Method and device for determining charging facility acceptance capacity of distribution network node

Abstract

The present application relates to a method, device, computer equipment and storage medium for determining the charging facility acceptance capacity of a distribution network node. The method includes: for any node, determining the target value interval of the charging facility acceptance capacity of the node; calculating by taking values ​​from the target value interval, continuously reducing the range of the target value interval until the selected target value interval meets the preset conditions; and determining the final value of the charging facility acceptance capacity of the node according to the target value interval finally selected. Compared with the prior art, since the charging facility acceptance capacity can be improved, the problem of distribution network expansion caused by the addition of new charging facilities can be alleviated, thereby improving the resource utilization rate of the distribution network and saving costs.

Description

Technical Field

[0001] The present application relates to the technical field of distribution network, and in particular to a method, device, computer equipment and storage medium for determining the charging facility acceptance capacity of a distribution network node. Background Art

[0002] With the development of electric vehicles, charging piles as a medium for obtaining energy have also developed rapidly. In the future, the scale of charging piles will continue to expand, and the demand for more charging pile construction will put a certain burden on the original distribution network. In related technologies, the traditional method is mainly used to obtain the charging facility acceptance capacity of the distribution network node, that is, by calculating the difference between the total capacity of the distribution network and the capacity occupied by the existing facilities of the distribution network, to obtain the charging facility acceptance capacity of the distribution network node. Among them, the capacity occupied by the existing facilities of the distribution network is related to the original load and charging load brought by the existing facilities of the distribution network.

[0003] Since the difference calculated by the above traditional method is actually calculated under the assumption that the capacity occupied by the existing facilities of the distribution network is used, and in reality the existing facilities of the distribution network cannot be used all the time, the charging facility acceptance capacity calculated above will be more conservative than the actual situation. At this time, if the distribution network resources are configured based on the acceptance capacity calculated above, the utilization rate of the distribution network resources will be reduced. If the distribution network is expanded for this reason, the cost will be increased. Summary of the invention

[0004] Based on this, it is necessary to provide a method, computer equipment and storage medium that can determine the charging facility acceptance capacity of a distribution network node in response to the above technical problems.

[0005] A method for determining charging facility acceptance capacity of a distribution network node, the method comprising:

[0006] For any node, determine the target value range of the charging facility acceptance capacity of the node;

[0007] Select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0008] Based on the final selected target value range, the final value of the charging facility acceptance capacity of any node is determined.

[0009] In one embodiment, calculating the limit-crossing judgment results of different values ​​includes:

[0010] Obtain the total load, charging load and grid information of the distribution network at every historical moment;

[0011] According to the total load and charging load at each historical moment, the total load characteristics and charging load characteristics at each evaluation moment are obtained;

[0012] Calculate the ratio between the total load characteristic at each evaluation moment and the total number of nodes in the distribution network as the input load of the node at each evaluation moment;

[0013] Normalizing the charging load characteristics at all evaluation moments to obtain a normalized value of the charging load at each evaluation moment;

[0014] For any value, the newly added charging load at each evaluation time is calculated based on the value and the normalized value of the charging load at different evaluation times;

[0015] According to the grid information, the newly added charging load at each evaluation moment and the input load at each evaluation moment, the predicted values ​​of the three prediction parameters of the node at each evaluation moment are calculated. The three prediction parameters are the node voltage per unit value, feeder current and network loss rate.

[0016] Determine the target values ​​corresponding to the three preset parameters of the node according to the predicted values ​​of the three prediction parameters at all evaluation moments of the node;

[0017] The over-limit judgment result of the value is determined according to the target values ​​corresponding to the three preset parameters of the node.

[0018] In one embodiment, the historical moments are divided into historical time periods of a preset length, and the division method of the historical moments between different historical time periods is the same; accordingly, according to the total load and charging load at each historical moment, the total load characteristics and charging load characteristics at each evaluation moment are obtained, including:

[0019] According to the total load and charging load at each historical moment in each historical time period, the total load characteristics and charging load characteristics at each evaluation moment in the evaluation time period of a preset length are calculated respectively; wherein the division method of the evaluation moments in the evaluation time period is the same as the division method of the historical moments in the historical time period.

[0020] In one embodiment, the charging load characteristics at all historical moments are normalized to obtain a normalized value of the charging load at each evaluation moment, including:

[0021] According to the charging load characteristics at each evaluation moment, determining the maximum value and the minimum value of the charging load characteristics;

[0022] According to the charging load characteristics, maximum value and minimum value at each evaluation moment, the normalized value of the charging load at each evaluation moment is calculated.

[0023] In one embodiment, for any value, the newly added charging load at each evaluation time is calculated according to the value and the normalized value of the charging load at different evaluation times, including:

[0024]

[0025] In the above formula (2), P add (t) represents the newly added charging load at the evaluation time t, P jie Represents any value, Represents the normalized value of the charging load at the evaluation time t.

[0026] In one embodiment, based on the grid information, the newly added charging load at each evaluation time, and the input load at each evaluation time, the predicted values ​​of the three prediction parameters of any node at each evaluation time are calculated, including:

[0027] For any evaluation time, the newly added charging load and the input load at any evaluation time are added to obtain the total input load at any evaluation time;

[0028] According to the grid information and the total input load at each evaluation moment, the power flow calculation is performed to obtain the predicted values ​​of the three prediction parameters of any node at each evaluation moment.

[0029] In one embodiment, according to the predicted values ​​of the three prediction parameters at all evaluation moments, the target values ​​corresponding to the three preset parameters are determined, including:

[0030] Determine the minimum value from the node voltage per unit values ​​at all evaluation moments and use it as the target value of the node voltage per unit value;

[0031] Determine the maximum value from the feeder currents at all evaluation moments and use it as the target value of the feeder current;

[0032] The maximum value is determined from the network loss rates at all evaluation moments and is used as the target value of the network loss rate.

[0033] In one embodiment, according to the target values ​​corresponding to the three preset parameters, determining the limit-crossing judgment result of any value includes:

[0034] Determine whether each of the target values ​​corresponding to the three preset parameters exceeds the limit;

[0035] If any of the target values ​​corresponding to the three preset parameters exceeds the limit, it is determined that any value exceeds the limit. If no target value exceeds the limit among the target values ​​corresponding to the three preset parameters, it is determined that any value does not exceed the limit.

[0036] In one embodiment, determining whether each of the target values ​​corresponding to the three preset parameters exceeds a limit includes:

[0037] If the target value of the node voltage per unit value is less than the minimum voltage lower limit, it is determined that the target value of the node voltage per unit value exceeds the limit;

[0038] If the target value of the feeder current is greater than the feeder current carrying capacity, it is determined that the target value of the feeder current exceeds the limit;

[0039] If the target value of the network loss rate is less than the network loss rate specified in the national standard, it is determined that the target value of the network loss rate exceeds the limit.

[0040] A device for determining charging facility acceptance capacity at a distribution network node, the device comprising:

[0041] A target value interval determination module, used to determine, for any node, a target value interval of the charging facility acceptance capacity of the node;

[0042] A target value interval screening module is used to select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, and repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0043] The final value determination module is used to determine the final value of the charging facility acceptance capacity of the node according to the target value interval finally screened out.

[0044] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0045] For any node, determine the target value range of the charging facility acceptance capacity of the node;

[0046] Select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0047] Based on the final selected target value range, the final value of the charging facility acceptance capacity of the node is determined.

[0048] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0049] For any node, determine the target value range of the charging facility acceptance capacity of the node;

[0050] Select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0051] Based on the final selected target value range, the final value of the charging facility acceptance capacity of the node is determined.

[0052] The above-mentioned method, device, computer equipment and storage medium for determining the charging facility acceptance capacity of the distribution network node, for any node, determine the target value range of the charging facility acceptance capacity of the node; select different values ​​of the charging facility acceptance capacity of the node within the target value range, calculate the over-limit judgment results of each different value, and form different intervals according to the size of the values ​​of each different value, and re-screen from the composed intervals the interval in which the over-limit judgment result of the lower limit is not over-limit and the over-limit judgment result of the upper limit is over-limit, as the target value range, repeat the above-mentioned process of selecting values ​​from the target value range, calculating the over-limit judgment result of the selected values, and re-screening the target value range from the interval composed of the values ​​until the screened target value range meets the preset conditions; according to the target value range finally screened, determine the final value of the charging facility acceptance capacity of the node.

[0053] Compared with the related art of obtaining the charging facility acceptance capacity of the distribution network node by calculating the difference between the total capacity of the distribution network and the capacity occupied by the existing facilities of the distribution network, the method of the present invention can improve the charging facility acceptance capacity and alleviate the distribution network expansion problem caused by the addition of new charging facilities, thereby improving the utilization rate of distribution network resources and saving costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of an application scenario of a method for determining charging facility acceptance capacity of a distribution network node in an embodiment;

[0055] Figure 2 A schematic diagram of a flow chart of a method for determining the charging facility acceptance capacity of a distribution network node in one embodiment;

[0056] Figure 3 A flowchart of a method for determining the charging facility acceptance capacity of a distribution network node in another embodiment;

[0057] Figure 4 A schematic diagram of a grid structure in an embodiment;

[0058] Figure 5 A schematic diagram of calculating the charging facility acceptance capacity using the method of the present invention and the traditional method in one embodiment;

[0059] Figure 6 A structural block diagram of a device for determining charging facility acceptance capacity of a distribution network node in one embodiment;

[0060] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application 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 application and are not used to limit the present application.

[0062] It is understood that the terms "first", "second", etc. used in this application can be used in this article to describe various professional terms, but unless otherwise specified, these professional terms are not limited by these terms. These terms are only used to distinguish one professional term from another professional term. For example, without departing from the scope of this application, the third preset threshold and the fourth preset threshold can be the same or different.

[0063] With the development of electric vehicles, charging piles as a medium for obtaining energy have also developed rapidly. In the future, the scale of charging piles will continue to expand, and the demand for more charging piles will put a certain burden on the original distribution network. In related technologies, the traditional method is mainly used to obtain the charging facility acceptance capacity of the distribution network node, that is, by calculating the difference between the total capacity of the distribution network and the capacity occupied by the existing facilities of the distribution network, to obtain the charging facility acceptance capacity of the distribution network node.

[0064] Since the difference calculated by the above traditional method is actually calculated under the assumption that the capacity occupied by the existing facilities of the distribution network is used, and in reality the existing facilities of the distribution network cannot be used all the time, the charging facility acceptance capacity calculated above will be more conservative than the actual situation. At this time, if the distribution network resources are configured based on the acceptance capacity calculated above, the utilization rate of the distribution network resources will be reduced. If the distribution network is expanded for this reason, the cost will be increased.

[0065] In view of the problems existing in the above-mentioned related technologies, an embodiment of the present invention provides a method for determining the charging facility acceptance capacity of a distribution network node, which can be applied to Figure 1 In the application environment shown, the terminal 101 communicates with the server 102 through a network. The terminal 101 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices, and the server 102 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0066] The server 102 stores the target value interval of the charging facility acceptance capacity of any node. The terminal 101 collects the total load, charging load and grid information of the distribution network at each historical moment and sends them to the server 102. The server 102 selects different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculates the over-limit judgment results of each different value, and forms different intervals according to the value size of each different value. The interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit is re-screened from the composed interval as the target value interval, and repeats the above process of selecting values ​​from the target value interval, calculating the over-limit judgment result of the selected values, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions; according to the target value interval finally screened, the final value of the charging facility acceptance capacity of the node is determined.

[0067] In one embodiment, Figure 2 As shown, a charging facility acceptance capacity method for a distribution network node is provided, and the method is applied to Figure 1 The application scenario in is taken as an example to illustrate, including the following steps:

[0068] 201. For any node, determine the target value range of the charging facility acceptance capacity of the node;

[0069] 202. Select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, and repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0070] 203. According to the target value interval finally screened out, determine the final value of the charging facility acceptance capacity of any node.

[0071] In the above step 201, the charging facility acceptance capacity of the node refers to the capacity of the charging facilities allowed to be added at the node in the distribution network. The target value range of the charging equipment acceptance capacity of the node refers to the value range of the capacity of the charging facilities allowed to be added at the node in the distribution network, wherein, when the value of the charging facility acceptance capacity is the lower limit of the target value range, the over-limit result should be no over-limit. When the value of the charging facility acceptance capacity is the upper limit of the target value range, the over-limit result should be over-limit. For example, the lower limit of the value range can be 0, and the upper limit can be the maximum capacity of the distribution network.

[0072] In the above step 202, it is possible to determine whether the value of the charging facility's acceptance capacity exceeds the limit in the operation simulation by means of a distribution network operation simulation.

[0073] In the above step 203, the upper limit of the target value range finally screened out can be used as the final value of the charging facility acceptance capacity of the node, the lower limit of the target value range finally screened out can be used as the final value of the charging facility acceptance capacity of the node, and any value can be selected from the target value range finally screened out as the final value of the charging facility acceptance capacity of the node.

[0074] For ease of understanding, the overall process of steps 201 to 203 is now described by way of example. Assume that the number of values ​​selected each time is 3, and the preset condition is that the difference between the upper limit and the lower limit of the target value interval is less than 10. -4 Take it as an example, the above process is as follows: select the lower limit of the target value interval as P jie小 , select the upper limit as P jie大 , take the mean of the sum of the upper and lower limits as the median, and record it as P jie中 Among them, it should be understood that Pjie小 , P jie中 and P jie大 Increase successively.

[0075] After selecting the above three values, the over-limit judgment results corresponding to the three values ​​can be calculated, and two different intervals [P jie小 ,P jie中 ] and [P jie中 , P jie大 ], select the interval with the lower limit judgment result of not exceeding the limit and the upper limit judgment result of exceeding the limit from these two intervals as the new target value interval. Referring to the above process, continue to process the new target value interval until the difference between the upper limit and the lower limit of the target value interval is less than 10 -4 , the above process is stopped and the final selected target value interval is obtained. The upper limit is selected from the final selected target value interval as the final value of the charging facility acceptance capacity of the node.

[0076] The method provided in the embodiment of the present invention determines the target value interval through multiple iterative screening processes, and determines a value from the target value interval determined by the multiple iterative screening processes as the charging facility acceptance capacity of the node. Compared with directly using the difference between the total capacity of the distribution network and the capacity occupied by the existing facilities of the distribution network as the charging facility acceptance capacity of the distribution network node, the screened value can be more accurate, thereby improving the utilization rate of the distribution network resources. At the same time, it can also reduce the cost of expanding the distribution network.

[0077] In one embodiment, if Figure 3 As shown, the embodiment of the present invention does not specifically limit the method of calculating the limit-crossing judgment results of different values, including but not limited to:

[0078] 301. Obtain the total load, charging load and grid information of the distribution network at each historical moment.

[0079] 302. According to the total load and charging load at each historical moment, obtain the total load characteristics and charging load characteristics at each evaluation moment.

[0080] 303. Calculate the ratio between the total load characteristic at each evaluation moment and the total number of nodes in the distribution network as the input load of the node at each evaluation moment.

[0081] 304. Normalize the charging load characteristics at all evaluation moments to obtain a normalized charging load value at each evaluation moment.

[0082] 305. For any value, calculate the additional charging load at each evaluation time according to the value and the normalized value of the charging load at different evaluation times.

[0083] 306. According to the grid information, the newly added charging load at each evaluation moment and the input load at each evaluation moment, the predicted values ​​of three prediction parameters of the node at each evaluation moment are calculated. The three prediction parameters are the node voltage per unit value, the feeder current and the network loss rate.

[0084] 307. Determine the target values ​​corresponding to the three preset parameters of the node respectively according to the predicted values ​​of the three prediction parameters of the node at all evaluation moments.

[0085] 308. Determine an over-limit judgment result of the value according to the target values ​​corresponding to the three preset parameters of the node.

[0086] In the above step 301, the total load at each historical moment refers to the total load of all nodes at each moment in the past period of time. Among them, the past period of time can refer to a certain time period in the past, such as a certain day in the past, and a day is a time period. The specific moment can be determined by the time interval for obtaining the load. For example, taking the total load of all nodes at different times in the past day, and the time interval for obtaining the load is 15 minutes as an example, the total load of all nodes at each historical moment obtained is: the total load of all nodes at 0:00 in the past day, the total load of all nodes at 0:15, ..., the total load of all nodes at 23:30 and the total load of all nodes at 23:45.

[0087] The charging load at each historical moment refers to the charging load of all nodes at each moment in the past period of time. Similarly, the past period of time can be specifically the past month, and the past month can be further divided into every day in the past month, and the specific moment can also be determined by the time interval for obtaining the load. For example, taking the charging load of all nodes at different times in the past day, and the acquisition time interval is 15 minutes as an example, the charging load of all nodes at each historical moment obtained are: the charging load of all nodes at 0:00 in the past day, the charging load of all nodes at 0:15,..., the charging load of all nodes at 23:30, and the charging load of all nodes at 23:45. It should be noted that the total load and the charging load acquisition time can be consistent. Grid information refers to the distribution network topology, line impedance and the length of each trunk branch.

[0088] It can be seen from the content of the above embodiment that each historical moment refers to each moment in the past period of time, and the past period of time can refer to a certain time period in the past, such as a certain day in the past, and a day is a time period. Therefore, if in step 301, the total load and charging load of each historical moment in a time period of a preset length in the past are obtained, then in this step 302, when the total load characteristics and charging load characteristics of each evaluation moment are obtained, the total load characteristics and charging load characteristics of each evaluation moment in the time period of the same preset length are also obtained. It should also be noted that the evaluation moment in this step is not a real time, but more as a time scale for summarizing a certain data. For example, the total load at 2 o'clock in the afternoon of each day last month can be summarized and summarized. Therefore, the latter "summarize and summarize at 2 o'clock in the afternoon every day" is the evaluation moment at 2 o'clock in the afternoon, which is mainly used as a time scale for summarizing a certain data, rather than as a real time.

[0089] In the above step 303, it should be noted that, since the total number of nodes in the distribution network is usually fixed, the input load of the node at each evaluation moment is actually determined by the total load characteristics at each evaluation moment.

[0090] In the above step 304, since the charging load characteristics at all evaluation moments are calculated by the charging loads at all historical moments, and there may be abnormal charging loads in the charging loads at all historical moments, there may also be abnormal charging load characteristics in the charging load characteristics at all evaluation moments. The existence of abnormal charging load characteristics will lead to inaccurate charging facility acceptance capacity. Therefore, in order to eliminate abnormal charging load characteristics, the charging load characteristics at all evaluation moments can be normalized.

[0091] In the above step 305, any value may refer to any value of the "various different values" in the above step 202, and the product obtained by multiplying the value with the normalized value of the charging load at different evaluation times is the newly added charging load corresponding to each evaluation time.

[0092] In the above step 306, the node voltage per unit value refers to the ratio of the voltage value at the node to the voltage reference value, the feeder current refers to the operating current of the grid line, and the network loss rate refers to the ratio of the line loss power in the grid to the power at the head end of the grid. Specifically, the newly added charging load at each evaluation moment can be added to the input load of any node at each evaluation moment, and the calculated sum is the total input load of the node at each evaluation moment. Then, based on the grid information and the total input load at each evaluation moment, the predicted values ​​of the three prediction parameters of the node at each evaluation moment are calculated, and the three predicted values ​​are the node voltage per unit value, the feeder current and the network loss rate.

[0093] In the above step 307, the target values ​​corresponding to the three preset parameters are obtained from the predicted values ​​corresponding to the three prediction parameters. More specifically, the minimum value can be determined from the node voltage per unit values ​​at all evaluation moments, and this value is used as the target value of the node voltage per unit value; the maximum value can be determined from the feeder current at all evaluation moments, and this value is used as the target value of the feeder current; the maximum value can be determined from the network loss rate at all evaluation moments, and this value is used as the target value of the network loss rate.

[0094] In the above step 308, before determining the over-limit judgment result of any value, it can be determined whether the target values ​​corresponding to the three preset parameters of any node are over-limited. If the target values ​​corresponding to the three preset parameters do not exceed the limit, the over-limit judgment result of any corresponding value is not over-limited. If the target values ​​corresponding to the three preset parameters exceed the limit, the over-limit judgment result of any corresponding value is over-limited.

[0095] The method provided by the embodiment of the present invention obtains the total load, charging load, grid information and the values ​​selected from the target value range at each historical moment in the past period of time to obtain the over-limit judgment result of the corresponding value, wherein the acquisition time of the total load and the charging load can be kept consistent, so the over-limit judgment result calculated will be more accurate. When the accuracy of the over-limit judgment result is improved, the accuracy of the charging facility's acceptance capacity finally obtained will also be improved, thereby improving the resource utilization of the distribution network.

[0096] In one embodiment, historical moments are divided into historical time periods of preset length, and the division method of historical moments between different historical time periods is the same; accordingly, the embodiment of the present invention does not specifically limit the method of obtaining the total load characteristics and charging load characteristics of each evaluation moment based on the total load and charging load at each historical moment, including but not limited to: according to the total load and charging load at each historical moment in each historical time period, respectively calculating the total load characteristics and charging load characteristics of each evaluation moment in the evaluation time period of preset length; wherein, the division method of the evaluation moments in the evaluation time period is the same as the division method of the historical moments in the historical time period.

[0097] Taking the preset length of one day as an example, the "same division method for historical moments between different historical time periods" mentioned in the above process means that each day in the past period of time is also divided into historical moments in the same way. Specifically, taking "the past period of time" as one year as an example, the above process can refer to the following calculation formula:

[0098]

[0099]

[0100] In the above formulas (3) and (4), P z (t) and P c (t) are the total load characteristics and charging load characteristics at the evaluation time t, respectively, z,i (t) and P c,i (t) are the total load and charging load at time t on the i-th day in the past year, respectively.

[0101] The method provided by the embodiment of the present invention can obtain the total load characteristics and charging load characteristics at each evaluation moment by acquiring the total load and charging load at each moment in the past period of time.

[0102] In one embodiment, the embodiment of the present invention does not specifically limit the method of normalizing the charging load characteristics of all historical moments to obtain the normalized value of the charging load at each evaluation moment, including but not limited to: determining the maximum and minimum values ​​of the charging load characteristics based on the charging load characteristics at each evaluation moment; calculating the normalized value of the charging load at each evaluation moment based on the charging load characteristics, maximum and minimum values ​​at each evaluation moment.

[0103] Specifically, after determining the maximum and minimum values ​​of the charging load characteristics, the process of calculating the normalized value of the charging load at each evaluation moment can refer to the following formula (5):

[0104]

[0105] In the above formula (5), is the normalized value of the charging load at the evaluation time t, P c (t) is the charging load characteristic at the evaluation time t, P max and P min are the maximum and minimum values ​​of the charging load characteristics respectively.

[0106] The method provided by the embodiment of the present invention obtains the normalized value of the charging load at each evaluation moment through the charging load characteristics at each evaluation moment. Since the charging load characteristics at each evaluation moment can be normalized, the accuracy of the charging load characteristics at each evaluation moment can be improved, and thus the accuracy of the charging facility acceptance capacity finally calculated can be improved.

[0107] In one embodiment, for any evaluation moment and any value within the target value range, the embodiment of the present invention does not specifically limit the method of calculating the newly added charging load at each evaluation moment based on any value and the charging load normalization value at different evaluation moments, including but not limited to: for any evaluation moment, multiplying the value by the charging load normalization value at the evaluation moment to obtain the newly added charging load at the evaluation moment. The specific process can be referred to the following formula (6):

[0108]

[0109] In the above formula (6), P add (t) represents the newly added charging load at the evaluation time t, P jie represents any value, P c * (t) represents the normalized value of the charging load at the evaluation time t. For example, if any value is determined and the newly added charging load at the evaluation time 13:00 is required, then any value can be multiplied by the normalized value of the charging load at the evaluation time 13:00 to obtain the newly added charging load at the evaluation time 13:00. Similarly, the newly added charging load at each evaluation time can be obtained.

[0110] The method provided in the embodiment of the present invention can determine the newly added charging load at each evaluation moment through any value and the charging load normalization value at different evaluation moments, thereby obtaining the total input load for the power flow calculation.

[0111] In one of the embodiments, the embodiment of the present invention does not specifically limit the method of calculating the predicted values ​​of the three prediction parameters of any node at each evaluation moment based on the grid information, the newly added charging load at each evaluation moment, and the input load at each evaluation moment, including but not limited to: for any evaluation moment, adding the newly added charging load and the input load at the evaluation moment to obtain the total input load at any evaluation moment; performing power flow calculation based on the grid information and the total input load at each evaluation moment to obtain the predicted values ​​of the three prediction parameters of any node at each evaluation moment.

[0112] Specifically, by performing power flow calculation based on the grid information, the newly added charging load at each evaluation time, and the input load at each evaluation time, the predicted values ​​of the three prediction parameters of the node at each evaluation time can be obtained. For example, for node m and evaluation time t, the grid information, the newly added charging load at evaluation time t, and the input load at evaluation time t can be determined first, and then the power flow calculation can be performed to obtain the predicted values ​​of the three prediction parameters of node m at evaluation time t.

[0113] The method provided by the embodiment of the present invention calculates the power flow through the grid information, the newly added charging load at each evaluation moment, and the input load at each evaluation moment, so that the predicted values ​​of the three prediction parameters of any node at each evaluation moment can be obtained.

[0114] In one of the embodiments, the embodiment of the present invention does not specifically limit the method of determining the target values ​​corresponding to the three preset parameters according to the predicted values ​​of the three prediction parameters at all evaluation moments, including but not limited to: determining the minimum value from the node voltage per unit value at all evaluation moments, and using it as the target value of the node voltage per unit value; determining the maximum value from the feeder current at all evaluation moments, and using it as the target value of the feeder current; determining the maximum value from the network loss rate at all evaluation moments, and using it as the target value of the network loss rate.

[0115] The method provided by the embodiment of the present invention determines the target values ​​of the predicted values ​​of the three prediction parameters at all evaluation moments, thereby obtaining the target values ​​corresponding to the three preset parameters respectively.

[0116] In one of the embodiments, the embodiment of the present invention does not specifically limit the method of determining the over-limit judgment result of any value based on the target values ​​corresponding to each of the three preset parameters, including but not limited to: judging whether each of the target values ​​corresponding to each of the three preset parameters exceeds the limit; if any of the target values ​​corresponding to each of the three preset parameters exceeds the limit, then determining that any of the values ​​exceeds the limit; if no target value exceeds the limit among the target values ​​corresponding to each of the three preset parameters, then determining that any of the values ​​does not exceed the limit.

[0117] The method provided by the embodiment of the present invention can reduce the probability of misjudgment of the over-limit judgment result of the corresponding value, because the over-limit judgment result of the corresponding value is determined by the over-limit judgment results of the target values ​​corresponding to the three preset parameters.

[0118] In one of the embodiments, it is determined whether each of the target values ​​corresponding to the three preset parameters exceeds the limit, including: if the target value of the node voltage per unit value is less than the minimum voltage lower limit, then it is determined that the target value of the node voltage per unit value exceeds the limit; if the target value of the feeder current is greater than the feeder current carrying capacity, then it is determined that the target value of the feeder current exceeds the limit; if the target value of the network loss rate is less than the network loss rate specified in the national standard, then it is determined that the target value of the network loss rate exceeds the limit.

[0119] Among them, the minimum voltage lower limit is 0.93 times the voltage reference value; the network loss rate stipulated by the national standard is 2%. Specifically, the node voltage per unit value refers to the ratio of the voltage value at the node to the voltage reference value; the feeder current refers to the operating current of the grid line; the network loss rate refers to the ratio of the power loss of the line in the grid to the power at the head end of the grid;

[0120] The method provided by the embodiment of the present invention performs over-limit judgment on the target values ​​corresponding to the three preset parameters respectively, thereby obtaining the over-limit judgment results corresponding to the three preset parameters respectively.

[0121] In one embodiment, the present invention does not specifically limit the load rate of the distribution network and the load, including but not limited to: taking a distribution network with 33 grid nodes and a voltage of 10 kV as an example, the grid structure is as follows: Figure 4 As shown, the cross-sectional area of ​​the overhead line is 240mm 2 , reactance and resistance are 0.307Ω / kM and 0.13Ω / kM respectively, the total length of the feeder is 5kM, the lines between the nodes are of equal length, the current carrying capacity of the feeder is 495A, the wiring form is 3-1 wiring, and the goal is to determine the charging facility acceptance capacity of node 16. When the load rate is 0%, 20%, 40%, and 60%, respectively, the charging facility acceptance capacity is calculated using the method of the present invention and the traditional method in the related art. The corresponding charging facility acceptance capacity is as follows: Figure 5 shown.

[0122] from Figure 5 It can be seen that when the load rate of the total load is 0%, there is no peak-shifting of the total load and the charging load. Therefore, the charging facility acceptance capacity obtained by the two methods is the difference between the total capacity of the distribution network and the capacity occupied by the existing facilities of the distribution network. When the load rate of the total load is 20%, 40%, and 60%, respectively, the charging facility acceptance capacity of the node obtained by the method of the present invention is higher than that of the traditional method. Therefore, if the construction planning of the new charging facilities is carried out according to the charging facility acceptance capacity determined by the method of the present invention, the problem of distribution network expansion caused by the new charging facilities can be alleviated, thereby improving the resource utilization rate of the distribution network and saving costs.

[0123] In combination with the contents of the above embodiments, in one embodiment, as Figure 6 As shown, a device for determining the charging facility acceptance capacity of a distribution network node is provided, comprising:

[0124] A target value interval determination module, used to determine, for any node, a target value interval of the charging facility acceptance capacity of the node;

[0125] A target value interval screening module is used to select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, and repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0126] The final value determination module is used to determine the final value of the charging facility acceptance capacity of the node according to the target value interval finally screened out.

[0127] In one embodiment, the device for determining the charging facility acceptance capacity of a distribution network node further includes:

[0128] Load acquisition module, used to obtain the total load, charging load and grid information of the distribution network at each historical moment;

[0129] A load characteristic module is used to obtain the total load characteristics and charging load characteristics at each evaluation moment based on the total load and charging load at each historical moment;

[0130] An input load calculation module is used to calculate the ratio between the total load characteristics at each evaluation moment and the total number of nodes in the distribution network as the input load of the node at each evaluation moment;

[0131] A normalized value calculation module is used to normalize the charging load characteristics at all evaluation moments and calculate the normalized value of the charging load at each evaluation moment;

[0132] A new charging load calculation module is added, which is used for any value, and calculates the new charging load at each evaluation time according to the value and the charging load normalization value at different evaluation times;

[0133] The prediction value calculation module is used to calculate the prediction values ​​of three prediction parameters of the node at each evaluation moment according to the grid information, the newly added charging load at each evaluation moment, and the input load at each evaluation moment. The three prediction parameters are the node voltage per unit value, the feeder current, and the network loss rate;

[0134] A target value determination module is used to determine the target values ​​corresponding to the three preset parameters of the node according to the predicted values ​​of the three prediction parameters at all evaluation moments of the node;

[0135] The over-limit judgment result determination module determines the over-limit judgment result of the value according to the target values ​​corresponding to the three preset parameters of the node.

[0136] In one embodiment, the load characteristic module includes:

[0137] A total load characteristic calculation unit, used to calculate the total load characteristic at each evaluation moment in an evaluation time period of a preset length according to the total load at each historical moment in each historical time period;

[0138] The charging load characteristic calculation unit is used to calculate the charging load characteristic at each evaluation moment in an evaluation time period of a preset length according to the charging load at each historical moment in each historical time period.

[0139] In one embodiment, the normalization value calculation module includes:

[0140] A maximum value determination unit, used to determine the maximum value and the minimum value of the charging load characteristic according to the charging load characteristic at each evaluation moment;

[0141] The normalized value calculation unit is used to calculate the normalized value of the charging load at each evaluation moment according to the charging load characteristics, maximum value and minimum value at each evaluation moment for any value.

[0142] In one embodiment, the newly added charging load calculation module includes:

[0143] For any value, based on the value and the normalized value of the charging load at different evaluation times, the formula for calculating the additional charging load at each evaluation time is:

[0144]

[0145] In the above formula (7), P add (t) represents the newly added charging load at the evaluation time t, P jie Represents any value, Represents the normalized value of the charging load at the evaluation time t.

[0146] In one embodiment, the prediction value calculation module includes:

[0147] A total input load calculation unit, for any evaluation moment, adding the newly added charging load to the input load at any evaluation moment to obtain the total input load at any evaluation moment;

[0148] The power flow calculation unit is used to perform power flow calculation according to the grid information and the total input load at each evaluation moment, and obtain the predicted values ​​of the three prediction parameters of the node at each evaluation moment.

[0149] In one embodiment, the target value determination module includes:

[0150] A first target value determination unit, used to determine a minimum value from the per-unit values ​​of the node voltages at all evaluation moments, and use the minimum value as a target value of the per-unit value of the node voltage;

[0151] A second target value determination unit, used to determine a maximum value from the feeder currents at all evaluation moments and use the maximum value as a target value of the feeder current;

[0152] The third target value determination unit is used to determine a maximum value from the network loss rates at all evaluation moments and use the maximum value as the target value of the network loss rate.

[0153] In one embodiment, the limit-crossing judgment result determination module includes:

[0154] A first over-limit judgment result determination unit, configured to determine that the target value of the node voltage per unit value exceeds the limit if the target value of the node voltage per unit value is less than the minimum voltage lower limit;

[0155] A second over-limit judgment result determination unit is used to determine that the target value of the feeder current exceeds the limit if the target value of the feeder current is greater than the feeder current carrying capacity;

[0156] The third over-limit judgment result determination unit is used to determine that the target value of the network loss rate exceeds the limit if the target value of the network loss rate is less than the network loss rate specified in the national standard.

[0157] The device provided by the embodiment of the present invention determines the target value interval of the charging facility acceptance capacity of any node; selects different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculates the over-limit judgment results of each different value, and forms different intervals by the different values ​​according to the value size, and re-screens the intervals in which the over-limit judgment result of the lower limit is not over-limited and the over-limit judgment result of the upper limit is over-limited from the composed intervals as the target value interval, repeats the above process of selecting values ​​from the target value interval, calculating the over-limit judgment result of the selected values, and re-screening the target value interval from the interval composed of the values, until the selected target value interval meets the preset conditions; according to the target value interval finally screened, the final value of the charging facility acceptance capacity of the node is determined. Compared with the related art of obtaining the charging facility acceptance capacity of the distribution network node by calculating the difference between the total capacity of the distribution network and the capacity occupied by the existing facilities of the distribution network, since the charging facility acceptance capacity can be improved, the problem of distribution network expansion caused by the newly added charging facilities can be alleviated, thereby improving the resource utilization rate of the distribution network, and thus saving costs.

[0158] For the specific definition of the device for determining the charging facility acceptance capacity of the distribution network node, please refer to the definition of the method for determining the charging facility acceptance capacity of the distribution network node above, which will not be repeated here. Each module in the above-mentioned device for determining the charging facility acceptance capacity of the distribution network node can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0159] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store preset thresholds. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for determining the charging facility acceptance capacity of a distribution network node is implemented.

[0160] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0161] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0162] For any node, determine the target value range of the charging facility acceptance capacity of the node;

[0163] Select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0164] Based on the final selected target value range, the final value of the charging facility acceptance capacity of the node is determined.

[0165] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0166] Obtain the total load, charging load and grid information of the distribution network at every historical moment;

[0167] According to the total load and charging load at each historical moment, the total load characteristics and charging load characteristics at each evaluation moment are obtained;

[0168] Calculate the ratio between the total load characteristic at each evaluation moment and the total number of nodes in the distribution network as the input load of the node at each evaluation moment;

[0169] Normalizing the charging load characteristics at all evaluation moments to obtain a normalized value of the charging load at each evaluation moment;

[0170] For any value, the additional charging load at each evaluation time is calculated based on the value and the normalized value of the charging load at different evaluation times;

[0171] According to the grid information, the newly added charging load at each evaluation moment and the input load at each evaluation moment, the predicted values ​​of the three prediction parameters of the node at each evaluation moment are calculated. The three prediction parameters are the node voltage per unit value, feeder current and network loss rate.

[0172] Determine the target values ​​corresponding to the three preset parameters of the node according to the predicted values ​​of the three prediction parameters at all evaluation moments of the node;

[0173] The over-limit judgment result of the value is determined according to the target values ​​corresponding to the three preset parameters of the node.

[0174] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0175] According to the total load and charging load at each historical moment in each historical time period, the total load characteristics and charging load characteristics at each evaluation moment in the evaluation time period of a preset length are calculated respectively; wherein the division method of the evaluation moments in the evaluation time period is the same as the division method of the historical moments in the historical time period.

[0176] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0177] According to the charging load characteristics at each evaluation moment, determining the maximum value and the minimum value of the charging load characteristics;

[0178] According to the charging load characteristics, maximum value and minimum value at each evaluation moment, the normalized value of the charging load at each evaluation moment is calculated.

[0179] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0180] For any value, the additional charging load at each evaluation time is calculated based on the value and the normalized value of the charging load at different evaluation times, including:

[0181]

[0182] In the above formula (8), P add (t) represents the newly added charging load at the evaluation time t, P jie Represents any value, Represents the normalized value of the charging load at the evaluation time t.

[0183] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0184] For any evaluation time, the newly added charging load and the input load at any evaluation time are added to obtain the total input load at any evaluation time;

[0185] According to the grid information and the total input load at each evaluation moment, the power flow calculation is performed to obtain the predicted values ​​of the three prediction parameters at each evaluation moment.

[0186] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0187] Determine the minimum value from the node voltage per unit values ​​at all evaluation moments and use it as the target value of the node voltage per unit value;

[0188] Determine the maximum value from the feeder currents at all evaluation moments and use it as the target value of the feeder current;

[0189] The maximum value is determined from the network loss rates at all evaluation moments and is used as the target value of the network loss rate.

[0190] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0191] Determine whether each of the target values ​​corresponding to the three preset parameters exceeds the limit;

[0192] If any of the target values ​​corresponding to the three preset parameters exceeds the limit, it is determined that any value exceeds the limit. If no target value exceeds the limit among the target values ​​corresponding to the three preset parameters, it is determined that any value does not exceed the limit.

[0193] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0194] If the target value of the node voltage per unit value is less than the minimum voltage lower limit, it is determined that the target value of the node voltage per unit value exceeds the limit;

[0195] If the target value of the feeder current is greater than the feeder current carrying capacity, it is determined that the target value of the feeder current exceeds the limit;

[0196] If the target value of the network loss rate is less than the network loss rate specified in the national standard, it is determined that the target value of the network loss rate exceeds the limit.

[0197] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0198] For any node, determine the target value range of the charging facility acceptance capacity of the node;

[0199] Select different values ​​of the charging facility acceptance capacity of the node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions;

[0200] Based on the final selected target value range, the final value of the charging facility acceptance capacity of the node is determined.

[0201] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0202] Obtain the total load, charging load and grid information of the distribution network at every historical moment;

[0203] According to the total load and charging load at each historical moment, the total load characteristics and charging load characteristics at each evaluation moment are obtained;

[0204] Calculate the ratio between the total load characteristic at each evaluation moment and the total number of nodes in the distribution network as the input load of the node at each evaluation moment;

[0205] Normalizing the charging load characteristics at all evaluation moments to obtain a normalized value of the charging load at each evaluation moment;

[0206] For any value, the additional charging load at each evaluation time is calculated based on the value and the normalized value of the charging load at different evaluation times;

[0207] According to the grid information, the newly added charging load at each evaluation moment and the input load at each evaluation moment, the predicted values ​​of the three prediction parameters of the node at each evaluation moment are calculated. The three prediction parameters are the node voltage per unit value, feeder current and network loss rate.

[0208] Determine the target values ​​corresponding to the three preset parameters of the node according to the predicted values ​​of the three prediction parameters at all evaluation moments of the node;

[0209] The over-limit judgment result of the value is determined according to the target values ​​corresponding to the three preset parameters of the node.

[0210] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0211] According to the total load and charging load at each historical moment in each historical time period, the total load characteristics and charging load characteristics at each evaluation moment in the evaluation time period of a preset length are calculated respectively; wherein the division method of the evaluation moments in the evaluation time period is the same as the division method of the historical moments in the historical time period.

[0212] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0213] According to the charging load characteristics at each evaluation moment, determining the maximum value and the minimum value of the charging load characteristics;

[0214] According to the charging load characteristics, maximum value and minimum value at each evaluation moment, the normalized value of the charging load at each evaluation moment is calculated.

[0215] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0216] For any value, the additional charging load at each evaluation time is calculated based on the value and the normalized value of the charging load at different evaluation times, including:

[0217]

[0218] In the above formula (9), P add (t) represents the newly added charging load at the evaluation time t, P jie Represents any value, Represents the normalized value of the charging load at the evaluation time t.

[0219] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0220] For any evaluation time, the newly added charging load and the input load at any evaluation time are added to obtain the total input load at any evaluation time;

[0221] According to the grid information and the total input load at each evaluation moment, the power flow calculation is performed to obtain the predicted values ​​of the three prediction parameters at each evaluation moment.

[0222] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0223] Determine the minimum value from the node voltage per unit values ​​at all evaluation moments and use it as the target value of the node voltage per unit value;

[0224] Determine the maximum value from the feeder currents at all evaluation moments and use it as the target value of the feeder current;

[0225] The maximum value is determined from the network loss rates at all evaluation moments and is used as the target value of the network loss rate.

[0226] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0227] Determine whether each of the target values ​​corresponding to the three preset parameters exceeds the limit;

[0228] If any of the target values ​​corresponding to the three preset parameters exceeds the limit, it is determined that any value exceeds the limit. If no target value exceeds the limit among the target values ​​corresponding to the three preset parameters, it is determined that any value does not exceed the limit.

[0229] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0230] If the target value of the node voltage per unit value is less than the minimum voltage lower limit, it is determined that the target value of the node voltage per unit value exceeds the limit;

[0231] If the target value of the feeder current is greater than the feeder current carrying capacity, it is determined that the target value of the feeder current exceeds the limit;

[0232] If the target value of the network loss rate is less than the network loss rate specified in the national standard, it is determined that the target value of the network loss rate exceeds the limit.

[0233] Those of ordinary skill 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, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer 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 at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0234] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above 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.

[0235] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for determining the charging facility acceptance capacity of a distribution network node, It is characterized in that The method comprises: For any node, determining a target value range of the charging facility acceptance capacity of the any node; Select different values ​​of the charging facility acceptance capacity of any node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals according to the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting a value from the target value interval, calculating the over-limit judgment result of the selected value, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions; The calculation of the limit-crossing judgment results of different values ​​includes: Obtain the total load, charging load and grid information of the distribution network at every historical moment; According to the total load and charging load at each historical moment, the total load characteristics and charging load characteristics at each evaluation moment are obtained; Calculating the ratio between the total load characteristic at each evaluation moment and the total number of nodes in the distribution network as the input load of any node at each evaluation moment; Normalizing the charging load characteristics at all evaluation moments to obtain a normalized value of the charging load at each evaluation moment; For any value, the newly added charging load at each evaluation time is calculated according to the any value and the normalized value of the charging load at different evaluation times; Calculate the predicted values ​​of three prediction parameters of any node at each evaluation time according to the grid information, the newly added charging load at each evaluation time, and the input load at each evaluation time, wherein the three prediction parameters are the node voltage per unit value, the feeder current, and the network loss rate; Determine the target values ​​corresponding to the three preset parameters of any node according to the predicted values ​​of the three prediction parameters at all evaluation moments of any node; Determine the over-limit judgment result of any value according to the target values ​​corresponding to the three preset parameters of any node; According to the target value interval finally screened out, the final value of the charging facility acceptance capacity of any node is determined.

2. The method according to claim 1, It is characterized in that The historical moments are divided into historical time periods of preset lengths, and the division method of historical moments between different historical time periods is the same; accordingly, the total load characteristics and charging load characteristics of each evaluation moment are obtained according to the total load and charging load of each historical moment, including: According to the total load and charging load at each historical moment in each historical time period, the total load characteristics and charging load characteristics at each evaluation moment in the evaluation time period of the preset length are calculated respectively; wherein the division method of the evaluation moments in the evaluation time period is the same as the division method of the historical moments in the historical time period.

3. The method according to claim 1, It is characterized in that The normalization of the charging load characteristics at all historical moments to obtain the normalized value of the charging load at each evaluation moment includes: According to the charging load characteristics at each evaluation moment, determining the maximum value and the minimum value of the charging load characteristics; A charging load normalization value at each evaluation moment is calculated according to the charging load characteristics at each evaluation moment, the maximum value, and the minimum value.

4. The method according to claim 1, It is characterized in that For any value, according to the any value and the normalized value of the charging load at different evaluation times, calculating the newly added charging load at each evaluation time includes: In the above formula (1): The evaluation time is t The additional charging load represents any of the above values, Represents the normalized value of the charging load at the evaluation time t.

5. The method according to claim 1, It is characterized in that The calculation of the predicted values ​​of the three prediction parameters of any node at each evaluation moment according to the grid information, the newly added charging load at each evaluation moment, and the input load at each evaluation moment includes: For any evaluation moment, the newly added charging load and the input load at any evaluation moment are added to obtain the total input load at any evaluation moment; According to the grid information and the total input load at each evaluation moment, a power flow calculation is performed to obtain the predicted values ​​of the three prediction parameters of any node at each evaluation moment.

6. The method according to claim 1, It is characterized in that The step of determining target values ​​corresponding to the three preset parameters respectively according to the predicted values ​​of the three prediction parameters at all evaluation moments includes: Determine the minimum value from the node voltage per unit values ​​at all evaluation moments and use it as the target value of the node voltage per unit value; Determine the maximum value from the feeder currents at all evaluation moments and use it as the target value of the feeder current; The maximum value is determined from the network loss rates at all evaluation moments and is used as the target value of the network loss rate.

7. The method according to claim 1, It is characterized in that The determining of the over-limit judgment result of any value according to the target values ​​corresponding to the three preset parameters respectively includes: Determine whether each of the target values ​​corresponding to the three preset parameters exceeds the limit; If any of the target values ​​corresponding to the three preset parameters exceeds the limit, it is determined that any of the values ​​exceeds the limit; if no target value exceeds the limit among the target values ​​corresponding to the three preset parameters, it is determined that any of the values ​​does not exceed the limit.

8. The method according to claim 7, It is characterized in that The determining whether each of the target values ​​corresponding to the three preset parameters exceeds a limit includes: If the target value of the node voltage per unit value is less than the minimum voltage lower limit, it is determined that the target value of the node voltage per unit value exceeds the limit; If the target value of the feeder current is greater than the feeder current carrying capacity, it is determined that the target value of the feeder current exceeds the limit; If the target value of the network loss rate is less than the network loss rate specified in the national standard, it is determined that the target value of the network loss rate exceeds the limit.

9. A device for determining the charging facility acceptance capacity of a distribution network node, It is characterized in that The device comprises: A target value interval determination module, used to determine, for any node, a target value interval of the charging facility acceptance capacity of the any node; A target value interval screening module is used to select different values ​​of the charging facility acceptance capacity of any node within the target value interval, calculate the over-limit judgment results of each different value, form different intervals by the value size of each different value, and re-screen the interval whose lower limit over-limit judgment result is not over-limit and whose upper limit over-limit judgment result is over-limit from the composed interval as the target value interval, repeat the above process of selecting values ​​from the target value interval, calculating the over-limit judgment result of the selected values, and re-screening the target value interval from the interval composed of the values ​​until the screened target value interval meets the preset conditions; wherein, a load acquisition module is used to obtain the total load, charging load and grid information of the distribution network at each historical moment; A load characteristic module is used to obtain the total load characteristics and charging load characteristics at each evaluation moment based on the total load and charging load at each historical moment; An input load calculation module, used to calculate the ratio between the total load characteristic at each evaluation moment and the total number of nodes in the distribution network as the input load of any node at each evaluation moment; A normalized value calculation module is used to normalize the charging load characteristics at all evaluation moments to obtain a normalized value of the charging load at each evaluation moment; A newly added charging load calculation module is used to calculate the newly added charging load at each evaluation time for any value according to the any value and the charging load normalization value at different evaluation times; A prediction value calculation module, used to calculate the prediction values ​​of three prediction parameters of any node at each evaluation moment according to the grid information, the newly added charging load at each evaluation moment, and the input load at each evaluation moment, wherein the three prediction parameters are the node voltage per unit value, the feeder current, and the network loss rate; A target value determination module, used to determine the target values ​​corresponding to the three preset parameters of any node according to the predicted values ​​of the three prediction parameters at all evaluation moments of any node; An over-limit judgment result determination module is used to determine the over-limit judgment result of any value according to the target values ​​corresponding to the three preset parameters of any node; The final value determination module is used to determine the final value of the charging facility acceptance capacity of any node according to the target value interval finally screened out.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program. It is characterized in that When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

11. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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