Scheduling method and system of new energy charging piles based on the Internet of Things

Abstract

The present invention discloses a scheduling method and system for new energy charging piles based on the Internet of Things, the method comprising: obtaining ambient temperature distribution information and charging pile distribution information of a region to be scheduled, and determining multiple sub-regions from the region to be scheduled according to the ambient temperature distribution information and the charging pile distribution information; predicting the target charging efficiency of the sub-region according to the current power consumption, average ambient temperature and maximum charging power of the sub-region, and predicting the target discharge efficiency of the sub-region according to the current power consumption, average ambient temperature and maximum discharge power; determining the sub-region with the highest target charging efficiency among the multiple sub-regions as the first sub-region, and determining the sub-region with the highest target discharge efficiency among the multiple sub-regions as the second sub-region; adjusting the charging piles in the first sub-region to the first working mode, and adjusting the charging piles in the second sub-region to the second working mode. The present invention can improve the scheduling efficiency of charging piles.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a scheduling method and system for new energy charging piles based on the Internet of Things. Background Art

[0002] As the popularity of electric vehicles continues to increase, the development trend of charging piles, as a key component of electric vehicle infrastructure, is becoming particularly important. Target charging piles will increasingly adopt Internet of Things technology to achieve remote monitoring, scheduling, fault diagnosis, maintenance management and other functions through cloud management systems.

[0003] Among them, with the advancement of the construction of new power systems, Vehicle-to-Grid (V2G) is receiving widespread attention. This is because through V2G technology, the problems of low grid efficiency and fluctuations in renewable energy can not only be alleviated to a great extent, but also create benefits for electric vehicle users.

[0004] However, the current V2G technology encourages users to charge their vehicles at a low price during low electricity consumption periods, and discharge their vehicles at a high price during peak electricity consumption periods to recover electricity. This may cause users to only charge or discharge their vehicles during these two electricity consumption periods, completely ignoring the efficiency of charging or discharging, thereby causing serious waste of energy. Summary of the invention

[0005] In view of the technical problem in the prior art that it is impossible to ensure that energy is not wasted when using V2G technology, the present invention provides a scheduling method and system for new energy charging piles based on the Internet of Things.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] In a first aspect of an embodiment of the present invention, a scheduling method for new energy charging piles based on the Internet of Things is provided, the method comprising:

[0008] Acquire ambient temperature distribution information and charging pile distribution information of the area to be scheduled, and determine multiple sub-areas from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-areas meets a preset number condition, and the ambient temperature of the sub-areas meets a preset temperature condition, and the charging piles are bidirectional charging piles;

[0009] For each of the sub-regions, obtaining the current power consumption, average ambient temperature, maximum charging power of each charging pile in the sub-region, and maximum discharge power of each vehicle to be discharged in the sub-region;

[0010] Predicting a target charging efficiency of the sub-region within a target time period based on the current power consumption, the average ambient temperature, and the maximum charging power, and predicting a target discharging efficiency of the sub-region within a target time period based on the current power consumption, the average ambient temperature, and the maximum discharging power, wherein the target time period is a time period from a current moment to a target moment;

[0011] Determine the sub-region with the highest target charging efficiency among the multiple sub-regions as the first sub-region, and determine the sub-region with the highest target discharging efficiency among the multiple sub-regions as the second sub-region;

[0012] During the target time period, the charging piles in the first sub-area are adjusted to a first working mode for charging vehicles, and the charging piles in the second sub-area are adjusted to a second working mode for receiving vehicle discharge, and the discharged electricity received by the charging piles in the second sub-area is transmitted to the charging piles in the first sub-area.

[0013] Optionally, predicting a target charging efficiency of the sub-region within a target time period according to the current power consumption, the average ambient temperature, and the maximum charging power includes:

[0014] Determining the available charging power of each charging pile in the sub-region according to the current power consumption;

[0015] For each charging pile, obtaining charging pile parameters of the charging pile, and determining a charging attenuation coefficient of the charging pile according to the charging pile parameters and the average ambient temperature;

[0016] Determining an initial charging efficiency of the charging pile according to the available charging power, the maximum charging power, and the charging attenuation coefficient;

[0017] Based on the initial charging efficiency of each of the charging posts, a target charging efficiency of the sub-region is determined.

[0018] Optionally, determining the initial charging efficiency of the charging pile according to the available charging power, the maximum charging power, and the charging attenuation coefficient includes:

[0019] The available charging power, the maximum charging power, and the charging attenuation coefficient are calculated using the following formula to obtain the initial charging efficiency:

[0020]

[0021] Wherein, η is the initial charging efficiency, t1 is the target time, t0 is the current time, t is the duration between the current time and the target time, t ′is the time between the current time and the target time, P usable is the available charging power, and k is the charging attenuation coefficient.

[0022] Optionally, the charging pile includes a storage battery, and determining the target charging efficiency of the sub-region based on the initial charging efficiency of each of the charging piles includes:

[0023] Obtaining the remaining power of the storage battery in each of the charging piles, and determining the fusion weight of the charging piles based on the remaining power;

[0024] Based on the fusion weight, the initial charging efficiency of each charging pile is fused to obtain the target charging efficiency of the sub-region.

[0025] Optionally, determining the available charging power of each charging pile in the sub-region according to the current power consumption includes:

[0026] Determining the electricity consumption level of the sub-region according to the current electricity consumption;

[0027] Obtain the load power upper limit corresponding to the power consumption level and the number of charging piles in the sub-area, and determine the available charging power of each charging pile according to the load power upper limit and the number of charging piles, wherein the available charging power of the charging pile is less than the maximum charging power of the charging pile.

[0028] Optionally, predicting a target discharge efficiency of the sub-region within a target time period according to the current power consumption, the average ambient temperature and the maximum discharge power includes:

[0029] Determining the actual discharge power of each vehicle to be discharged in the sub-region according to the current power consumption;

[0030] For each vehicle to be discharged, obtaining battery parameters of the vehicle to be discharged, and determining a discharge attenuation coefficient of the vehicle to be discharged according to the battery parameters and the average ambient temperature;

[0031] Determining the initial discharge efficiency of the vehicle to be discharged according to the actual discharge power, the maximum discharge power, and the discharge attenuation coefficient;

[0032] Based on the initial discharge efficiency of each of the vehicles to be discharged, a target discharge efficiency of the sub-region is determined.

[0033] Optionally, the charging pile in the sub-region includes an image acquisition device, and the obtaining of battery parameters of the vehicle to be discharged includes:

[0034] Acquire the location information of the vehicle to be discharged, and determine at least one charging pile located around the vehicle to be discharged in the sub-region as a collection charging pile according to the location information;

[0035] The image of the vehicle to be discharged is acquired by using the image acquisition device of the charging pile to obtain a vehicle image;

[0036] identifying the vehicle type of the vehicle to be discharged based on the vehicle image;

[0037] According to the vehicle type, battery parameters of the vehicle to be discharged are determined.

[0038] Optionally, determining a plurality of sub-regions from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information includes:

[0039] Dividing the area to be scheduled into a plurality of initial sub-areas according to the ambient temperature distribution information, wherein the difference between the upper ambient temperature limit and the lower ambient temperature limit corresponding to each of the initial sub-areas is less than or equal to a first difference threshold, and the difference between the average ambient temperatures corresponding to any two initial sub-areas in the plurality of initial sub-areas is greater than a second difference threshold;

[0040] For each initial sub-region of the plurality of initial sub-regions, determining the number of charging piles in the initial sub-region according to the charging pile distribution information;

[0041] If the number of charging posts in the initial sub-region is greater than or equal to the number threshold, the initial sub-region is determined to be the sub-region.

[0042] Optionally, the ambient temperature distribution information includes a geographical coordinate set corresponding to the area to be scheduled and an ambient temperature value corresponding to each geographical coordinate in the geographical coordinate set;

[0043] The charging pile distribution information includes the geographical coordinates of each charging pile in the area to be scheduled.

[0044] In a second aspect of an embodiment of the present invention, a scheduling system for new energy charging piles based on the Internet of Things is provided, the system comprising:

[0045] A sub-region determination module, used to obtain ambient temperature distribution information and charging pile distribution information of the area to be scheduled, and determine multiple sub-regions from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-regions meeting a preset number condition, and the ambient temperature of the sub-regions meeting a preset temperature condition, and the charging piles are bidirectional charging piles;

[0046] An acquisition module, for acquiring, for each of the sub-regions, the current power consumption, the average ambient temperature, the maximum charging power of each charging pile in the sub-region, and the maximum discharge power of each vehicle to be discharged in the sub-region;

[0047] a prediction module, configured to predict a target charging efficiency of the sub-region within a target time period according to the current power consumption, the average ambient temperature, and the maximum charging power, and to predict a target discharge efficiency of the sub-region within a target time period according to the current power consumption, the average ambient temperature, and the maximum discharge power, wherein the target time period is a time period between a current moment and a target moment;

[0048] a determination module, configured to determine a sub-region with the highest target charging efficiency among the plurality of sub-regions as a first sub-region, and determine a sub-region with the highest target discharging efficiency among the plurality of sub-regions as a second sub-region;

[0049] The scheduling module is used to adjust the charging piles in the first sub-area to a first working mode for charging vehicles, and adjust the charging piles in the second sub-area to a second working mode for receiving vehicle discharge during the target time period, and transmit the discharged electricity received by the charging piles in the second sub-area to the charging piles in the first sub-area.

[0050] The present invention provides a scheduling method and system for new energy charging piles based on the Internet of Things. Compared with the prior art, it has the following beneficial effects:

[0051] The solution provided in this embodiment obtains the ambient temperature distribution information and the charging pile distribution information of the area to be scheduled, and determines multiple sub-areas from the area to be scheduled based on the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-area meets the preset number condition, and the ambient temperature of the sub-area meets the preset temperature condition, and the charging piles are bidirectional charging piles; for each sub-area, the current power consumption, average ambient temperature, maximum charging power of each charging pile in the sub-area, and maximum discharge power of each to-be-discharged vehicle in the sub-area are obtained; based on the current power consumption, average ambient temperature and maximum charging power, the target charging pile of the sub-area within the target time period is predicted. Efficiency, and according to the current power consumption, average ambient temperature and maximum discharge power, predict the target discharge efficiency of the sub-region within the target time period, the target time period is the time period between the current moment and the target moment; determine the sub-region with the highest target charging efficiency among multiple sub-regions as the first sub-region, and determine the sub-region with the highest target discharge efficiency among multiple sub-regions as the second sub-region; in the target time period, adjust the charging pile in the first sub-region to the first working mode for charging the vehicle, and adjust the charging pile in the second sub-region to the second working mode for receiving the vehicle discharge, and transmit the discharge power received by the charging pile in the second sub-region to the charging pile in the first sub-region. In this way, the target charging efficiency and target discharge efficiency of each region can be accurately identified in combination with the regional temperature of different regions, and the working state of the charging pile in each region can be adjusted according to the target charging efficiency and target discharge efficiency, which can encourage users to charge their vehicles in areas with high charging efficiency and discharge their vehicles in areas with high discharge efficiency, thereby improving the energy conversion efficiency and avoiding the problem of energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a schematic diagram of an application scenario of a scheduling method for new energy charging piles based on the Internet of Things according to an exemplary embodiment;

[0053] Figure 2 is a flow chart of a method for scheduling new energy charging piles based on the Internet of Things according to an exemplary embodiment;

[0054] Figure 3 is a schematic diagram of sub-area division according to an exemplary embodiment;

[0055] Figure 4 It is a principle block diagram of a scheduling system for new energy charging piles based on the Internet of Things according to an exemplary embodiment. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] It is understandable that in the specific implementation of this application, data related to access requests, addresses, etc. is involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0058] Figure 1 is a schematic diagram of an application environment of a scheduling method for new energy charging piles based on the Internet of Things according to an exemplary embodiment. Figure 1 As shown, the application environment can be a target Internet of Things network, which can include a scheduling server, multiple vehicles and multiple charging piles, wherein the multiple vehicles and multiple charging piles are in a to-be-scheduled area, and the scheduling server can be used to schedule the charging piles in the to-be-scheduled area. The scheduling server can be a separate server or a server cluster, which is not limited here. The scheduling server can be respectively connected to multiple vehicles and multiple charging piles in communication, and optionally, multiple charging piles can also be connected in communication.

[0059] Figure 2 is a flow chart of a method for scheduling new energy charging piles based on the Internet of Things according to an exemplary embodiment. Figure 2 As shown, the above method comprises the following steps:

[0060] 110. Obtain the ambient temperature distribution information and charging pile distribution information of the area to be scheduled, and determine multiple sub-areas from the area to be scheduled based on the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-area meets the preset number condition, and the ambient temperature of the sub-area meets the preset temperature condition, and the charging piles are bidirectional charging piles.

[0061] Among them, the area to be dispatched is the area where IoT charging piles need to be dispatched. The area can be an area corresponding to a province, an area corresponding to a city, or an area customized by the dispatcher according to actual needs.

[0062] Among them, a bidirectional charging pile is a charging pile that uses advanced charging technology, which allows a two-way flow of electricity between electric vehicles (EVs) and the power grid, that is, it can charge new energy vehicles and receive the discharge of new energy vehicles to recycle electricity to the grid. This technology is usually based on vehicle-to-V2G technology, through which electric vehicles can not only obtain electricity from the grid for charging, but also transmit the electricity stored in the battery back to the grid.

[0063] In some embodiments, the ambient temperature distribution information includes a set of geographical coordinates corresponding to the area to be scheduled and an ambient temperature value corresponding to each geographical coordinate in the set of geographical coordinates; wherein the geographical coordinates can be represented by longitude and latitude.

[0064] The charging pile distribution information includes the geographical coordinates of each charging pile in the area to be scheduled.

[0065] In some embodiments, determining a plurality of sub-regions from the region to be scheduled according to the ambient temperature distribution information and the charging pile distribution information may include:

[0066] The area to be scheduled is divided into multiple initial sub-areas according to the ambient temperature distribution information, wherein the difference between the upper and lower ambient temperature corresponding to each initial sub-area is less than or equal to a first difference threshold, and the difference between the average ambient temperatures corresponding to any two initial sub-areas in the multiple initial sub-areas is greater than a second difference threshold.

[0067] Exemplarily, in the area to be scheduled, multiple candidate sub-areas can be randomly divided in advance, such as candidate sub-area A, candidate sub-area B, etc. Then, if it is detected according to the environmental distribution information that the upper limit of the ambient temperature of candidate sub-area A is 28 degrees and the lower limit of the ambient temperature is 25 degrees, assuming that the first difference threshold is 5°, then candidate sub-area A can be determined as the initial sub-area, and so on, multiple initial sub-areas can be obtained.

[0068] For example, Figure 3As shown, a target geographic coordinate O can be selected, an initial distance d1 can be set, and then a circular area can be formed with the target geographic coordinate as the center and the initial distance as the radius, and real-time detection can be performed to see whether the upper and lower limits of the ambient temperature in the circular area exceed the first difference threshold. If not, the initial distance can be increased, and detection can be continued based on the increased initial distance until the first difference threshold is exceeded, and the currently obtained circular area can be used as an initial sub-area (such as initial sub-area C). Then, the initial distance can be continued to be increased (such as increasing the initial distance to a distance of d2) around the periphery of the initial sub-area C to obtain an annular area. If the annular area also satisfies the condition that the upper and lower limits of the ambient temperature exceed the first difference threshold, the annular area can be determined as a new initial sub-area D, and multiple initial sub-areas can be obtained by analogy.

[0069] For each initial sub-region among the multiple initial sub-regions, the number of charging piles in the initial sub-region is determined according to the charging pile distribution information.

[0070] If the number of charging piles in the initial sub-region is greater than or equal to the number threshold, the initial sub-region is determined to be a sub-region.

[0071] For example, for each initial sub-region, the number of charging piles in the initial sub-region may be determined based on the number of overlaps between the geographical coordinate set corresponding to the initial sub-region and the geographical coordinates of the charging piles in the area to be scheduled, wherein the number of overlaps is consistent with the number of charging piles.

[0072] In this embodiment, by dividing the area with similar ambient temperature in the area to be scheduled into a sub-area, the charging piles in the divided sub-area can be conveniently scheduled uniformly using the ambient temperature, thereby improving the scheduling efficiency. In addition, by ensuring that the number of charging piles in the sub-area is greater than or equal to the number threshold, it is avoided that there are not enough charging piles in the sub-area to be scheduled, affecting the scheduling effect, thereby improving the scheduling accuracy.

[0073] 120. For each sub-region, obtain the current power consumption, average ambient temperature, maximum charging power of each charging pile in the sub-region, and maximum discharge power of each vehicle to be discharged in the sub-region.

[0074] The current power consumption of the sub-region may refer to the power consumption of all power-consuming devices in the sub-region, including the power consumption of household devices, the power consumption of public devices, etc. The current power consumption may be obtained by requesting the power grid system.

[0075] The average ambient temperature may be the middle value between the upper and lower ambient temperature in the sub-region, or may be the quotient of the cumulative value of the ambient temperature value corresponding to each pre-calibrated geographic coordinate in the sub-region and the number of the pre-calibrated geographic coordinates.

[0076] Among them, the maximum charging power of the charging pile is the rated charging power of the charging pile, and the maximum charging power can be uploaded to the server in advance. Among them, the maximum discharge power of the vehicle to be discharged can be obtained by sending an acquisition request to the vehicle-mounted terminal of the vehicle to be discharged. Alternatively, it can be obtained by performing image acquisition and image recognition through an image acquisition device set in the charging pile near the vehicle to be discharged in the sub-area, for example, by collecting the model of the vehicle to be discharged, and then querying the corresponding maximum discharge power on the Internet according to the model.

[0077] 130. Based on the current power consumption, average ambient temperature and maximum charging power, predict the target charging efficiency of the sub-region within the target time period. Based on the current power consumption, average ambient temperature and maximum discharge power, predict the target discharge efficiency of the sub-region within the target time period. The target time period is the time period from the current moment to the target moment.

[0078] In some embodiments, the current power consumption, average ambient temperature, and maximum charging power may be input into a pre-trained charging efficiency prediction model to obtain a target charging efficiency output by the charging efficiency prediction model. The charging efficiency prediction model may be trained based on pre-labeled power consumption samples, ambient temperature samples, charging power samples, and charging efficiency information samples. Specifically, the relationship between the current power consumption, average ambient temperature, maximum charging power, and target charging efficiency may be learned by training the charging efficiency prediction model.

[0079] In some embodiments, in step 130, based on the current power consumption, the average ambient temperature, and the maximum charging power, a specific implementation of predicting the target charging efficiency of the sub-region within the target time period may include:

[0080] A1. Determine the available charging power of each charging pile in the sub-region based on the current power consumption.

[0081] In some implementations, determining the available charging power of each charging pile in the sub-region according to the current power consumption may include:

[0082] Determine the electricity consumption level of the sub-region based on the current electricity consumption.

[0083] The power consumption level may be a pre-divided level, and each level may correspond to a load power upper limit in advance, indicating that the current power consumption cannot exceed the load power upper limit corresponding to the corresponding power consumption level.

[0084] The load power upper limit corresponding to the power consumption level and the number of charging piles in the sub-region are obtained, and the available charging power of each charging pile is determined according to the load power upper limit and the number of charging piles, wherein the available charging power of the charging pile is less than the maximum charging power of the charging pile.

[0085] The load power limit can be divided by the number of charging piles in the sub-region to obtain the charging power limit of each charging pile, and then the scheduling server can adjust the available charging power of the charging pile according to the charging power limit, such as adjusting the available charging power to a specified power less than the charging power limit. Alternatively, the scheduling server can adjust the available charging power of each charging pile according to actual needs, and only needs to ensure that the available charging power of each does not exceed the charging power limit.

[0086] Optionally, the available charging power of the charging pile can be

[0087] A2. For each charging pile, obtain the charging pile parameters of the charging pile, and determine the charging attenuation coefficient of the charging pile according to the charging pile parameters and the average ambient temperature.

[0088] Among them, charging pile parameters may include but are not limited to: charging current, charging voltage, charging interface type, etc.

[0089] For example, a charging degradation constant can be determined based on the charging current, charging voltage, and charging interface type. The charging degradation constant is usually used to describe the degree to which the performance of the charging pile gradually decreases over time or the number of times it is used during the charging process. The larger the degradation constant, the faster the performance decreases.

[0090] Then, the charging attenuation coefficient of the charging pile can be determined according to the decay constant, the average ambient temperature and a preset first relationship function, wherein the first relationship function can be a relationship function summarized according to the historical decay constant, the historical ambient temperature and the historical charging attenuation coefficient.

[0091] Taking into account that the long-term ambient temperature of the region will have a certain impact on the charging effect of the charging pile, specifically on the charging decay constant of the charging pile, in this embodiment, the charging pile parameters of the charging pile are used to determine the charging attenuation coefficient of the charging pile according to the charging pile parameters and the average ambient temperature, thereby improving the accuracy of the charging attenuation coefficient.

[0092] A3. Determine the initial charging efficiency of the charging pile based on the available charging power, maximum charging power, and charging attenuation coefficient.

[0093] In some embodiments, determining the initial charging efficiency of the charging pile according to the available charging power, the maximum charging power, and the charging attenuation coefficient may include:

[0094] The available charging power, maximum charging power, and charging attenuation coefficient are calculated using the following formula to obtain the initial charging efficiency:

[0095]

[0096] Where η is the initial charging efficiency, t1 is the target time, t0 is the current time, t is the time between the current time and the target time, and t ′ is the time between the current time and the target time, P usable is the available charging power, and k is the charging attenuation coefficient.

[0097] A4. Based on the initial charging efficiency of each charging pile, determine the target charging efficiency of the sub-region.

[0098] In some embodiments, the charging pile includes a storage battery, and determining the target charging efficiency of the sub-region based on the initial charging efficiency of each charging pile may include:

[0099] The remaining power of the storage battery in each charging pile is obtained, and the fusion weight of the charging pile is determined based on the remaining power; based on the fusion weight, the initial charging efficiency of each charging pile is fused to obtain the target charging efficiency of the sub-region.

[0100] Among them, since the charging pile does not need to process, convert, or perform other operations on the electric energy in the power grid when charging through the storage battery, the remaining power of the storage battery in the charging pile can be positively correlated with the fusion weight, that is, the larger the remaining power of the storage battery in the charging pile, the larger the fusion weight corresponding to the charging pile.

[0101] For example, the charging piles in a sub-region include charging pile 1, charging pile 2, and charging pile 3. The target charging efficiency corresponding to charging pile 1 is η1, and the fusion weight is w1. The target charging efficiency corresponding to charging pile 2 is η2, and the fusion weight is w2. The target charging efficiency corresponding to charging pile 3 is η3, and the fusion weight is w3. Then the target charging efficiency of the sub-region can be expressed as: (η1·w1+η2·w2+η3·w3) / 3.

[0102] In some embodiments, in step 130, predicting the target discharge efficiency of the sub-region within the target time period according to the current power consumption, the average ambient temperature and the maximum discharge power may include:

[0103] B1. Determine the actual discharge power of each vehicle to be discharged in the sub-region based on the current power consumption.

[0104] Among them, when the current power consumption of a region is large, such as during the peak power consumption period, the load power of the power grid is large. If the vehicle to be discharged inputs a large power when discharging to the region, it will affect the stability of the power grid. Therefore, in this embodiment, the actual discharge power of each vehicle to be discharged in the sub-region can be determined by the current power consumption to ensure that the actual discharge power does not affect the stability of the power grid. Among them, the specific implementation method of predicting the target discharge efficiency of the sub-region within the target time period based on the current power consumption, average ambient temperature and maximum discharge power can refer to the implementation method of A1 and is not repeated here.

[0105] B2. For each vehicle to be discharged, obtain the battery parameters of the vehicle to be discharged, and determine the discharge attenuation coefficient of the vehicle to be discharged according to the battery parameters and the average ambient temperature.

[0106] In this embodiment, since discharging is the reverse process of charging, the charging object and the discharging object are simply swapped, the specific implementation of step B2 can be the same as that of step A1 and will not be described in detail here.

[0107] In some embodiments, the charging pile in the sub-region includes an image acquisition device, and obtaining battery parameters of the vehicle to be discharged may include:

[0108] The position information of the vehicle to be discharged is obtained, and at least one charging pile located around the vehicle to be discharged in the sub-area is determined as a collection charging pile according to the position information; an image collection device of the charging pile is used to collect an image of the vehicle to be discharged to obtain a vehicle image; the vehicle type of the vehicle to be discharged is identified based on the vehicle image; and the battery parameters of the vehicle to be discharged are determined according to the vehicle type.

[0109] Optionally, considering that the image acquisition device of a single charging pile may not be able to capture a complete image of the vehicle to be discharged due to the limitation of the acquisition angle, image acquisition devices of multiple charging piles can be used to capture images of the vehicle to be discharged from different angles, and then the multiple images captured are integrated to obtain a complete image of the vehicle to be discharged, so as to facilitate accurate identification of the type of vehicle.

[0110] The dispatch server may pre-store different vehicle types and battery parameters corresponding to different vehicle types, so as to quickly query and obtain corresponding battery parameters after identifying the vehicle type. The battery parameters may include battery capacity, discharge current, discharge voltage and other parameters of the battery.

[0111] B3. Determine the initial discharge efficiency of the vehicle to be discharged based on the actual discharge power, the maximum discharge power, and the discharge attenuation coefficient.

[0112] B4. Determine the target discharge efficiency of the sub-region based on the initial discharge efficiency of each vehicle to be discharged.

[0113] The specific implementation of step B3 and step B4 can refer to step A3 and step A4, so they will not be described here in detail.

[0114] 140. Determine a sub-region with the highest target charging efficiency among the multiple sub-regions as a first sub-region, and determine a sub-region with the highest target discharging efficiency among the multiple sub-regions as a second sub-region.

[0115] 150. During the target time period, the charging piles in the first sub-area are adjusted to a first operating mode for charging vehicles, and the charging piles in the second sub-area are adjusted to a second operating mode for receiving vehicle discharge, and the discharged electricity received by the charging piles in the second sub-area is transmitted to the charging piles in the first sub-area.

[0116] Among them, when the charging pile is in the first working mode, the charging pile is only allowed to charge the vehicle. When the new energy vehicle searches for the charging pile, it can be displayed that the charging pile only has the charging function. When the charging pile is in the second working mode, the charging pile is only allowed to receive the discharge of the vehicle. When the new energy vehicle searches for the charging pile, it can be displayed that the charging pile only has the function of receiving the discharge of the vehicle, so that the user can make accurate charging and discharging decisions based on the search results.

[0117] In some embodiments, for other sub-regions in the plurality of sub-regions except the first sub-region and the second sub-region, the scheduling server may further adjust the second ratio between the number of charging piles entering the first working state and the number of charging piles entering the second working state in the other sub-regions according to the first ratio between the target charging efficiency and the target discharging efficiency in the other sub-regions, wherein the first ratio and the second ratio may be positively correlated. Optionally, the first ratio and the second ratio may be equal.

[0118] It can be seen that in this embodiment, by obtaining the ambient temperature distribution information and the charging pile distribution information of the area to be scheduled, and according to the ambient temperature distribution information and the charging pile distribution information, multiple sub-areas are determined from the area to be scheduled, the number of charging piles set in the sub-area meets the preset number condition, and the ambient temperature of the sub-area meets the preset temperature condition, and the charging piles are bidirectional charging piles; for each sub-area, the current power consumption, average ambient temperature, maximum charging power of each charging pile in the sub-area, and maximum discharge power of each to-be-discharged vehicle in the sub-area are obtained; according to the current power consumption, average ambient temperature and maximum charging power, the target charging pile of the sub-area within the target time period is predicted. The target discharge efficiency of the sub-region within the target time period is predicted based on the current power consumption, the average ambient temperature and the maximum discharge power; the sub-region with the highest target charging efficiency among the multiple sub-regions is determined as the first sub-region, and the sub-region with the highest target discharge efficiency among the multiple sub-regions is determined as the second sub-region; in the target time period, the charging piles in the first sub-region are adjusted to a first working mode for charging the vehicle, and the charging piles in the second sub-region are adjusted to a second working mode for receiving the discharge of the vehicle, and the discharged power received by the charging piles in the second sub-region is transmitted to the charging piles in the first sub-region. Therefore, it is possible to accurately identify the target charging efficiency and target discharging efficiency of each region in combination with the regional temperature of different regions, and adjust the working state of the charging piles in each region according to the target charging efficiency and target discharging efficiency, which can encourage users to charge their vehicles in areas with high charging efficiency and discharge their vehicles in areas with high discharging efficiency, thereby improving the energy conversion efficiency and causing energy waste. In addition, it also avoids the problem that car owners charge and discharge in high-load areas in order to sell electricity at high prices during peak electricity consumption and charge at low prices during low electricity consumption periods, thereby affecting the stability of the power grid. Moreover, in this embodiment, multiple charging piles in the sub-region are uniformly dispatched as a dispatching unit, thereby avoiding the tediousness of individually dispatching each charging pile, thereby improving the dispatching efficiency.

[0119] In this embodiment, if Figure 4 As shown, a scheduling system for a new energy charging pile based on the Internet of Things is also provided. The scheduling system 300 for a new energy charging pile based on the Internet of Things includes:

[0120] The sub-region determination module 310 is used to obtain the ambient temperature distribution information and the charging pile distribution information of the area to be scheduled, and determine multiple sub-regions from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-region meets the preset number condition, and the ambient temperature of the sub-region meets the preset temperature condition, and the charging pile is a bidirectional charging pile;

[0121] An acquisition module 320 is used to acquire, for each sub-region, the current power consumption of the sub-region, the average ambient temperature, the maximum charging power of each charging pile in the sub-region, and the maximum discharge power of each vehicle to be discharged in the sub-region;

[0122] The prediction module 330 is used to predict the target charging efficiency of the sub-region within the target time period according to the current power consumption, the average ambient temperature and the maximum charging power, and to predict the target discharge efficiency of the sub-region within the target time period according to the current power consumption, the average ambient temperature and the maximum discharge power, where the target time period is the time period from the current moment to the target moment;

[0123] A determination module 340, configured to determine a sub-region with the highest target charging efficiency among the multiple sub-regions as a first sub-region, and determine a sub-region with the highest target discharging efficiency among the multiple sub-regions as a second sub-region;

[0124] The scheduling module 350 is used to adjust the charging piles in the first sub-area to a first working mode for charging the vehicle, and adjust the charging piles in the second sub-area to a second working mode for receiving the discharge of the vehicle during the target time period, and transmit the discharged power received by the charging piles in the second sub-area to the charging piles in the first sub-area.

[0125] In some implementations, the prediction module 330 is specifically configured to:

[0126] Determine the available charging power of each charging pile in the sub-region according to the current power consumption;

[0127] For each charging pile, obtaining charging pile parameters of the charging pile, and determining a charging attenuation coefficient of the charging pile according to the charging pile parameters and the average ambient temperature;

[0128] Determining the initial charging efficiency of the charging pile according to the available charging power, the maximum charging power, and the charging attenuation coefficient;

[0129] Based on the initial charging efficiency of each of the charging piles, the target charging efficiency of the sub-region is determined.

[0130] In some implementations, the prediction module 330 is further configured to:

[0131] The available charging power, the maximum charging power, and the charging attenuation coefficient are calculated using the following formula to obtain the initial charging efficiency:

[0132]

[0133] Wherein, η is the initial charging efficiency, t1 is the target time, t0 is the current time, t is the time between the current time and the target time, t ′ is the time between the current time and the target time, P usable is the available charging power, and k is the charging attenuation coefficient.

[0134] In some embodiments, the charging pile includes a storage battery, and the prediction module 330 is further used to:

[0135] Obtaining the remaining power of the storage battery in each of the charging piles, and determining the fusion weight of the charging piles based on the remaining power;

[0136] Based on the above fusion weights, the initial charging efficiency of each of the above charging piles is fused to obtain the target charging efficiency of the above sub-region.

[0137] In some implementations, the prediction module 330 is further configured to:

[0138] Determine the electricity consumption level of the sub-region according to the current electricity consumption;

[0139] Obtain the load power upper limit corresponding to the above-mentioned power consumption level and the number of charging piles in the above-mentioned sub-area, and determine the available charging power of each of the above-mentioned charging piles based on the above-mentioned load power upper limit and the number of the above-mentioned charging piles, wherein the available charging power of the above-mentioned charging piles is less than the maximum charging power of the above-mentioned charging piles.

[0140] In some implementations, the prediction module 330 is further configured to:

[0141] Determine the actual discharge power of each vehicle to be discharged in the sub-region according to the current power consumption;

[0142] For each vehicle to be discharged, obtaining battery parameters of the vehicle to be discharged, and determining a discharge attenuation coefficient of the vehicle to be discharged according to the battery parameters and the average ambient temperature;

[0143] Determining the initial discharge efficiency of the vehicle to be discharged according to the actual discharge power, the maximum discharge power, and the discharge attenuation coefficient;

[0144] Based on the initial discharge efficiency of each of the vehicles to be discharged, a target discharge efficiency of the sub-region is determined.

[0145] In some implementations, the prediction module 330 is further configured to:

[0146] Acquire the location information of the vehicle to be discharged, and determine at least one charging pile located around the vehicle to be discharged in the sub-region as a collection charging pile according to the location information;

[0147] The image of the vehicle to be discharged is acquired by the image acquisition device of the charging pile to obtain a vehicle image;

[0148] Identifying the vehicle type of the vehicle to be discharged based on the vehicle image;

[0149] According to the above vehicle type, the battery parameters of the above vehicle to be discharged are determined.

[0150] In some implementations, the sub-region determination module 310 is specifically configured to:

[0151] Divide the area to be scheduled into a plurality of initial sub-areas according to the ambient temperature distribution information, wherein the difference between the upper ambient temperature limit and the lower ambient temperature limit corresponding to each of the initial sub-areas is less than or equal to a first difference threshold, and the difference between the average ambient temperatures corresponding to any two of the plurality of initial sub-areas is greater than a second difference threshold;

[0152] For each of the multiple initial sub-regions, determining the number of charging piles in the initial sub-region according to the charging pile distribution information;

[0153] If the number of charging piles in the initial sub-region is greater than or equal to the number threshold, the initial sub-region is determined to be the sub-region.

[0154] In some embodiments, the ambient temperature distribution information includes a set of geographical coordinates corresponding to the area to be scheduled and an ambient temperature value corresponding to each geographical coordinate in the set of geographical coordinates;

[0155] The above charging pile distribution information includes the geographical coordinates of each charging pile in the above scheduling area.

[0156] Based on the above ideal embodiments of this application, the relevant staff can make various changes and modifications without departing from the technical concept of this application through the above description. The technical scope of this application is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

[0157] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A scheduling method for new energy charging piles based on the Internet of Things, characterized in that: include: Acquire ambient temperature distribution information and charging pile distribution information of the area to be scheduled, and determine multiple sub-areas from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-areas meets a preset number condition, and the ambient temperature of the sub-areas meets a preset temperature condition, and the charging piles are bidirectional charging piles; For each of the sub-regions, obtaining the current power consumption, average ambient temperature, maximum charging power of each charging pile in the sub-region, and maximum discharge power of each vehicle to be discharged in the sub-region; Predicting a target charging efficiency of the sub-region within a target time period based on the current power consumption, the average ambient temperature, and the maximum charging power, and predicting a target discharging efficiency of the sub-region within a target time period based on the current power consumption, the average ambient temperature, and the maximum discharging power, wherein the target time period is a time period from a current moment to a target moment; Determine the sub-region with the highest target charging efficiency among the multiple sub-regions as the first sub-region, and determine the sub-region with the highest target discharging efficiency among the multiple sub-regions as the second sub-region; During the target time period, the charging piles in the first sub-area are adjusted to a first working mode for charging vehicles, and the charging piles in the second sub-area are adjusted to a second working mode for receiving vehicle discharge, and the discharged electricity received by the charging piles in the second sub-area is transmitted to the charging piles in the first sub-area.

2. The method for scheduling new energy charging piles based on the Internet of Things according to claim 1, characterized in that: The predicting, according to the current power consumption, the average ambient temperature, and the maximum charging power, the target charging efficiency of the sub-region within the target time period includes: Determining the available charging power of each charging pile in the sub-region according to the current power consumption; For each charging pile, obtaining charging pile parameters of the charging pile, and determining a charging attenuation coefficient of the charging pile according to the charging pile parameters and the average ambient temperature; Determining an initial charging efficiency of the charging pile according to the available charging power, the maximum charging power, and the charging attenuation coefficient; Based on the initial charging efficiency of each of the charging posts, a target charging efficiency of the sub-region is determined.

3. The method for scheduling new energy charging piles based on the Internet of Things according to claim 2 is characterized in that: The determining the initial charging efficiency of the charging pile according to the available charging power, the maximum charging power, and the charging attenuation coefficient includes: The available charging power, the maximum charging power, and the charging attenuation coefficient are calculated using the following formula to obtain the initial charging efficiency: Wherein, η is the initial charging efficiency, t1 is the target time, t0 is the current time, t is the duration between the current time and the target time, t′ is the time between the current time and the target time, P usable is the available charging power, and k is the charging attenuation coefficient.

4. The method for scheduling new energy charging piles based on the Internet of Things according to claim 3 is characterized in that: The charging pile includes a storage battery, and determining the target charging efficiency of the sub-region based on the initial charging efficiency of each of the charging piles includes: Obtaining the remaining power of the storage battery in each of the charging piles, and determining the fusion weight of the charging piles based on the remaining power; Based on the fusion weight, the initial charging efficiency of each charging pile is fused to obtain the target charging efficiency of the sub-region.

5. The method for scheduling new energy charging piles based on the Internet of Things according to claim 2, characterized in that: The determining, according to the current power consumption, the available charging power of each charging pile in the sub-region includes: Determining the electricity consumption level of the sub-region according to the current electricity consumption; Obtain the load power upper limit corresponding to the power consumption level and the number of charging piles in the sub-area, and determine the available charging power of each charging pile according to the load power upper limit and the number of charging piles, wherein the available charging power of the charging pile is less than the maximum charging power of the charging pile.

6. The method for scheduling new energy charging piles based on the Internet of Things according to claim 1, characterized in that: The predicting, according to the current power consumption, the average ambient temperature and the maximum discharge power, the target discharge efficiency of the sub-region within the target time period includes: Determining the actual discharge power of each vehicle to be discharged in the sub-region according to the current power consumption; For each vehicle to be discharged, obtaining battery parameters of the vehicle to be discharged, and determining a discharge attenuation coefficient of the vehicle to be discharged according to the battery parameters and the average ambient temperature; Determining the initial discharge efficiency of the vehicle to be discharged according to the actual discharge power, the maximum discharge power, and the discharge attenuation coefficient; Based on the initial discharge efficiency of each of the vehicles to be discharged, a target discharge efficiency of the sub-region is determined.

7. The method for scheduling new energy charging piles based on the Internet of Things according to claim 6, characterized in that: The charging pile of the sub-region includes an image acquisition device, and the obtaining of battery parameters of the vehicle to be discharged includes: Acquire the location information of the vehicle to be discharged, and determine at least one charging pile located around the vehicle to be discharged in the sub-region as a collection charging pile according to the location information; The image of the vehicle to be discharged is acquired by using the image acquisition device of the charging pile to obtain a vehicle image; identifying the vehicle type of the vehicle to be discharged based on the vehicle image; According to the vehicle type, battery parameters of the vehicle to be discharged are determined.

8. The method for scheduling new energy charging piles based on the Internet of Things according to any one of claims 1 to 7, characterized in that: The determining of a plurality of sub-regions from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information comprises: Dividing the area to be scheduled into a plurality of initial sub-areas according to the ambient temperature distribution information, wherein the difference between the upper ambient temperature limit and the lower ambient temperature limit corresponding to each of the initial sub-areas is less than or equal to a first difference threshold, and the difference between the average ambient temperatures corresponding to any two initial sub-areas in the plurality of initial sub-areas is greater than a second difference threshold; For each initial sub-region of the plurality of initial sub-regions, determining the number of charging piles in the initial sub-region according to the charging pile distribution information; If the number of charging posts in the initial sub-region is greater than or equal to the number threshold, the initial sub-region is determined to be the sub-region.

9. The method for scheduling new energy charging piles based on the Internet of Things according to claim 8, characterized in that: The ambient temperature distribution information includes a set of geographical coordinates corresponding to the area to be scheduled and an ambient temperature value corresponding to each geographical coordinate in the set of geographical coordinates; The charging pile distribution information includes the geographical coordinates of each charging pile in the area to be scheduled.

10. A scheduling system for new energy charging piles based on the Internet of Things, characterized in that: include: A sub-region determination module, used to obtain ambient temperature distribution information and charging pile distribution information of the area to be scheduled, and determine multiple sub-regions from the area to be scheduled according to the ambient temperature distribution information and the charging pile distribution information, the number of charging piles set in the sub-regions meeting a preset number condition, and the ambient temperature of the sub-regions meeting a preset temperature condition, and the charging piles are bidirectional charging piles; An acquisition module, for acquiring, for each of the sub-regions, the current power consumption, the average ambient temperature, the maximum charging power of each charging pile in the sub-region, and the maximum discharge power of each vehicle to be discharged in the sub-region; a prediction module, configured to predict a target charging efficiency of the sub-region within a target time period according to the current power consumption, the average ambient temperature, and the maximum charging power, and to predict a target discharge efficiency of the sub-region within a target time period according to the current power consumption, the average ambient temperature, and the maximum discharge power, wherein the target time period is a time period between a current moment and a target moment; a determination module, configured to determine a sub-region with the highest target charging efficiency among the plurality of sub-regions as a first sub-region, and determine a sub-region with the highest target discharging efficiency among the plurality of sub-regions as a second sub-region; The scheduling module is used to adjust the charging piles in the first sub-area to a first working mode for charging vehicles, and adjust the charging piles in the second sub-area to a second working mode for receiving vehicle discharge during the target time period, and transmit the discharged electricity received by the charging piles in the second sub-area to the charging piles in the first sub-area.

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