Alternating current charging pile ordered charging control method and device

Abstract

The invention belongs to the technical field of charging, and particularly relates to an alternating current charging pile ordered charging control method and device, and the method comprises the steps: S1, an information collection master station module obtains historical power utilization records of all common power utilization modules, and selects a preset model from all preset models as a final model; s2, the information acquisition master station module judges whether a preset time point is reached or not, if yes, the current total power consumption data is input into the final model, and the final model outputs the total power consumption data of all the common power consumption modules at a preset future time point; s3, the information acquisition master station module determines final total power consumption data of all the common power consumption modules at a preset future time point, and checks whether the final total power consumption data is greater than preset total power consumption data; and S4, the information acquisition master station module secretly sends a control command to the concentrator module. According to the invention, ordered charging by using the charging pile can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of charging, and in particular relates to a method and device for controlling orderly charging of an AC charging pile. Background Art

[0002] At present, electric vehicles are becoming more and more popular among the public due to their environmental protection and low cost. As a result, the number of charging piles is also increasing. However, the existing methods of charging using charging piles are mostly disorderly charging methods, which are easy to overlap with the peak of daily electricity consumption. Even if the service fee time-sharing price difference is used to guide the orderly use of charging piles for charging, the problem of overload of transformers in the substation still exists.

[0003] A similar prior art includes a Chinese patent application with publication number CN116872773A, which provides a method, device and charging pile for timed charging of a charging pile, wherein the method comprises: loading at least one timed charging task to be executed into a list of charging tasks to be executed of the charging pile according to the timing setting information of the charging pile, determining the target execution state of the timed charging task to be executed according to the current time, the timing time of the timed charging task to be executed and the charging state of the charging pile, and judging whether to start the execution of the task, stop the execution of the task, or delete the execution of the task according to the current time, the charging start time of the timed charging task to be executed and other conditions. In addition, similar prior art includes a Chinese patent application with publication number CN110626209A, which discloses a charging pile charging method and a charging pile charging system, obtains the current user's charging request for the current charging pile, performs user authentication on the current user identification information, and after authentication, queries the current use status of the current charging pile based on the current charging pile identification information, and feeds back the current use status to the user. When the current use status indicates that the current charging pile is available, remotely controls the current charging pile to perform charging operations for the current user, authenticates the user, and can perform subsequent operations only after authentication. However, the above patent applications cannot achieve orderly charging, and the use of charging piles may still affect the electricity consumption of life. Summary of the invention

[0004] The present invention selects a final model and uses the final model to estimate the peak time of daily electricity consumption in advance. When the charging pile module is used during the peak time of daily electricity consumption, a control command is secretly sent to a charging power controller module connected to the charging pile module to control the charging process to ensure that the normal use of daily electricity is not affected.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides an AC charging pile orderly charging control method as described below, which mainly includes the following steps:

[0006] S1. The information collection main station module obtains the historical power consumption records of all common power consumption modules based on the current time point, and the information collection main station module selects a preset model from all preset models as the final model;

[0007] S2, the information collection master station module determines whether the preset time point has been reached. If not, continue to wait and determine whether the preset time point has been reached. If yes, obtain the current total power consumption data of all the common power consumption modules, input the current total power consumption data into the final model, and the final model outputs the total power consumption data of all the common power consumption modules at the preset future time point, and determines whether the end condition is met. If so, end this step, and if not, repeat this step;

[0008] S3, the information collection master station module determines the final total power consumption data of all the common power consumption modules at a preset future time point according to the total power consumption data output by the final model, and checks whether the final total power consumption data is greater than the preset total power consumption data. If yes, proceed to the next step;

[0009] S4. Before the preset future time point arrives, the information collection main station module sends detection information to the charging power controller modules connected to all charging pile modules. When it is detected that the charging pile modules are in use, the control command is secretly sent to the concentrator module. The control command is forwarded by the concentrator module to the charging power controller module connected to the corresponding charging pile module, and the charging process is controlled by the charging power controller module.

[0010] As a preferred technical solution of the present invention, in S1, the information acquisition main station module selects a preset model from all preset models as the final model, including the following steps:

[0011] S11, determining a preset model from all preset models, performing a first setting on the determined preset model, and generating and storing a data record corresponding to the determined preset model based on the historical power consumption record, wherein the data record includes the determined preset model, the first total power consumption data, the first difference value, the second total power consumption data, and the second difference value;

[0012] S12, resetting the determined preset model, generating a new data record, determining whether the second difference value in the new data record is less than the second difference value in the stored data record, if so, deleting the stored data record, storing the new data record, and continuing to S13, if so, directly continuing to S13;

[0013] S13, judging whether the determined preset model can be reset, if yes, jumping to S12, if no, judging whether all preset models have been determined, if yes, continuing to S14, if no, jumping to S11;

[0014] S14. For each data record corresponding to the stored preset model, identification data is set according to the size of the first difference value and the second difference value in the data record, the identification data is added to the data record, and the final model is selected based on the data records corresponding to all the stored preset models.

[0015] As a preferred technical solution of the present invention, in S11, based on the historical electricity consumption records, generating and storing data records corresponding to a determined preset model includes: based on the historical electricity consumption records, the total electricity consumption data of the first preset historical time point and the second preset historical time point contained in the historical electricity consumption records are respectively input into the final model, the final model respectively outputs the first total electricity consumption data and the second total electricity consumption data of the preset future time point, respectively calculates the first difference value and the second difference value between the first total electricity consumption data and the second total electricity consumption data and the actual total electricity consumption data of the preset future time point, and uses the determined preset model, the first total electricity consumption data, the first difference value, the second total electricity consumption data, and the second difference value to form a data record.

[0016] As a preferred technical solution of the present invention, in S14, setting the identification data according to the size of the first difference value and the second difference value in the data record includes: when the first difference value is greater than the second difference value, setting the identification data to 1; when the first difference value is equal to the second difference value, setting the identification data to 0; when the first difference value is less than the second difference value, setting the identification data to -1.

[0017] As a preferred technical solution of the present invention, in S14, selecting the final model based on the data records corresponding to all stored preset models includes the following steps:

[0018] S141. Based on all data records, calculate the mean of the first difference value and the second difference value in the data record, and check whether there is a data record whose corresponding mean value is less than a preset mean threshold value. If so, continue to check whether the data record whose corresponding mean value is less than the mean threshold value is unique. If so, take the preset model corresponding to the data record whose corresponding mean value is less than the mean threshold value as the final model. If not, continue to S142.

[0019] S142. Among all data records whose corresponding means are less than the mean threshold, check whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to S11. If yes, continue to check whether the data records with corresponding identification data of 1 or 0 are unique. If yes, take the preset model corresponding to the data records with corresponding identification data of 1 or 0 as the final model. If not, among all data records with corresponding identification data of 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

[0020] As a preferred technical solution of the present invention, in S141, when there is no corresponding data record whose mean value is less than the mean threshold value, the following steps are performed:

[0021] S1411, based on all data records, check whether there is a data record whose corresponding second difference value is less than a preset difference value threshold value, if not, re-acquire the historical power consumption record, jump to S11, if yes, continue to check whether the data record whose corresponding second difference value is less than the difference value threshold value is unique, if yes, take the data record whose corresponding second difference value is less than the difference value threshold value as the final model, if not, continue to S1412;

[0022] S1412. Among all data records whose corresponding second difference values ​​are less than the difference value threshold, check whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to S11. If yes, continue to check whether the data records with corresponding identification data of 1 or 0 are unique. If yes, take the preset model corresponding to the data records with corresponding identification data of 1 or 0 as the final model. If not, among all data records with corresponding identification data of 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

[0023] As a preferred technical solution of the present invention, in S4, the information collection main station module secretly sends a control command to the concentrator module, including the following steps:

[0024] S41, storing initial values ​​in advance in the information collection main station module and the concentrator module, and the information collection main station module and the concentrator module start accumulation processing at the same time;

[0025] S42, the information collection master station module generates a first value, connects its own characteristic value with the first value to obtain a first connection value, performs a preset operation on the initial value and the characteristic value to obtain an operation result value, uses the operation result value to perform a secret operation on the first connection value to obtain a first secret value, and sends the first secret value to the concentrator module;

[0026] S43, the concentrator module receives the first secret value, adjusts its own characteristic value, restores the first value from the first secret value, generates a second value, uses the restored first value to perform a secret operation on the second value to obtain a second secret value, and sends the second secret value to the information collection main station module;

[0027] S44, the information acquisition main station module receives the second secret value, uses its own first numerical value to perform a recovery operation on the second secret value to obtain a second numerical value, and the information acquisition main station module uses the obtained second numerical value to perform a secret operation on the control command, and sends the secret operation result value to the concentrator module, and the concentrator module uses its own second numerical value to perform a recovery operation on the secret operation result value to obtain the control command.

[0028] As a preferred technical solution of the present invention, the process of the accumulation processing refers to increasing the characteristic value by 1 every time a preset fixed time passes.

[0029] As a preferred technical solution of the present invention, in S43, the concentrator module receives the first secret value, adjusts its own characteristic value, and recovers the first value from the first secret value, including the following steps:

[0030] S431, the concentrator module adjusts its own characteristic value, performs a preset operation on the initial value and the adjusted characteristic value, uses the result value after the preset operation to perform a recovery operation on the first secret value, and intercepts an intermediate result value of a preset length from the result value after the recovery operation;

[0031] S432, the concentrator module determines whether the intermediate result value is the same as the adjusted feature value. If so, in the result value after the recovery operation, the other part except the intermediate result value is regarded as the first value. If not, jump to S431.

[0032] The present invention also provides an AC charging pile orderly charging control device, which mainly includes the following modules:

[0033] The information collection master station module is used to obtain the historical power consumption records of all common power consumption modules based on the current time point, and select a preset model from all preset models as the final model;

[0034] It is also used to determine whether the preset time point has been reached. If not, continue to wait. At the same time, determine whether the preset time point has been reached. If yes, obtain the current total power consumption data of all common power consumption modules, input the current total power consumption data into the final model, and the final model outputs the total power consumption data of all common power consumption modules at the preset future time point, and determine whether the end condition is met. If so, end the processing, and if not, repeat the processing;

[0035] And used to determine the final total power consumption data of all common power consumption modules at a preset future time point according to the total power consumption data output by the final model, and check whether the final total power consumption data is greater than the preset total power consumption data;

[0036] It is also used to send detection information to the charging power controller modules connected to all charging pile modules before the preset future time point arrives, and secretly send control commands to the concentrator module when it is detected that a charging pile module is in use;

[0037] A general power consumption module is used to consume the power transmitted by the power system;

[0038] The concentrator module is used to receive the control command from the information collection master station module and forward the control command to the charging power controller module connected to the corresponding charging pile module;

[0039] A charging pile module is used to connect to the charging power controller module and charge the electric vehicle;

[0040] The charging power controller module is used to connect the electric vehicle and the charging pile module to control the charging process of the electric vehicle.

[0041] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0042] In the present invention, first, the information acquisition main station module obtains the historical power consumption records of all ordinary power consumption modules based on the current time point, and selects a preset model from all preset models as the final model; secondly, the information acquisition main station module determines whether the preset time point has been reached. If so, the current total power consumption data of all ordinary power consumption modules is obtained, and the current total power consumption data is input into the final model, and the final model outputs the total power consumption data of all ordinary power consumption modules at the preset future time point; thirdly, the information acquisition main station module determines the final total power consumption data of all ordinary power consumption modules at the preset future time point according to the total power consumption data output by the final model, and checks whether the final total power consumption data is greater than the preset total power consumption data; finally, before the preset future time point is reached, the information acquisition main station module sends detection information to the charging power controller module connected to all charging pile modules, and when it is detected that a charging pile module is in use, the control command is secretly sent to the concentrator module, and the control command is forwarded by the concentrator module to the charging power controller module connected to the corresponding charging pile module, and the charging power controller module controls the charging process. Through the present invention, not only can the peak time of domestic electricity consumption be accurately estimated, but when the charging pile is used during the peak time of domestic electricity consumption, the charging process can be controlled by sending control commands, thereby avoiding the use of the charging pile affecting the normal use of domestic electricity. In addition, the control commands can be sent secretly to ensure the security of the control commands, and thus the safety of the charging process. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a flow chart of an AC charging pile orderly charging control method of the present invention;

[0044] Figure 2 It is a structural diagram of an AC charging pile orderly charging control device of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0046] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0047] The present invention provides Figure 1The orderly charging control method of an AC charging pile shown is mainly implemented by executing the following steps:

[0048] S1. The information collection master station module obtains the historical power consumption records of all common power consumption modules based on the current time point, and the information collection master station module selects a preset model from all preset models as the final model;

[0049] S2, the information collection master station module determines whether the preset time point has been reached. If not, continue to wait and determine whether the preset time point has been reached. If yes, obtain the current total power consumption data of all common power consumption modules, input the current total power consumption data into the final model, and the final model outputs the total power consumption data of all common power consumption modules at the preset future time point, and determines whether the end condition is met. If so, end this step, and if not, repeat this step;

[0050] S3, the information collection master station module determines the final total power consumption data of all common power consumption modules at a preset future time point according to the total power consumption data output by the final model, and checks whether the final total power consumption data is greater than the preset total power consumption data. If yes, proceed to the next step;

[0051] S4. Before the preset future time point arrives, the information collection main station module sends detection information to the charging power controller modules connected to all charging pile modules. When it is detected that a charging pile module is in use, a control command is secretly sent to the concentrator module. The control command is forwarded by the concentrator module to the charging power controller module connected to the corresponding charging pile module, and the charging process is controlled by the charging power controller module.

[0052] Specifically, in order to realize the orderly use of charging piles for charging, the present invention proposes steps S1 to S4. Steps S1 to S4 are executed once every certain period of time, for example, starting from midnight every day, they are executed once every 15 minutes. In step S1, the information acquisition main station module obtains the historical power consumption records of all common power consumption modules based on the current time point. The common power consumption modules can be household appliances. In order to facilitate the understanding of the historical power consumption records, for example, the current time point is 9:18 am, then the time interval corresponding to the historical power consumption records is 9:00 am to 9:15 am. The historical power consumption records are specifically the total power consumption data of all common power consumption modules at 9:00 am, the total power consumption data at 9:01 am, the total power consumption data at 9:02 am... The information acquisition main station module also selects a preset model from all preset models as the final model. The role of the final model will be described below. In step S2, the information collection main station module determines whether the preset time point has been reached. For the convenience of understanding the preset time point, for example, if the current time point is 9:18 a.m., then the time interval corresponding to the current time point is 9:15 a.m. to 9:30 a.m. In the time interval from 9:15 a.m. to 9:30 a.m., 9:20 a.m. and 9:25 a.m. can be used as preset time points. If any preset time point has not been reached, continue to wait and determine whether the preset time point has been reached. If any time point has been reached, for example, the preset time point of 9:20 a.m. has been reached, Obtain the current total electricity consumption data of all common electricity consumption modules, and continue with the above example, that is, the total electricity consumption data of all common electricity consumption modules at 9:20 am, the total electricity consumption data at 9:19 am..., input the current total electricity consumption data into the final model, and the final model outputs the total electricity consumption data of all common electricity consumption modules at a preset future time point. Continuing with the above example, the preset future time point is 9:30 am, and then determine whether the end condition is met. The end condition may be that all preset time points have been reached. If the end condition is met, end this step. If the end condition is not met, repeat this step.In step S3, the information acquisition main station module determines the final total power consumption data of all common power consumption modules at a preset future time point based on the total power consumption data output by the final model. In this embodiment, the number of preset time points is 2. Of course, the number of preset time points can also be a value other than 2, that is, the final model outputs two total power consumption data, and the average of the two total power consumption data can be taken as the final total power consumption data. Of course, other methods can also be used to determine the final total power consumption data, and then check whether the final total power consumption data is greater than the preset total power consumption data. It should be noted that in this embodiment, the information acquisition main station module, the concentrator module, the common power consumption module, the charging pile module, and the charging power controller module are all in one substation. Considering that the substation transformer usually has a capacity peak, that is, the maximum power that the substation transformer can safely carry under rated conditions, the preset total power consumption data refers to the total power consumption data that can be allocated to all common power consumption modules at a preset future time point without affecting the use of the charging pile. Specifically, it can be the result value after deducting the capacity peak of the substation transformer from the power expected to be allocated to the charging pile. If it is greater, continue to step S4. In step S4, the information collection main station module sends detection information to the charging power controller modules connected to all charging pile modules before the preset future time point arrives. If it is detected that a charging pile module is in use, a control command is secretly sent to the concentrator module, wherein the control command specifically includes the charging power and the charging time. The secret sending method can prevent the control command from being stolen and tampered with, thereby ensuring charging safety. The control command is forwarded by the concentrator module to the charging power controller module connected to the used charging pile module. The used charging pile module controls the charging process through the connected charging power controller module when the preset future time point arrives. The charging power controller module can specifically reduce the charging power.

[0053] Through the above method, when the charging pile is used during the peak period of household electricity consumption, the charging power can be reduced to ensure that it does not affect the normal use of household electricity.

[0054] Furthermore, the information collection main station module selects a preset model from all preset models as the final model, including the following steps:

[0055] S11, determining a preset model from all preset models, performing a first setting on the determined preset model, and generating and storing a data record corresponding to the determined preset model based on the historical power consumption record, wherein the data record includes the determined preset model, the first total power consumption data, the first difference value, the second total power consumption data, and the second difference value;

[0056] S12, resetting the determined preset model, generating a new data record, determining whether the second difference value in the new data record is less than the second difference value in the stored data record, if so, deleting the stored data record, storing the new data record, and continuing to S13, if so, directly continuing to S13;

[0057] S13, judging whether the determined preset model can be reset, if yes, jumping to S12, if no, judging whether all preset models have been determined, if yes, continuing to S14, if no, jumping to S11;

[0058] S14, for each stored data record corresponding to the preset model, setting identification data according to the magnitude of the first difference value and the second difference value in the data record, adding the identification data to the data record, and selecting a final model based on the data records corresponding to all stored preset models;

[0059] Specifically, the main process of the information collection main station module selecting a preset model from all preset models as the final model is introduced here. In step S11, a preset model is determined from all preset models. All preset models can be prediction models in the prior art that can predict future electricity consumption data based on historical electricity consumption data, including but not limited to time series models, regression analysis models, deep learning models, machine learning models and Bayesian models. This embodiment does not impose specific restrictions on all preset models. The determined model can be any preset model. The determined preset model is set for the first time, that is, the value of the operating data in the preset model is set once, for example, the values ​​of p, d, and q are set simultaneously in the ARIMA model, and according to the historical electricity consumption records, the data records corresponding to the determined preset model are generated and stored, wherein the data records include the determined preset model, the first total electricity consumption data, the first difference value, the second total electricity consumption data, the second difference value, and the generation process of the data records will be described below. In step S12, the determined preset model is reset, that is, there is more than one value of the running data, and a new data record is generated at the same time. It is determined whether the second difference value in the new data record is less than the second difference value in the stored data record. If it is less than, the stored data record is deleted, the new data record is stored, and the next step is continued. If it is greater than or equal to, the next step is directly continued. In step S13, it is determined whether the determined preset model can be reset, that is, whether there is still a value of the running data that has not been set. If so, jump to the previous step. If not, it is determined whether all preset models have been determined. If they have been determined, continue to the next step. If not, jump to step S11, determine a new preset model and execute subsequent steps. In step S14, for the data record corresponding to each stored preset model, set the identification data according to the size of the first difference value and the second difference value in the data record, and add the identification data to the data record. The process of setting the identification data will be described below. On this basis, the final model can be selected based on the data records corresponding to all stored preset models. The detailed selection process will be described below. Through the above method, not only the final model can be determined, but also the operating data in the final model can be guaranteed to be optimal.

[0060] Further, in S11, based on the historical electricity consumption records, generating and storing data records corresponding to the determined preset model includes: based on the historical electricity consumption records, inputting the total electricity consumption data of the first preset historical time point and the second preset historical time point contained in the historical electricity consumption records into the final model respectively, the final model outputs the first total electricity consumption data and the second total electricity consumption data of the preset future time point respectively, calculating the first difference value and the second difference value between the first total electricity consumption data and the second total electricity consumption data and the actual total electricity consumption data of the preset future time point respectively, and using the determined preset model, the first total electricity consumption data, the first difference value, the second total electricity consumption data, and the second difference value form a data record.

[0061] Specifically, the process of generating data records corresponding to the preset model is introduced here. First, based on the historical electricity consumption records, the total electricity consumption data of the first preset historical time point and the second preset historical time point contained in the historical electricity consumption records are respectively input into the final model. Continuing with the above example, the historical electricity consumption records are the total electricity consumption data of all ordinary electricity consumption modules every one minute in the time interval from 9 am to 9:15 am, so the first preset historical time point is 9:05 am, and the second preset historical time point is 9:10 am. Secondly, the final model outputs the first total electricity consumption data and the second total electricity consumption data of the preset future time point respectively. Continuing with the above example, the preset future time point is 9:15 am, and the first difference value and the second difference value of the first total electricity consumption data and the second total electricity consumption data and the actual total electricity consumption data at the preset future time point are calculated respectively. The first difference value and the second difference value can be obtained by calculating the absolute value of the difference. Finally, using the determined preset model, the first total electricity consumption data, the first difference value, the second total electricity consumption data, and the second difference value form a data record.

[0062] Further, in S14, setting the identification data according to the size of the first difference value and the second difference value in the data record includes: when the first difference value is greater than the second difference value, setting the identification data to 1; when the first difference value is equal to the second difference value, setting the identification data to 0; when the first difference value is less than the second difference value, setting the identification data to -1.

[0063] Specifically, this describes how to set identification data according to the size of the first difference value and the second difference value in the data record. The setting process includes: if the first difference value is greater than the second difference value, it means that with the passage of time, the output accuracy of the preset model is improving, so the identification data is set to 1; if the first difference value is equal to the second difference value, it means that with the passage of time, the output accuracy of the preset model has not changed, so the identification data is set to 0; if the first difference value is less than the second difference value, it means that with the passage of time, the output accuracy of the preset model is decreasing, so the identification data is set to -1.

[0064] Further, in S14, selecting a final model based on the data records corresponding to all stored preset models includes the following steps:

[0065] S141. Based on all data records, calculate the mean of the first difference value and the second difference value in the data record, and check whether there is a data record whose corresponding mean value is less than a preset mean threshold value. If so, continue to check whether the data record whose corresponding mean value is less than the mean threshold value is unique. If so, take the preset model corresponding to the data record whose corresponding mean value is less than the mean threshold value as the final model. If not, continue to S142.

[0066] S142. Among all data records whose corresponding means are less than the mean threshold, check whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to S11. If yes, continue to check whether the data records with corresponding identification data of 1 or 0 are unique. If yes, take the preset model corresponding to the data records with corresponding identification data of 1 or 0 as the final model. If not, among all data records with corresponding identification data of 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

[0067] Specifically, here we begin to introduce the process of selecting the final model based on the data records corresponding to all the stored preset models. In step S141, among all the stored data records, the mean of the first difference value and the second difference value in the data record is calculated, and then it is determined whether there is a data record with a corresponding mean value less than the preset mean threshold value. If not, the specific method will be described below. If so, it is determined whether the data record with the corresponding mean value less than the mean threshold value is unique. If so, the preset model corresponding to the data record with the corresponding mean value less than the mean threshold value is regarded as the final model. If not, proceed to the next step. In step S142, based on all data records whose corresponding means are less than the mean threshold, determine whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to the above step S11 to continue execution. Continuing with the above example, the time interval corresponding to the historical electricity consumption records is from 9:00 a.m. to 9:15 a.m., then the time interval corresponding to the re-acquired historical electricity consumption records is from 8:45 a.m. to 9:00 a.m. If it exists, determine whether the data record with corresponding identification data of 1 or 0 is unique. If so, take the preset model corresponding to the data record with corresponding identification data of 1 or 0 as the final model. If not, among all data records with corresponding identification data of 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

[0068] Further, in S141, when there is no corresponding data record whose mean value is less than the mean threshold value, the following steps are performed:

[0069] S1411, based on all data records, check whether there is a data record whose corresponding second difference value is less than a preset difference value threshold value, if not, re-acquire the historical power consumption record, jump to S11, if yes, continue to check whether the data record whose corresponding second difference value is less than the difference value threshold value is unique, if yes, take the data record whose corresponding second difference value is less than the difference value threshold value as the final model, if not, continue to S1412;

[0070] S1412. In all data records whose corresponding second difference values ​​are less than the difference value threshold, check whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to S11. If yes, continue to check whether the data records with corresponding identification data of 1 or 0 are unique. If yes, take the preset model corresponding to the data records with corresponding identification data of 1 or 0 as the final model. If not, in all data records whose corresponding identification data are 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

[0071] Specifically, the steps to be performed when there is no corresponding data record with a mean value less than the mean threshold are introduced here. In step S1411, based on all the stored data records, it is determined whether there is a data record with a corresponding second difference value less than the preset difference value threshold. If not, the historical power consumption record is re-acquired, and the above step S11 is jumped to continue execution. If it exists, it is determined whether the corresponding data record with a second difference value less than the difference value threshold is unique. If yes, the data record with a corresponding second difference value less than the difference value threshold is regarded as the final model. If not, the next step is continued. In step S1412, among all the data records with a corresponding second difference value less than the difference value threshold, it is determined whether there is a corresponding data record with a corresponding identification data of 1 or 0. If not, the historical power consumption record is re-acquired, and the above step S11 is jumped to continue execution. If yes, it is determined whether the corresponding data record with an identification data of 1 or 0 is unique. If unique, the preset model corresponding to the data record with the corresponding identification data of 1 or 0 is regarded as the final model. If not unique, the preset model corresponding to the data record with the corresponding smallest second difference value among all the data records with the corresponding identification data of 1 or 0 is regarded as the final model. Through the above method, the best preset model can be selected from all the preset models as the final model, so that the final model can accurately estimate the peak time of household electricity consumption.

[0072] Further, in S4, the information collection master station module secretly sends a control command to the concentrator module, including the following steps:

[0073] S41, storing initial values ​​in advance in the information collection main station module and the concentrator module, and the information collection main station module and the concentrator module start accumulation processing at the same time;

[0074] S42, the information collection main station module generates a first value, connects its own characteristic value and the first value to obtain a first connection value, performs a preset operation on the initial value and the characteristic value to obtain an operation result value, uses the operation result value to perform a secret operation on the first connection value to obtain a first secret value, and sends the first secret value to the concentrator module;

[0075] S43, the concentrator module receives the first secret value, adjusts its own characteristic value, recovers the first value from the first secret value, generates a second value, performs a secret operation on the second value using the recovered first value to obtain a second secret value, and sends the second secret value to the information collection main station module;

[0076] S44, the information collection main station module receives the second secret value, uses its own first value to perform a recovery operation on the second secret value to obtain a second value, and uses the obtained second value to perform a secret operation on the control command, and sends the secret operation result value to the concentrator module, and the concentrator module uses its own second value to perform a recovery operation on the secret operation result value to obtain the control command;

[0077] Furthermore, the accumulation process refers to increasing the characteristic value by 1 every time a preset fixed time passes.

[0078] Specifically, the process of the information collection main station module secretly sending a control command to the concentrator module is introduced here. In step S41, the same initial value is stored in advance in the information collection main station module and the concentrator module, and the information collection main station module and the concentrator module start to perform accumulation processing at the same time. The accumulation processing process includes increasing the pre-stored characteristic value by 1 every preset fixed time, for example, the fixed time is 5 seconds. It should be noted that the characteristic values ​​initially stored in the information collection main station module and the concentrator module are the same. In step S42, the information collection main station module generates a first value, which can be obtained by an algorithm in the prior art such as the linear congruential method and the Mersenne rotation algorithm, connects its own characteristic value with the first value to obtain a first connection value, performs a preset operation on the initial value and the characteristic value to obtain an operation result value, the preset operation can be an exclusive operation, uses the operation result value to perform a secret operation on the first connection value to obtain a first secret value, and then sends the first secret value to the concentrator module. The secret operation is an encryption operation performed using an algorithm in the prior art such as RC4. In step S43, the concentrator module receives the first secret value, adjusts its own characteristic value, recovers the first value from the first secret value, and the specific recovery process will be described below, and generates a second value. The method for generating the second value is the same as the method for generating the first value. The second value is secret-operated using the recovered first value to obtain the second secret value, and then the second secret value is sent to the information acquisition main station module. In step S44, the information acquisition main station module receives the second secret value, and uses its own first value to perform a recovery operation on the second secret value to obtain the second value. The recovery operation is the inverse operation of the secret operation. At this point, the information acquisition main station module and the concentrator module have safely shared the second value. On this basis, the information acquisition main station module uses the obtained second value to perform a secret operation on the control command, and sends the secret operation result value to the concentrator module. The concentrator module uses its own second value to perform a recovery operation on the secret operation result value to obtain the control command. Through the above method, the safe sharing of the second value can be guaranteed, and the security of the control command can also be ensured.

[0079] Further, in S43, the concentrator module receives the first secret value, adjusts its own characteristic value, and restores the first value from the first secret value, including the following steps:

[0080] S431, the concentrator module adjusts its own characteristic value, performs a preset operation on the initial value and the adjusted characteristic value, uses the result value after the preset operation to perform a recovery operation on the first secret value, and intercepts an intermediate result value of a preset length from the result value after the recovery operation;

[0081] S432, the concentrator module determines whether the intermediate result value is the same as the adjusted feature value. If so, in the result value after the recovery operation, the other part except the intermediate result value is regarded as the first value. If not, jump to S431.

[0082] Specifically, the above recovery process is introduced here. Before the introduction, it should be explained that although the characteristic values ​​stored in the information collection main station module and the concentrator module are the same at first, after a period of time, the characteristic values ​​stored in the information collection main station module and the characteristic values ​​stored in the concentrator module may deviate, and the deviation is usually within a certain range, so the concentrator module needs to adjust its own characteristic value. In step S431, the concentrator module adjusts its own characteristic value, for example, increases or decreases the characteristic value by 1, performs a preset operation on the initial value and the adjusted characteristic value, uses the result value after the preset operation to perform a recovery operation on the first secret value, and intercepts the intermediate result value of the preset length from the result value after the recovery operation. The preset length is actually the length of the characteristic value, and the length of the characteristic value can be set to a fixed 40 bits in advance. In step S432, the concentrator module determines whether the intermediate result value is the same as the adjusted characteristic value. If the same, in the result value after the recovery operation, the other parts except the intermediate result value are regarded as the first value. If they are not the same, jump to the previous step to continue execution.

[0083] References Figure 2 As shown, the present invention also provides an AC charging pile orderly charging control device, including an information collection main station module, a general power consumption module, a concentrator module, a charging pile module, and a charging power controller module, which is used to implement an AC charging pile orderly charging control method as described above.

[0084] The functions of each module are as follows:

[0085] The information collection master station module is used to obtain the historical power consumption records of all common power consumption modules based on the current time point, and select a preset model from all preset models as the final model;

[0086] It is also used to determine whether the preset time point has been reached. If not, continue to wait. At the same time, determine whether the preset time point has been reached. If yes, obtain the current total power consumption data of all common power consumption modules, input the current total power consumption data into the final model, and the final model outputs the total power consumption data of all common power consumption modules at the preset future time point, and determine whether the end condition is met. If so, end the processing, and if not, repeat the processing;

[0087] And used to determine the final total power consumption data of all common power consumption modules at a preset future time point according to the total power consumption data output by the final model, and check whether the final total power consumption data is greater than the preset total power consumption data;

[0088] It is also used to send detection information to the charging power controller modules connected to all charging pile modules before the preset future time point arrives, and secretly send control commands to the concentrator module when it is detected that a charging pile module is in use;

[0089] A general power consumption module is used to consume the power transmitted by the power system;

[0090] The concentrator module is used to receive the control command from the information collection master station module and forward the control command to the charging power controller module connected to the corresponding charging pile module;

[0091] A charging pile module is used to connect to the charging power controller module and charge the electric vehicle;

[0092] The charging power controller module is used to connect the electric vehicle and the charging pile module to control the charging process of the electric vehicle.

[0093] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0094] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The above-mentioned program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0095] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0096] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0097] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for controlling orderly charging of an AC charging pile, characterized in that: The method comprises the following steps: S1. The information collection main station module obtains the historical power consumption records of all common power consumption modules based on the current time point, and the information collection main station module selects a preset model from all preset models as the final model; S2, the information collection master station module determines whether the preset time point has been reached. If not, continue to wait and determine whether the preset time point has been reached. If yes, obtain the current total power consumption data of all the common power consumption modules, input the current total power consumption data into the final model, and the final model outputs the total power consumption data of all the common power consumption modules at the preset future time point, and determines whether the end condition is met. If so, end this step, and if not, repeat this step; S3, the information collection master station module determines the final total power consumption data of all the common power consumption modules at a preset future time point according to the total power consumption data output by the final model, and checks whether the final total power consumption data is greater than the preset total power consumption data. If yes, proceed to the next step; S4. Before the preset future time point arrives, the information collection main station module sends detection information to the charging power controller modules connected to all charging pile modules. When it is detected that the charging pile modules are in use, the control command is secretly sent to the concentrator module. The control command is forwarded by the concentrator module to the charging power controller module connected to the corresponding charging pile module, and the charging process is controlled by the charging power controller module.

2. The method for controlling orderly charging of an AC charging pile according to claim 1, characterized in that: In S1, the information collection main station module selects a preset model from all preset models as the final model, including the following steps: S11, determining a preset model from all preset models, performing a first setting on the determined preset model, and generating and storing a data record corresponding to the determined preset model based on the historical power consumption record, wherein the data record includes the determined preset model, the first total power consumption data, the first difference value, the second total power consumption data, and the second difference value; S12, resetting the determined preset model, generating a new data record, determining whether the second difference value in the new data record is less than the second difference value in the stored data record, if so, deleting the stored data record, storing the new data record, and continuing to S13, if so, directly continuing to S13; S13, judging whether the determined preset model can be reset, if yes, jumping to S12, if no, judging whether all preset models have been determined, if yes, continuing to S14, if no, jumping to S11; S14. For each data record corresponding to the stored preset model, identification data is set according to the size of the first difference value and the second difference value in the data record, the identification data is added to the data record, and the final model is selected based on the data records corresponding to all the stored preset models.

3. The method for controlling orderly charging of an AC charging pile according to claim 2, characterized in that: In S11, based on the historical electricity consumption records, generating and storing data records corresponding to the determined preset model includes: based on the historical electricity consumption records, inputting the total electricity consumption data of the first preset historical time point and the second preset historical time point contained in the historical electricity consumption records into the final model respectively, the final model outputs the first total electricity consumption data and the second total electricity consumption data of the preset future time point respectively, calculating the first difference value and the second difference value between the first total electricity consumption data and the second total electricity consumption data and the actual total electricity consumption data of the preset future time point respectively, and using the determined preset model, the first total electricity consumption data, the first difference value, the second total electricity consumption data, and the second difference value form a data record.

4. The method for controlling orderly charging of an AC charging pile according to claim 2, characterized in that: In the S14, setting the identification data according to the size of the first difference value and the second difference value in the data record includes: when the first difference value is greater than the second difference value, setting the identification data to 1; when the first difference value is equal to the second difference value, setting the identification data to 0; when the first difference value is less than the second difference value, setting the identification data to -1.

5. The method for controlling orderly charging of an AC charging pile according to claim 4, characterized in that: In S14, selecting the final model based on the data records corresponding to all stored preset models includes the following steps: S141. Based on all data records, calculate the mean of the first difference value and the second difference value in the data record, and check whether there is a data record whose corresponding mean value is less than a preset mean threshold value. If so, continue to check whether the data record whose corresponding mean value is less than the mean threshold value is unique. If so, take the preset model corresponding to the data record whose corresponding mean value is less than the mean threshold value as the final model. If not, continue to S142. S142. Among all data records whose corresponding means are less than the mean threshold, check whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to S11. If yes, continue to check whether the data records with corresponding identification data of 1 or 0 are unique. If yes, take the preset model corresponding to the data records with corresponding identification data of 1 or 0 as the final model. If not, among all data records with corresponding identification data of 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

6. The method for controlling orderly charging of an AC charging pile according to claim 5, characterized in that: In the S141, when there is no corresponding data record whose mean value is less than the mean value threshold, the following steps are performed: S1411, based on all data records, check whether there is a data record whose corresponding second difference value is less than a preset difference value threshold value, if not, re-acquire the historical power consumption record, jump to S11, if yes, continue to check whether the data record whose corresponding second difference value is less than the difference value threshold value is unique, if yes, take the data record whose corresponding second difference value is less than the difference value threshold value as the final model, if not, continue to S1412; S1412. Among all data records whose corresponding second difference values ​​are less than the difference value threshold, check whether there are data records with corresponding identification data of 1 or 0. If not, re-acquire the historical electricity consumption records and jump to S11. If yes, continue to check whether the data records with corresponding identification data of 1 or 0 are unique. If yes, take the preset model corresponding to the data records with corresponding identification data of 1 or 0 as the final model. If not, among all data records with corresponding identification data of 1 or 0, take the preset model corresponding to the data record with the smallest second difference value as the final model.

7. The method for controlling orderly charging of an AC charging pile according to claim 1, characterized in that: In S4, the information collection main station module secretly sends a control command to the concentrator module, including the following steps: S41, storing initial values ​​in advance in the information collection main station module and the concentrator module, and the information collection main station module and the concentrator module start accumulation processing at the same time; S42, the information collection master station module generates a first value, connects its own characteristic value with the first value to obtain a first connection value, performs a preset operation on the initial value and the characteristic value to obtain an operation result value, uses the operation result value to perform a secret operation on the first connection value to obtain a first secret value, and sends the first secret value to the concentrator module; S43, the concentrator module receives the first secret value, adjusts its own characteristic value, recovers the first value from the first secret value, generates a second value, performs a secret operation on the second value using the recovered first value to obtain a second secret value, and sends the second secret value to the information collection main station module; S44, the information acquisition main station module receives the second secret value, uses its own first numerical value to perform a recovery operation on the second secret value to obtain a second numerical value, and the information acquisition main station module uses the obtained second numerical value to perform a secret operation on the control command, and sends the secret operation result value to the concentrator module, and the concentrator module uses its own second numerical value to perform a recovery operation on the secret operation result value to obtain the control command.

8. The method for controlling orderly charging of an AC charging pile according to claim 7, characterized in that: The accumulation process refers to increasing the characteristic value by 1 every time a preset fixed time passes.

9. The method for controlling orderly charging of an AC charging pile according to claim 8, characterized in that: In S43, the concentrator module receives the first secret value, adjusts its own characteristic value, and restores the first value from the first secret value, including the following steps: S431, the concentrator module adjusts its own characteristic value, performs a preset operation on the initial value and the adjusted characteristic value, uses the result value after the preset operation to perform a recovery operation on the first secret value, and intercepts an intermediate result value of a preset length from the result value after the recovery operation; S432, the concentrator module determines whether the intermediate result value is the same as the adjusted feature value. If so, in the result value after the recovery operation, the other part except the intermediate result value is regarded as the first value. If not, jump to S431.

10. An AC charging pile orderly charging control device, used to implement the method according to any one of claims 1 to 9, characterized in that: Includes the following modules: The information collection master station module is used to obtain the historical power consumption records of all common power consumption modules based on the current time point, and select a preset model from all preset models as the final model; It is also used to determine whether the preset time point has been reached. If not, continue to wait. At the same time, determine whether the preset time point has been reached. If yes, obtain the current total power consumption data of all common power consumption modules, input the current total power consumption data into the final model, and the final model outputs the total power consumption data of all common power consumption modules at the preset future time point, and determine whether the end condition is met. If so, end the processing, and if not, repeat the processing; And used to determine the final total power consumption data of all common power consumption modules at a preset future time point according to the total power consumption data output by the final model, and check whether the final total power consumption data is greater than the preset total power consumption data; It is also used to send detection information to the charging power controller modules connected to all charging pile modules before the preset future time point arrives, and secretly send control commands to the concentrator module when it is detected that a charging pile module is in use; A general power consumption module is used to consume the power transmitted by the power system; The concentrator module is used to receive the control command from the information collection master station module and forward the control command to the charging power controller module connected to the corresponding charging pile module; A charging pile module is used to connect to the charging power controller module and charge the electric vehicle; The charging power controller module is used to connect the electric vehicle and the charging pile module to control the charging process of the electric vehicle.

Images