Battery charging and discharging method, device, equipment and computer storage medium

Abstract

Embodiments of the present application provide a battery charging and discharging method, apparatus, device, and computer storage medium. The method includes: obtaining base station data, including base station location data, power outage data, and electricity price information; clustering and grouping the base station data based on the base station location data and power outage data to obtain a preset number of groups; determining charging and discharging times based on the electricity price information and power outage data; and charging and discharging based on the preset number of groups and the charging and discharging times of the base station batteries within the groups. The battery charging and discharging method according to embodiments of the present application can reduce base station electricity costs while ensuring a quality of user experience.

Description

Technical Field

[0001] The present application belongs to the field of 5G base station technology, and in particular relates to a battery charging and discharging method, device, equipment and computer storage medium. Background Art

[0002] Wireless communication technology has entered the 5G era. While 5G networks offer a superior user experience compared to 4G networks, they also consume significantly more energy. For example, a 4G user watching a high-definition movie online consumes 10GB of throughput, while a 5G user can choose 4K or 8K ultra-high-definition movies, consuming over 200GB of throughput. The high energy consumption and resulting costs are a pressing issue for operators.

[0003] The existing method of reducing the power consumption of 5G base stations is to set wireless functions such as symbol shutdown function, channel shutdown function, discontinuous transmission, etc. on the base station, or to shut down the cell or base station by methods such as carrier shutdown and base station hard shutdown. The above methods all shut down some functions to reduce power consumption and thus reduce electricity costs. However, the above methods will damage user perception and reduce user experience. Summary of the Invention

[0004] The embodiments of the present application provide a battery charging and discharging method, device, equipment and computer storage medium, which can reasonably utilize the charging and discharging process of the base station battery to provide power, realize peak-shifting power consumption, and achieve the purpose of saving electricity costs without compromising user experience.

[0005] In a first aspect, an embodiment of the present application provides a battery charging and discharging method, the method comprising:

[0006] Obtaining target base station data, the target base station data including battery life of the target base station, electricity price information, power outage time data of the target base station within a first preset time period, the target base station location, and power outage time data of the target base station within a second preset time period, the target base station power outage time data including the power outage time and restoration time of the target base station, and the second preset time period including the first preset time period;

[0007] Determine the battery charge and discharge time of the target base station according to the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information;

[0008] Clustering the target base stations based on their locations and power outage time data within a first preset time period to obtain a base station itemset;

[0009] Calculating base station itemsets according to the power outage time of the target base station within the first preset time period to obtain frequent itemsets of the base station;

[0010] Selecting itemsets containing the same base station data in the frequent itemsets of the base stations and fusing them to obtain at least one first set;

[0011] Clustering the base station data in the target base station data except for the item set containing the same base station data based on the base station location to obtain at least one second set;

[0012] Evenly dividing the items in each of the at least one first set and the items in each of the at least one second set into a predetermined number of groups;

[0013] The battery of the target base station is charged and discharged according to a preset number of groups and the charging and discharging time of the batteries of the target base stations in the groups.

[0014] In a second aspect, an embodiment of the present application provides a battery charging and discharging device, the device comprising:

[0015] an acquisition module, configured to acquire target base station data, the target base station data including battery life of the target base station, electricity price information, power outage time data of the target base station within a first preset time period, the target base station location, and power outage time data of the target base station within a second preset time period, the target base station power outage time data including the power outage time and restoration time of the target base station, and the second preset time period including the first preset time period;

[0016] a determination module, configured to determine a battery charge and discharge time of the target base station according to the power outage time data of the target base station within a second preset time period, the battery life of the target base station, and electricity price information;

[0017] A clustering module, configured to cluster the target base stations based on their locations and the power outage time data of the target base stations within a first preset time period to obtain a base station itemset;

[0018] A calculation module, configured to calculate base station itemsets according to the power outage time of the target base station within the first preset time period to obtain frequent itemsets of the base station;

[0019] A fusion module, configured to select itemsets containing the same base station data from the frequent itemsets of the base stations and fuse them to obtain at least one first set;

[0020] The clustering module is further configured to cluster the base station data in the target base station data except for the item set containing the same base station data based on the base station location to obtain at least one second set;

[0021] a partitioning module, configured to evenly partition the items in each of the at least one first set and the items in each of the at least one second set into a preset number of groups;

[0022] The charging and discharging module is used to charge and discharge the battery of the target base station according to a preset number of groups and the charging and discharging time of the batteries of the target base stations in the groups.

[0023] In a third aspect, an embodiment of the present application provides a battery charging and discharging device, the device comprising:

[0024] a processor, and a memory storing computer program instructions;

[0025] The processor reads and executes computer program instructions to implement the battery charging and discharging method of the first aspect.

[0026] In a fourth aspect, an embodiment of the present application provides a computer storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the battery charging and discharging method of the first aspect is implemented.

[0027] The battery charging and discharging methods, devices, equipment, and computer storage media of the embodiments of the present application can determine the base station's power outage period by obtaining base station location data, power outage data, battery data, and electricity price information, and select charging and discharging times outside of the power outage period. The base station data is then organized into groups, and the base station battery is charged and discharged based on the groupings and the charging and discharging times of the base stations within the groups. By discharging when electricity prices are high and charging when prices are low, the electricity costs of 5G base stations can be significantly reduced while ensuring the user experience quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0029] Figure 1 This is a flow chart of a battery charging and discharging method provided in an embodiment of the present application;

[0030] Figure 2 This is a schematic structural diagram of a battery charging and discharging device provided in an embodiment of the present application;

[0031] Figure 3 It is a structural schematic diagram of a battery charging and discharging device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0033] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0034] While 5G technology offers a better user experience, it also consumes more energy, significantly increasing the cost of 5G. Existing cost-cutting solutions involve disabling certain functions at base stations to reduce power consumption, thereby lowering costs to a certain extent. However, this also impacts the user experience.

[0035] In order to solve the problems of the prior art, the embodiments of the present application provide a battery charging and discharging method, device, equipment and computer storage medium. The battery charging and discharging method provided by the embodiments of the present application is first introduced below.

[0036] Figure 1 FIG1 shows a flow chart of a battery charging and discharging method provided by an embodiment of the present application. Figure 1 As shown, the method may include the following steps:

[0037] S110. Obtain target base station data, the target base station data including the battery life of the target base station, electricity price information, power outage time data of the target base station within a first preset time period, the target base station location, and power outage time data of the target base station within a second preset time period. The target base station power outage time data includes the power outage time and restoration time of the target base station, and the second preset time period includes the first preset time period.

[0038] Get the battery life and electricity price information of the target base station.

[0039] Dynamic environment monitoring data is collected from the dynamic environment monitoring platform. This data includes dynamic environment alarm data for the target base station within a first preset time period and a second preset time period. The second preset time period is approximately S months, and the first preset time period is approximately T months, where T is less than S. Dynamic environment alarm data includes power outage duration data for the target base station, specifically including the power outage time and restoration time. The values ​​of S and T are configurable, and the units are not limited to months; other time units can be used without limitation.

[0040] Obtain the target base station's engineering parameter data from the resource management platform, where the engineering parameter data includes the target base station's location data.

[0041] In some embodiments, after acquiring the dynamic environment alarm data of the target base station, the dynamic environment alarm is deduplicated, that is, multiple alarm data generated by the same power outage event are deduplicated, and only the initial alarm data is retained.

[0042] S120 . Determine the battery charge and discharge time of the target base station according to the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information.

[0043] According to the power outage time period of the target base station and the battery life of the target base station within the second preset time period, a time period with a higher electricity price other than the power outage time period of the target base station is selected as the discharge time period of the target base station battery, and a time period with a lower electricity price other than the power outage time period of the target base station and the discharge time period of the target base station battery is selected as the charging time period of the target base station battery.

[0044] S130 : Clustering the target base stations based on their locations and the power outage time data of the target base stations within a first preset time period to obtain a base station itemset.

[0045] The target base station's operating parameter data and alarm data are correlated, and the target base station data is divided into different geographical groups based on the target base station's location data in the operating parameter data. The target base station data within each geographical group is clustered based on the target base station's power outage duration data within a first preset time period to obtain a set of base station items with substantially the same power outage duration data.

[0046] For example, for base stations {A, B, C, D, E, F, G, H}, base stations in the same area are grouped according to their geographic location, resulting in multiple geographic groups: {A, B, C, D}, {E, F}, and {G, H}. Clustering is performed on each geographic group based on power outage time data. For the first geographic group {A, B, C, D}, clustering yields the base station item set {A, B}, {C}, and {D}. The power outage and restoration times for A and B are essentially the same, and no base station in C or D has an essentially identical power outage and restoration time.

[0047] S140 : Calculate base station itemsets according to the power outage time of the target base station within the first preset time period to obtain frequent itemsets of the base station.

[0048] Using the Apriori algorithm, we mine and calculate base station itemsets based on the power outage times of target base stations within a first preset time period. This outputs frequent itemsets for base stations with the same power outage time across all geographic groups. Frequent itemsets are defined as those with a support greater than the minimum support, where support refers to how often a set appears in all data.

[0049] For example, for the first geographical group of base stations {A, B, C, D, E, F, G, H}, by clustering the power outage time of the base stations, we can obtain the frequent item sets {A, B, C}, {C, D, E, F}, {G, H}.

[0050] In some embodiments, when using the Apriori algorithm for data mining, the system calls the Python language Apriori related library mlxtend:

[0051] #Load the library

[0052] from mlxtend.frequent_patterns import apriori#Frequent item set mining

[0053] from mlxtend.frequent_patterns import association_rules#Association rule mining

[0054] #Frequent item set mining function

[0055] frequent_itemsets=apriori(SCi,min_support=0.1,use_colnames=False)

[0056] #Association rule mining function

[0057] rules=association_rules(frequent_itemsets,min_threshold=0.7)

[0058] Parameter min_support support: the proportion of records in the dataset that contain this item set. The system default setting is 0.03.

[0059] The parameter use_colnames uses column names: the column name of the item is not included in the frequent item set.

[0060] Parameter min_threshold confidence threshold: the probability of other items appearing when certain items appear (conditional probability), the system default setting is 0.7.

[0061] All parameters can be adjusted.

[0062] S150: Select itemsets containing the same base station data from the frequent itemsets of the base stations and fuse them to obtain at least one first set.

[0063] The base station data belonging to different item sets are fused to obtain at least one first set, so that the fused item sets do not contain duplicate data.

[0064] In some embodiments, selecting itemsets containing the same base station data in frequent itemsets of base stations and fusing them to obtain at least one first set includes: dividing base station data belonging to at least two frequent itemsets into at least two sets with fewer items in the frequent itemsets.

[0065] For example, two groups of base stations {A, B, C} and {C, D, E, F} that frequently experience power outages at the same time, where C is the intersection of the two groups of base station item sets. Assign C to the group with fewer items, and finally obtain {A, B, C} and {D, E, F}.

[0066] S160: Cluster the base station data in the target base station data except for the item set containing the same base station data based on the base station location to obtain at least one second set.

[0067] Item sets other than those containing the same base station data are selected, and the base station data in each item set are subjected to an improved Kmeans clustering algorithm, specifically including: clustering the base station location data by calculating the distances between the base stations in the item set to obtain at least one second set.

[0068] In some embodiments, the distance between base stations is Euclidean distance or Manhattan distance, etc. The specific distance calculation formula may be:

[0069] R*arcos[cos(Y1)*cos(Y2)*cos(X1-X2)+sin(Y1)*sin(Y2)], where (X1, Y1) is the longitude and latitude of one point, (X2, Y2) is the longitude and latitude of another point, and R is the radius of the earth, 6371.

[0070] For example, for an item set {A, B, C, D, E, F} other than the item set containing the same base station data, clustering is performed according to the latitude and longitude positions of its base stations to obtain a second set {A, B}, {C}, {D, E, F}.

[0071] S170: Evenly divide the items in each of the at least one first set and the items in each of the at least one second set into a preset number of groups.

[0072] The items in each of the at least one first set are randomly and evenly divided into n first groups, the items in each of the at least one second set are randomly and evenly divided into n second groups, and the n first groups and the n second groups are sequentially divided into a preset number of groups in a round-robin manner. Where n is the preset number, which can be set and is not limited.

[0073] For example: n is 2, a first set is {A, B, C, D}, which is randomly divided to obtain 2 first sets {A, D}, {B, C}, a second set is {E, F, G, H, I}, which is randomly divided to obtain 2 second sets {E, F, H}, {G, I}, and a preset number of groups {A, D, E, F, H}, {B, C, G, I} are obtained by polling division.

[0074] S180: Charge and discharge the battery of the target base station according to a preset number of groups and the charge and discharge time of the batteries of the target base stations in the groups.

[0075] In some embodiments, the battery of the target base station is charged and discharged according to a preset number of groups and the battery charge and discharge time of the target base stations within the preset number of groups, including: selecting one of the groups as the target group; charging and discharging the batteries of the base stations within the target group according to the battery charge and discharge time of the target base station.

[0076] The battery charging and discharging method provided in the embodiments of the present application can determine the base station's power outage period by obtaining base station location data, power outage data, battery data, and electricity price information, and select charging and discharging times during times other than the power outage period. The method also organizes the base station data into groups and charges and discharges the base station battery based on the groups and the charge and discharge times of the base stations within the groups. By discharging when electricity prices are high and charging when prices are low, the electricity costs of 5G base stations can be reduced without compromising the user experience.

[0077] In some embodiments, the battery charge and discharge time of the target base station is determined based on the power outage time data of the target base station within a second preset time period, the battery life of the target base station, and the electricity price information, including: calculating the power outage time data of the target base station within the second preset time period to obtain the power outage period of the target base station; determining the battery charge and discharge time of the target base station based on the power outage period of the target base station, the battery life of the target base station, and the electricity price information.

[0078] In some embodiments, calculating the target base station power outage time data within a second preset time period to obtain the target base station power outage period includes: calculating the target base station power outage time data within the second preset time period to obtain a frequent item set of the target base station power outage period; and merging the frequent item sets of the target base station power outage period to obtain the target base station power outage period. The Apriori algorithm is used to mine the target base station power outage time data within the second preset time period to obtain a frequent item set of each base station power outage period, wherein the frequent item set represents the period when each base station frequently experiences power outages. The frequent item sets of each base station power outage period are merged to obtain the high-risk power outage period of the target base station. For example, if the frequent item set of the power outage period of one base station is {4, 6}, {12, 15}, then the high-risk power outage period of the target base station obtained by merging is {4, 6, 12, 15}.

[0079] In some embodiments, the target base station's battery charge and discharge times are determined based on the target base station's power outage period, the target base station's battery life, and electricity price information. This includes: determining peak, normal, and off-peak periods based on electricity price information; calculating the battery's dischargeable duration based on the target base station's battery data; and, after excluding high-risk power outage periods, selecting a period that meets the battery's dischargeable duration as the discharge period according to a preset first priority. Peak, normal, and off-peak periods are determined based on electricity price information. For example, peak period electricity consumption is 1.025 yuan / kWh, normal period electricity consumption is 0.725 yuan / kWh, and off-peak period electricity consumption is 0.425 yuan / kWh. Peak period is 5:00 PM to 10:00 PM, off-peak period is 0:00 AM to 7:00 AM, and the remaining periods are normal periods. Battery dischargeable duration = battery life * k, where k is the defined ratio for power scheduling, typically within the range of [0.2, 0.7]. In the time periods other than the high-risk power outage period, a period that includes the battery discharge time calculated above is selected, and then the discharge period is determined according to the preset first priority. The preset first priority is that peak hours have high priority, normal hours have low priority, and off-peak hours do not discharge, and the selection is made in order from late to early. For example, the high-risk power outage period of a base station is {9, 10, 11, 12, 17, 18, 20}, the battery life of the base station is 4 hours, and the k value is 0.5. The calculated discharge time is 2, and the high-risk period is proposed, resulting in the selectable time periods {0, 1, 2, 3, 4, 5, 6, 7, 8, 13, 14, 15, 16, 19, 21, 22, 23}. Based on the peak and off-peak periods in the above example, the final discharge period is determined to be {21, 22}.

[0080] In some embodiments, the method further includes: selecting a charging start time according to a preset second priority after excluding high-risk power outage periods and discharge periods. The second priority has a higher priority for off-peak periods and a lower priority for normal periods, and the priority ranges from morning to night. For example, if the high-risk power outage periods are {9, 10, 11, 12, 17, 18, 20} and the determined discharge periods are {21, 22}, excluding the high-risk periods and discharge periods to obtain {0, 1, 2, 3, 4, 5, 6, 7, 8, 13, 14, 15, 16, 19, 23}, then the charging start time is determined to be 0:00. If charging is not complete from 0:00 to the start of the discharge period, i.e., 21:00, the base station battery will not be discharged and charging will continue on that day.

[0081] In some embodiments, to fuse the item sets that contain the same base station data in the frequently occurring item sets of the selected base stations to obtain at least one first set, the method includes: dividing the base station data that belongs to at least two frequently occurring item sets into the set with fewer items in the at least two frequently occurring item sets. For example, when there are two sets of base stations with frequent power outages {A, B, C} and {C, D, E, F}, where C belongs to both frequently occurring item sets and the number of items in the first item set is fewer, so C is classified into the first item set.

[0082] In some embodiments, to charge and discharge the storage batteries of the target base stations according to a preset number of groups and the charge and discharge times of the storage batteries of the target base stations within the preset number of groups, the method includes: selecting one of the groups as the target group; charging and discharging the storage batteries of the base stations within the target group according to the charge and discharge times of the storage batteries of the target base stations. When performing charge and discharge on the base stations, select one group every day and perform the corresponding charge and discharge operations according to the set charge and discharge times within each group.

[0083] In some embodiments, the specific algorithm for clustering the target base station data in each geographical group according to the power outage time data of the target base stations within the first preset time period to obtain the base station item sets with basically the same power outage time data is as follows:

[0084] Input: A data frame containing base station names, power outage times, and restoration times. Let the input set be SR.

[0085] Output: The machine room item sets with AC power outage alarms occurring at basically the same time and alarm restoration at basically the same time, such as {{A}, {B}, {A}, {A}, {A, B}, {A, B}, {B}, {A, B, C}...}, where A, B, and C represent base station names. Let the output set be SC.

[0086] Initial state: SC is empty. Read the first sample x1(a1, b1) from SR and form the item set S1 = {X1} (x1 is the machine room, a1 is the AC power outage time, and b1 is the AC restoration time).

[0087] Read the second sample X2(a2, b2) from SR. If |a1 – a2| < Tb and |b1 – b2| < Ts, then the sample X2 is classified into S1; otherwise, form the item set S2 = {X2}, (where Tb and Ts are system setting parameters, which are the measurement conditions for clustering the AC power outage events of the machine rooms. The system is set to 10 minutes, and this is not limited herein, and the specific values can be modified).

[0088] Read the kth sample Xk(ak,,bk) from SR. Assume that there are multiple item sets S1…Sh in the current SC. Then traverse the above item sets until the absolute value of the power outage time difference and the absolute value of the restoration time difference between Xk and all samples in a certain item set are less than Tb and Ts respectively. Then Xk belongs to this item set. Otherwise, the item set Sk={Xk} is formed.

[0089] Take the last sample Xn from SR and put it into SC for clustering calculation, and finally form the output set SC.

[0090] In some embodiments, before selecting itemsets containing the same base station data in frequent itemsets of base stations for fusion to obtain at least one first set, the method further includes: performing blacklist and whitelist screening. During the screening, the base station data is filtered based on the importance of the base stations, and transmission node base stations and important scene base stations are not included in the subsequent processing scope.

[0091] In some embodiments, the clustering model parameter K value is calculated as follows: the ratio of the number of base stations excluding the base station data in the item set containing the same base station data to a preset number, and the ratio is rounded up.

[0092] In some embodiments, evenly dividing the items in each of the at least one first set and the items in each of the at least one second set into a predetermined number of groups includes:

[0093] Filter the number of collections. If the number of computer rooms in each collection is less than the preset number (i.e., the number of defined scheduling groups), the density of sites in the area covered by the collection is insufficient, and subsequent charging and discharging operations are not performed, and power time-domain scheduling is not performed.

[0094] Charge and discharge group arrangement. Sets with a preset number of base stations will be placed in the charge and discharge group arrangement. Sets with a preset number of base stations will be randomly arranged into a preset number of groups. Sets with a preset number of base stations will be sorted by name and polled in the preset number of groups.

[0095] The battery charging method provided in the embodiments of this application determines the base station's power outage period, selects charging and discharging times outside of the outage period, organizes base station data into groups, and charges and discharges the base station battery based on the groups and the charging and discharging times of the base stations within them. By discharging when electricity prices are high and charging when prices are low, the user experience quality is guaranteed while reducing the base station's electricity costs.

[0096] Figure 2 This is a schematic diagram of a device structure provided in an embodiment of the present application. Figure 2As shown, the apparatus may include an acquisition module 210 , a determination module 220 , a clustering module 230 , a calculation module 240 , a fusion module 250 , a division module 260 , and a discharge module 270 .

[0097] An acquisition module 210 is configured to acquire target base station data, the target base station data including battery life of the target base station, electricity price information, power outage time data of the target base station within a first preset time period, the target base station location, and power outage time data of the target base station within a second preset time period, the target base station power outage time data including the power outage time and restoration time of the target base station, and the second preset time period including the first preset time period;

[0098] The determination module 220 is configured to determine the battery charge and discharge time of the target base station according to the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information;

[0099] A clustering module 230 is configured to cluster the target base stations based on their locations and the power outage time data of the target base stations within a first preset time period to obtain a base station itemset;

[0100] A calculation module 240 is configured to calculate base station itemsets according to the power outage time of the target base station within the first preset time period to obtain frequent itemsets of the base station;

[0101] A fusion module 250 is configured to select itemsets containing the same base station data from the frequent itemsets of the base stations and fuse them to obtain at least one first set;

[0102] The clustering module 230 is further configured to cluster the base station data in the target base station data except for the item set containing the same base station data based on the base station location to obtain at least one second set;

[0103] a partitioning module 260 for evenly partitioning the items in each of the at least one first set and the items in each of the at least one second set into a preset number of groups;

[0104] The charging and discharging module 270 is configured to charge and discharge the battery of the target base station according to a preset number of groups and the charging and discharging time of the batteries of the target base stations in the groups.

[0105] The embodiments of the present application provide a method for determining a base station's power outage period by acquiring base station location data, power outage data, battery data, and electricity price information, and selecting charging and discharging times outside of the power outage period. The method also organizes the base station data into groups, and charges and discharges the base station battery based on the groups and the charge and discharge times of the base stations within the groups. By discharging when electricity prices are high and charging when prices are low, the base station's electricity costs can be significantly reduced without compromising the user experience.

[0106] In some embodiments, the determination module 220 is used to determine the battery charge and discharge time of the target base station based on the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information, including: a determination module, used to calculate the power outage time data of the target base station within the second preset time period to obtain the power outage period of the target base station; the determination module is also used to determine the battery charge and discharge time of the target base station based on the power outage period of the target base station, the battery life of the target base station, and the electricity price information.

[0107] In some embodiments, the determination module 220 is used to calculate the power outage time data of the target base station within the second preset time period to obtain the power outage period of the target base station, including: a determination module, used to calculate the power outage time data of the target base station within the second preset time period to obtain the frequent item set of the power outage period of the target base station; the determination module is also used to merge the frequent item set of the power outage period of the target base station to obtain the power outage period of the target base station.

[0108] In some embodiments, the determination module 220 is also used to determine the charge and discharge time of the battery of the target base station based on the power outage period of the target base station, the battery life of the target base station, and the electricity price information, including: a determination module for determining the peak period, normal period and off-peak period based on the electricity price information; the determination module is also used to calculate the battery discharge time based on the battery data of the target base station; the determination module is also used to select a time period that meets the battery discharge time as the discharge period according to a preset first preset priority after excluding the high-risk power outage period.

[0109] In some embodiments, the apparatus further includes: a selection module 280 for selecting a charging start time according to a preset second preset priority after excluding high-risk power outage periods and discharge periods.

[0110] In some embodiments, the fusion module 250 is used to select item sets containing the same base station data in the frequent item sets of the base station and fuse them to obtain at least one first set, including: a fusion module is used to divide the base station data that belongs to at least two frequent item sets at the same time into at least two sets with fewer items in the frequent item sets.

[0111] In some embodiments, the charging and discharging module 270 is used to charge and discharge the battery of the target base station according to a preset number of groups and the battery charging and discharging time of the target base station in the group, including: the charging and discharging module 270 is used to select one of the groups as the target group; charge and discharge the battery of the base station in the target group according to the battery charging and discharging time of the target base station.

[0112] The embodiments of the present application provide a method for determining the power outage period of a base station by acquiring base station location data, power outage data, battery data, and electricity price information, and selecting charging and discharging times outside of the power outage period. The method also groups the base station data and charges and discharges the base station battery based on the groupings and the charge and discharge times of the base stations within the groupings. By discharging when electricity prices are high and charging when prices are low, the electricity cost of 5G base stations can be significantly reduced while ensuring the quality of user experience.

[0113] Figure 2 Each module in the device shown has the function of realizing Figure 1 The functions of each step in the embodiment can achieve the corresponding technical effects, which will not be described in detail here for the sake of brevity.

[0114] Figure 3 The figure shows a hardware structure diagram of the battery charging and discharging device provided in the embodiment of the present application.

[0115] The battery charging and discharging device may include a processor 301 and a memory 302 storing computer program instructions.

[0116] Specifically, the processor 301 may include a central processing unit (CPU) or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0117] The memory 302 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 302 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In one example, the memory 302 may include a removable or non-removable (or fixed) medium, or the memory 302 may be a non-volatile solid-state memory. The memory 302 may be inside or outside the integrated gateway disaster recovery device.

[0118] In one example, the memory 302 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory 302 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present application.

[0119] The processor 301 reads and executes the computer program instructions stored in the memory 302 to implement Figure 1 The method / steps S110 to S170 in the embodiment shown, and achieving Figure 1 The corresponding technical effects achieved by executing the methods / steps in the illustrated example will not be repeated here for the sake of brevity.

[0120] In one example, the battery charging and discharging device may further include a communication interface 303 and a bus 310. Figure 3 As shown, the processor 301 , the memory 302 , and the communication interface 303 are connected via a bus 310 and communicate with each other.

[0121] The communication interface 303 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0122] Bus 310 includes hardware, software or both, and couples the components of battery charging and discharging equipment to each other. For example, and not limitation, bus may include Accelerated Graphics Port (AGP) or other graphics bus, Enhanced Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), Hyper Transport (HT) interconnection, Industry Standard Architecture (ISA) bus, InfiniBand interconnection, Low Pin Count (LPC) bus, memory bus, Micro Channel Architecture (MCA) bus, Peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 310 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0123] The battery charging and discharging device can execute the battery charging and discharging method in the embodiment of the present application based on the acquired base station data and the power outage time of the base station, thereby realizing the combination of Figure 1 Described battery charging and discharging method.

[0124] In addition, in conjunction with the battery charging and discharging methods in the above embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the battery charging and discharging methods in the above embodiments is implemented.

[0125] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0126] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0127] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0128] Aspects of the present application have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed via the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. This processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or the flowchart and the combination of the boxes in the block diagram and / or the flowchart can also be implemented by the dedicated hardware that performs the specified function or action, or can be implemented by the combination of dedicated hardware and computer instructions.

[0129] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A battery charging and discharging method, characterized in that: include: Obtaining target base station data, the target base station data including battery life of the target base station, electricity price information, power outage time data of the target base station within a first preset time period, the target base station location, and power outage time data of the target base station within a second preset time period, the target base station power outage time data including the power outage time and restoration time of the target base station, and the second preset time period including the first preset time period; Determining the battery charge and discharge time of the target base station according to the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information; Clustering the target base stations based on the locations of the target base stations and the power outage time data of the target base stations within the first preset time period to obtain a base station itemset; Calculating the base station itemset according to the power outage time of the target base station within the first preset time period to obtain a frequent itemset of the base station; Selecting itemsets containing the same base station data in the frequent itemsets of the base stations and fusing them to obtain at least one first set; Clustering the base station data in the target base station data except the item set containing the same base station data based on base station locations to obtain at least one second set; Evenly dividing the items in each of the at least one first set and the items in each of the at least one second set into a preset number of groups; The battery of the target base station is charged and discharged according to the preset number of groups and the charging and discharging time of the batteries of the target base stations in the groups.

2. The method according to claim 1, characterized in that The determining the battery charge and discharge time of the target base station according to the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information includes: Calculating the power outage time data of the target base station within the second preset time period to obtain the power outage period of the target base station; The charging and discharging time of the battery of the target base station is determined according to the power outage period of the target base station, the battery life of the target base station, and the electricity price information.

3. The method according to claim 2, characterized in that The calculating the power outage time data of the target base station within the second preset time period to obtain the power outage period of the target base station includes: Calculating the power outage time data of the target base station within the second preset time period to obtain a power outage period frequent item set of the target base station; The power outage period frequent item sets of the target base station are merged to obtain the power outage period of the target base station.

4. The method according to claim 2, characterized in that The determining the charge and discharge time of the battery of the target base station according to the power outage period of the target base station, the battery life of the target base station, and the electricity price information includes: Determining peak hours, normal hours, and off-peak hours based on the electricity price information; Calculating the battery discharge time according to the battery data of the target base station; After excluding the power outage period, a period that meets the dischargeable time of the battery is selected as the discharge period according to a preset first preset priority.

5. The method according to claim 4, characterized in that The method further comprises: After excluding the power outage period and the discharging period, the charging start time is selected according to a preset second preset priority.

6. The method according to claim 1, wherein The selecting of itemsets containing the same base station data in the frequent itemsets of the base stations and fusing them to obtain at least one first set includes: The base station data belonging to at least two frequent item sets are divided into sets with fewer items in the at least two frequent item sets.

7. The method according to claim 1, wherein charging and discharging the battery of the target base station according to the preset number of groups and the charging and discharging times of the batteries of the target base stations in the preset number of groups comprises: Select one of the groups as the target group; The batteries of the base stations in the target group are charged and discharged according to the charging and discharging time of the batteries of the target base station.

8. A battery charging and discharging device, characterized in that: The device comprises: an acquisition module, configured to acquire target base station data, the target base station data including battery life of the target base station, electricity price information, power outage time data of the target base station within a first preset time period, the target base station location, and power outage time data of the target base station within a second preset time period, the target base station power outage time data including the power outage time and restoration time of the target base station, the second preset time period including the first preset time period; a determination module, configured to determine a battery charge and discharge time of the target base station according to the power outage time data of the target base station within the second preset time period, the battery life of the target base station, and the electricity price information; a clustering module, configured to cluster the target base stations based on the locations of the target base stations and the power outage time data of the target base stations within the first preset time period to obtain a base station itemset; a calculation module, configured to calculate the base station itemset according to the power outage time of the target base station within the first preset time period to obtain a frequent itemset of the base station; A fusion module, configured to select itemsets containing the same base station data in the frequent itemsets of the base stations and fuse them to obtain at least one first set; The clustering module is further configured to cluster the base station data in the target base station data except the item set containing the same base station data based on the base station location to obtain at least one second set; a partitioning module, configured to evenly partition the items in each of the at least one first set and the items in each of the at least one second set into a preset number of groups; The charging and discharging module is used to charge and discharge the battery of the target base station according to the preset number of groups and the charging and discharging time of the batteries of the target base stations in the groups.

9. A battery charging and discharging device, characterized in that: The battery charging and discharging device includes: a processor, and a memory storing computer program instructions; The processor reads and executes the computer program instructions to implement the battery charging and discharging method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that The computer storage medium stores computer program instructions, which, when executed by a processor, implement the battery charging and discharging method according to any one of claims 1 to 7.

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