discharge coefficient according to the real-time grid electricity price information to obtain a first depth of discharge coefficient, and calculate the maximum discharge amount according to the electricity storage amount information and the first depth of discharge coefficient when the remaining electricity storage amount information is greater than or equal to a preset lower limit value of the electricity storage amount. The first depth of discharge coefficient is positively correlated with the real-time grid electricity price information; A first power supply module 3, configured to control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0; A second power supply module 4, configured to control the mains supply regulation component to supply power to the charging pile according to the charging power demand when the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0.

[0051] A photovoltaic energy storage intelligent management device provided by this application includes an information acquisition module 1, a maximum discharge amount acquisition module 2, a first power supply module 3, and a second power supply module 4. The photovoltaic energy storage intelligent management device provided by this embodiment is used to execute the steps in a photovoltaic energy storage intelligent management method provided in the first aspect above. The principle of the photovoltaic energy storage intelligent management device provided by this embodiment is the same as that of the photovoltaic energy storage intelligent management method provided in the first aspect above, and will not be elaborated in detail here.

[0052] As can be seen from the above, a photovoltaic energy storage intelligent management method and device provided by this application can obtain a first discharge depth coefficient associated with real-time grid electricity price information, and calculate the maximum discharge amount according to the stored electricity information and the first discharge depth coefficient when the remaining stored electricity information is greater than or equal to a preset lower limit value of the stored electricity. Since the first discharge depth coefficient is positively correlated with the real-time grid electricity price information, that is, this application can effectively retain the available discharge amount of the energy storage component by reducing the discharge amount of the energy storage component during the low electricity price period, so as to increase the discharge amount of the energy storage component during the high electricity price period. Therefore, this application can effectively solve the problem that the electricity of the energy storage battery is exhausted before the high electricity price period, resulting in the need to purchase electricity from the grid during the high electricity price period, and the effect of reducing the operating cost through the energy storage system is limited. That is, this application can effectively improve the effect of reducing the operating cost. And since the maximum discharge amount of this application is calculated when the remaining stored electricity information is greater than or equal to the preset lower limit value of the stored electricity, that is, this application can avoid the deep discharge of the energy storage component. Therefore, this application can effectively solve the problem that the energy storage battery is accelerated to decay due to frequent deep discharge of the energy storage battery, and the service life of the energy storage battery is significantly shortened, thereby effectively reducing the replacement cost of the energy storage battery and further improving the effect of reducing the operating cost.

[0053] In the embodiments provided by this application, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are only illustrative. For example, the above unit division is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another robot, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0054] In addition, in each embodiment of this application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0055] In this document, relational terms such as first and second are used solely to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0056] The above description is only for the embodiments of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, various modifications and changes can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A photovoltaic energy storage intelligent management method is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component, and a mains power supply regulation component. The energy storage component is used to store the electric energy generated by a photovoltaic power generation component, and is characterized in that, The photovoltaic energy storage intelligent management method includes the following steps: S1. Obtain the stored electricity information of the energy storage component, the charging power demand of the charging pile, and the real-time grid electricity price information; S2. Query the pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain the first discharge depth coefficient, and calculate the maximum discharge amount according to the stored electricity information and the first discharge depth coefficient when the remaining stored electricity information is greater than or equal to the preset lower limit of stored electricity. The first discharge depth coefficient is positively correlated with the real-time grid electricity price information; S3. Control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand drops to 0; S4. When the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0, control the mains power supply adjustment component to supply power to the charging pile according to the charging power demand.

2. The photovoltaic energy storage intelligent management method according to claim 1, characterized in that Step S2 includes: S21. Query the pre-constructed mapping relation table of grid electricity price and discharge depth coefficient according to the real-time grid electricity price information to obtain the first discharge depth coefficient; S22. Input the historical charge and discharge data of the energy storage component into the pre-trained health state evaluation model of the energy storage component to obtain the health state score; S23. Query the pre-constructed mapping relation table of health state score and discharge depth coefficient according to the health state score to obtain the second discharge depth coefficient; S24. Calculate the preliminary discharge amount according to the stored electricity information, the first discharge depth coefficient, and the second discharge depth coefficient, and then calculate the remaining electricity information according to the stored electricity information and the preliminary discharge amount; S25. Analyze whether the remaining electricity information is greater than or equal to the preset lower limit of stored electricity. If so, use the preliminary discharge amount as the maximum discharge amount. If not, reduce the preliminary discharge amount until the remaining electricity information is greater than or equal to the preset lower limit of stored electricity, and use the reduced preliminary discharge amount as the maximum discharge amount.

3. The photovoltaic energy storage intelligent management method according to claim 2, characterized in that, Step S24 includes: S241. Obtain the ambient temperature information, and query the pre-constructed mapping relation table of ambient temperature and discharge depth coefficient according to the ambient temperature information to obtain the third discharge depth coefficient; S242. Calculate the preliminary discharge amount according to the stored electricity information, the first discharge depth coefficient, the second discharge depth coefficient, and the third discharge depth coefficient, and then calculate the remaining electricity information according to the stored electricity information and the preliminary discharge amount.

4. The photovoltaic energy storage intelligent management method according to claim 3, wherein, Step S25 includes: S251. Query the pre-constructed mapping relation table of health state score, ambient temperature and lower limit of stored electricity according to the health state score and the ambient temperature information to obtain the preset lower limit of stored electricity; S252. Analyze whether the remaining power information is greater than or equal to the preset lower limit of the stored power. If so, use the preliminary discharge amount as the maximum discharge amount. If not, reduce the preliminary discharge amount until the remaining power information is greater than or equal to the preset lower limit of the stored power, and use the reduced preliminary discharge amount as the maximum discharge amount.

5. The photovoltaic energy storage intelligent management method according to claim 1, wherein, The photovoltaic power generation component is also electrically connected to the charging pile. Step S3 includes: S31. Obtain the power generation power information of the photovoltaic power generation component, and analyze whether the power generation power information is greater than or equal to the charging power demand. If so, control the photovoltaic power generation component to supply power to the charging pile, and when the power generation power information is greater than the charging power demand and the stored power information has not reached the preset upper limit of the stored power, control the photovoltaic power generation component to charge the energy storage component with the difference between the power generation power information and the charging power demand. If not, execute step S32 or step S33; S32. When the power generation power information is 0, control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0; S33. When the power generation power information is not 0, control the photovoltaic power generation component to supply power to the charging pile with the power generation power information, and control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0.

6. The photovoltaic energy storage intelligent management method according to claim 5, characterized in that Step S32 includes: S321. When the power generation power information is 0, analyze whether the real-time grid electricity price information is less than or equal to the first preset threshold. If so, control the mains power supply adjustment component to supply power to the charging pile according to the charging power demand. If not, control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0; Step S33 includes: S331. When the power generation power information is not 0, analyze whether the real-time grid electricity price information is less than or equal to the first preset threshold. If so, control the photovoltaic power generation component to supply power to the charging pile with the power generation power information, and control the mains power supply adjustment component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information. If not, control the photovoltaic power generation component to supply power to the charging pile with the power generation power information, and control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0.

7. The photovoltaic energy storage intelligent management method according to claim 6, wherein The step of controlling the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information includes: A1. Analyze whether the difference between the charging power demand and the power generation power information is greater than the upper limit value of the power supply of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the upper limit value of the power supply, and control the mains power supply adjustment component to supply power to the charging pile according to the difference between the difference between the charging power demand and the power generation power information and the upper limit value of the power supply. If not, control the energy storage component to supply power to the charging pile according to the difference between the charging power demand and the power generation power information; The step of controlling the energy storage component to supply power to the charging pile according to the charging power demand includes: B1. Analyze whether the charging power demand is greater than the upper limit value of the power supply of the energy storage component. If so, control the energy storage component to supply power to the charging pile at the upper limit value of the power supply, and control the mains power supply adjustment component to supply power to the charging pile according to the difference between the charging power demand and the upper limit value of the power supply. If not, control the energy storage component to supply power to the charging pile according to the charging power demand.

8. The photovoltaic energy storage intelligent management method according to claim 7, characterized in that The upper limit value of the power supply is determined based on the health status score of the energy storage component and the ambient temperature information.

9. The photovoltaic energy storage intelligent management method according to claim 1, wherein The photovoltaic energy storage intelligent management method further includes the step of: S5. When the power generation power information is 0, the real-time grid electricity price information is less than or equal to the second preset threshold, and the stored electricity information has not reached the preset upper limit value of the stored electricity, control the mains power supply adjustment component to charge the energy storage component.

10. A photovoltaic energy storage intelligent management device is applied in an electric vehicle charging station. The electric vehicle charging station includes a charging pile, an energy storage component, and a mains power supply regulation component. The energy storage component is used to store the electric energy generated by a photovoltaic power generation component, and is characterized in that, The photovoltaic energy storage intelligent management device includes: An information acquisition module, configured to acquire the stored electricity information of the energy storage component, the charging power demand of the charging pile, and the real-time grid electricity price information; A maximum discharge amount acquisition module, configured to query a pre-constructed mapping relationship table of grid electricity prices and discharge depth coefficients according to the real-time grid electricity price information to obtain a first discharge depth coefficient, and calculate the maximum discharge amount according to the stored electricity information and the first discharge depth coefficient when the remaining stored electricity information is greater than or equal to the preset lower limit value of the stored electricity. The first discharge depth coefficient is positively correlated with the real-time grid electricity price information; A first power supply module, configured to control the energy storage component to supply power to the charging pile according to the charging power demand until the discharge amount of the energy storage component reaches the maximum discharge amount or the charging power demand is reduced to 0; A second power supply module, configured to, when the discharge amount of the energy storage component reaches the maximum discharge amount and the charging power demand is not 0, control the mains power supply adjustment component to supply power to the charging pile according to the charging power demand.

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