CN114390371B - Electric quantity scheduling method and device and electronic equipment - Google Patents

Abstract

Embodiments of the present invention provide a power scheduling method, device, and electronic equipment. The method includes: obtaining the power supply required by multiple AAU devices corresponding to the target aggregation nodes in the power supply network within a preset time period, and according to multiple The power supply required by the AAU equipment determines the total required power supply of the target aggregation node within the preset time period, determines whether the total required power supply of the target aggregation node meets the first preset condition within the preset time period, and When the total required power supply within the preset time period meets the first preset condition, the node determines the power scheduling strategy for power scheduling for the target sink node, and then performs power scheduling for the target sink node according to the power scheduling strategy. Through the embodiments of the present invention, it is possible to solve the technical problem that the power consumption of the 5G base station is too large to provide backup power guarantee for AAU-level equipment.

Description

A power scheduling method, device, and electronic equipment

technical field

The present invention relates to the technical field of mobile communication, in particular to a power scheduling method, device, and electronic equipment.

Background technique

The 5G base station is the core equipment of the communication network. It is mainly composed of BBU (Base band Unit, baseband processing unit) and AAU (Active Antenna Unit, active antenna unit). With the substantial improvement of 5G mobile communication technology performance indicators, the power consumption of base station equipment has also increased rapidly. Compared with the 8T/8R antenna of the 4G base station, the AAU of the 5G base station uses a 64T/64R antenna array, and the number of channels is greatly increased, which greatly increases the overall power consumption of the AAU. The power consumption of a single 5G base station system is 4 to 5 times that of a 4G base station system.

However, since the AAU is an active antenna unit, the AAU equipment in the 5G base station needs power supply to send the signal. Once the power supply of the above-mentioned base station is insufficient, it will not be able to guarantee the backup power supply for the AAU-level equipment. The situation that the AAU equipment in the above-mentioned base station cannot be supplied with power occurs, so that the base station cannot send signals normally, thereby affecting user experience.

Contents of the invention

The purpose of the embodiments of the present invention is to provide a power scheduling method, device and electronic equipment to solve the technical problem that the 5G base station consumes too much power and cannot provide backup power guarantee for AAU-level equipment.

In order to solve the above-mentioned technical problems, the embodiment of the present invention is implemented as follows:

In the first aspect, an embodiment of the present invention provides a power scheduling method, including:

Obtain the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period;

determining the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices;

judging whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition;

When the total power demand of the target convergence node within a preset time period satisfies the first preset condition, determine a power scheduling strategy for power scheduling for the target convergence node;

Perform power scheduling for the target sink node according to the power scheduling policy.

Optionally, the judging whether the total power demand of the target convergence node within a preset time period meets a first preset condition includes: acquiring the actual power supply of the target convergence node at a current moment;

According to the actual power supply amount of the target aggregation node at the current moment and the total required power amount of the target aggregation node, it is judged whether the total required power amount of the target aggregation node within a preset time period is less than the target aggregation node. The actual power supply at the current moment.

Optionally, in the case that the total power demand of the target convergence node within a preset time period meets the first preset condition, determining the power scheduling strategy for power scheduling for the target convergence node includes :

In the case that the total power demand of the target convergence node within the preset time period satisfies the first preset condition, according to the total power demand of the target convergence node within the preset time period and the current The actual power supply at any time, to determine the power to be dispatched by the target convergence node within the preset time period;

An electric quantity scheduling strategy for performing electric quantity scheduling for the target convergence node is determined according to the electric quantity to be dispatched.

Optionally, the above-mentioned determination of an electric quantity scheduling strategy for performing electric quantity scheduling for the target convergence node according to the electric quantity to be dispatched includes:

According to the electricity to be dispatched and the distribution area of each aggregation node in the power supply network, determine the aggregation node to be scheduled for power scheduling for the target aggregation node;

judging whether the scheduling of the electricity to be dispatched from the aggregation node to be scheduled meets a second preset condition;

When the second preset condition is satisfied, determine to execute an electric quantity scheduling strategy of dispatching the electric quantity to be dispatched from the to-be-scheduled converging node to the target converging node for electric quantity scheduling;

If the second preset condition is not satisfied, it is determined to prohibit the execution of the power scheduling policy of scheduling the power to be dispatched from the to-be-scheduled converging node to the target converging node for power scheduling.

Optionally, the above-mentioned judging whether the dispatching of the electricity to be dispatched from the convergence node to be dispatched meets a second preset condition includes:

According to the area where the aggregation node to be scheduled and the target aggregation node are located, determine the power consumption when the aggregation node to be scheduled is dispatching the electricity to be dispatched for the target aggregation node;

Judging whether the power consumption is less than a preset threshold.

Optionally, before the acquisition of the power supply required by the multiple AAU devices corresponding to the target convergence node in the power supply network within the preset time period, the method further includes:

Obtain the traffic data, traffic data, and RRC connection number corresponding to the AAU device in the historical time period;

Determine the required power consumption of the AAU device within a preset time period according to the traffic data, the traffic data, and the number of RRC connections;

According to the required power consumption of the AAU device within the preset time period, the power supply required by the plurality of AAU devices corresponding to each convergence node in the power supply network is determined within the preset time period.

Optionally, the above-mentioned target convergence node includes a BBU pool, the BBU pool includes multiple BBU devices, and multiple AAU devices are connected to the BBU device;

The method also includes:

The power supply network of multiple BBU devices corresponding to the multiple convergence nodes included in the target area is used as the convergence backbone, and the power supply lines of the multiple AAU devices connected to each BBU device are used as the convergence branches to construct a power supply network.

In a second aspect, an embodiment of the present invention provides a power scheduling device, including:

The first obtaining module is used to obtain the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period;

The first determination module is configured to determine the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices;

A judging module, configured to judge whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition;

A second determining module, configured to determine the amount of electricity for power scheduling of the target sink node when the total power demand of the target sink node within a preset time period satisfies the first preset condition Scheduling strategy;

A power scheduling module, configured to perform power scheduling for the target aggregation node according to the power scheduling policy.

In the third aspect, the embodiment of the present invention provides an electronic device, including: including a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory complete the mutual communication through the bus Communication; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to implement the steps of the power scheduling method as described in the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the power scheduling as described in the first aspect is implemented Method steps.

In the power scheduling method, device, and electronic equipment in the embodiments of the present invention, by obtaining the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period, according to the power supply required by multiple AAU devices Determine the total required power supply of the target aggregation node within the preset time period, determine whether the total required power supply of the target aggregation node within the preset time period meets the first preset condition, and When the total required power supply in the segment satisfies the first preset condition, determine the power scheduling strategy for power scheduling for the target sink node, and then perform power scheduling for the target sink node according to the power scheduling strategy. Through the embodiments of the present invention, it is possible to solve the technical problem that the power consumption of the 5G base station is too large to provide backup power guarantee for AAU-level equipment.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments described in the present invention. Those skilled in the art can also obtain other drawings based on these drawings without any creative effort.

Fig. 1 is a schematic flow chart of the first kind of electric quantity dispatching method provided by the embodiment of the present invention;

Fig. 2 is a second schematic flow chart of the power scheduling method provided by the embodiment of the present invention;

FIG. 3 is a schematic flow chart of a third power scheduling method provided by an embodiment of the present invention;

FIG. 4 is a schematic diagram of a fourth flow chart of a power scheduling method provided by an embodiment of the present invention;

Fig. 5 is a schematic flow chart of a fifth type of electricity scheduling method provided by an embodiment of the present invention;

FIG. 6 is a structural diagram of a power supply network provided by an embodiment of the present invention;

Fig. 7 is a schematic diagram of the module composition of the power dispatching device provided by the embodiment of the present invention;

FIG. 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention.

Detailed ways

Embodiments of the present invention provide a method, device and electronic equipment for power scheduling.

In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in Figure 1, an embodiment of the present invention provides a power scheduling method. The execution subject of the method may be a server or a network device, wherein the server may be an independent server, a distributed server, or a A server cluster composed of multiple servers, and the server or network device may be a server or network device capable of determining a power scheduling strategy for the target aggregation node. The method specifically may include the following steps:

In step S102, the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period is obtained.

Wherein, the aforementioned preset time period may be from 8:00 am to 12:00 noon, or from 12:00 noon to 18:00 pm, or from 18:00 pm to 24:00 am. Or, the above preset time period can also be every preset time interval in the preset time period, for example: it can be every 15 minutes or 30 minutes from 8:00 am to 12:00 noon, or it can also be from 8:00 am to 12:00 noon. Every 15 minutes or 30 minutes between 0:00 and 24:00.

The foregoing power supply network may be composed of a plurality of convergence nodes and a power transmission line network in which a plurality of AAU devices connected to each convergence node are located. The aggregation node may be an equipment room where BBU equipment is centrally placed in the base station, that is, a BBU pool equipment room. The target aggregation node may be an aggregation node carrying target identification information, and the target identification may be identification information for distinguishing each aggregation node, for example, a geographic name of an area where the aggregation node is located. Each of the above-mentioned BBU pool machine rooms is equipped with a set of independent power supply equipment, which may include switching power supply cabinets, AC power distribution cabinets, storage batteries and other equipment. Wherein, multiple BBU devices can be placed in the BBU pool computer room, and at least one AAU device is connected to each BBU device. Specifically, taking a certain city as an example, there are mainly four computer rooms in which BBU equipment is centralized, that is, BBU pool computer rooms. These four BBU pool computer rooms correspond to a power supply area respectively, that is, each BBU pool computer room The power supply for the BBU equipment in the pool equipment room and the multiple AAU equipment attached to the BBU equipment can be determined according to the network formed by the power transmission lines of the four BBU pool equipment rooms and the multiple AAU equipment attached to the BBU pool equipment rooms. Networking for power supply.

It should be noted that the electricity between the aggregation nodes in the above power supply network can be transferred to each other. For example, the above four BBU pool computer rooms are respectively A computer room, B computer room, C computer room and D computer room. When the above four When a computer room in a BBU pool computer room (such as A computer room) has insufficient power to supply power to the AAU device connected to a BBU device in the BBU pool computer room, the income from dispatching power during the power scheduling process is satisfied. When it is much greater than the value corresponding to the power loss that occurs during the power scheduling process, or when the power loss that occurs during the power scheduling process is less than a predetermined threshold, at least one BBU pool can be selected from the power supply network computer room, and draw an appropriate amount of power from the power of at least one selected BBU pool computer room to supply the above-mentioned computer room with insufficient power. In this way, by scheduling the power between the aggregation nodes in the power supply network, It can provide favorable backup power guarantee for AAU-level equipment in the power supply network.

In the process of implementation, in the process of constructing 5G network based on the base station of the existing network and the follow-up higher-level network of the 5G network, it mainly faces problems such as mains capacity, DC power capacity, backup power time, and output power distribution. Or replace the existing power supply equipment solution, but this solution has a long implementation period, which will hinder the rapid construction of 5G/6G networks and increase the construction and operation and maintenance costs, mainly in the following aspects: For sites with insufficient mains power capacity , It takes a long time for the application and construction of the mains capacity increase (generally 3 to 6 months), and some dense urban sites cannot carry out the construction of the mains capacity increase project due to the limited overall capacity of the power grid and the difficulty of laying lines; for sites with insufficient DC power capacity, In the face of insufficient expansion slots for rectifier modules or the suspension of production of rectifier modules of the same type, system expansion cannot be performed, and the entire DC power supply system needs to be replaced, which affects the normal operation of communication equipment on the existing network, and at the same time causes waste of existing power equipment assets and increases construction costs; for Sites with insufficient power backup time are mainly faced with insufficient space or load bearing in the equipment room, and cannot expand or replace the battery pack, which affects the reliability of power supply and increases the cost of operation and maintenance support. For the long-distance (greater than 100 meters) outdoor high-power consumption equipment (such as: AAU equipment) power supply site, the indoor -48V DC power supply is used, the power supply line loss is large, and the low terminal voltage causes the communication equipment to fail to work normally. It is necessary to add a separate set The booster equipment adjusts the output power supply voltage according to the power supply distance, which cannot be matched with the existing power supply management, which has a certain impact on the reliability of power supply and increases the cost of construction operation and maintenance. Based on the above problems, at present, for each power supply room (such as the BBU pool machine room), it is impossible to implement a separate backup power guarantee for the AAU equipment at each point. In the process of power supply, it is also difficult to solve the problems of the physical location of the control, the power supply conditions, and the cost of the backup power supply. To this end, the embodiments of the present invention provide a technical solution capable of solving the above problems, and details may be referred to the following content.

Taking the above power supply network as an example composed of multiple convergence nodes and a power transmission line network where multiple AAU devices connected to each convergence node are located, obtain the network diagram of the power supply area of each convergence node included in the target area Specifically, the network diagram of the above power supply area may include the power supply line network diagram of the BBU equipment corresponding to each convergence node, and the power supply line network diagram of each AAU equipment corresponding to each BBU equipment. The network diagram of the power supply line of the BBU equipment corresponding to each aggregation node in the network, and the network diagram of the power supply line of each AAU equipment corresponding to each BBU equipment to construct the power supply network in the above target area, so that the above network area can be connected to The overall scheduling of the electricity between the aggregation nodes, or the overall scheduling of the electricity between the aggregation nodes in the above-mentioned networking area, and the separate scheduling of the electricity in each aggregation node, In this way, by scheduling the power between the aggregation nodes in the power supply network, it can provide a favorable backup power guarantee for the AAU-level equipment in the power supply network, which not only avoids the construction of 5G network and the construction of 5G In the follow-up higher-level network process of the network, the implementation period caused by capacity expansion or replacement of the existing power supply equipment is long, the implementation cost of operation and maintenance is high, and a lot of manpower and material resources are wasted. The problem of unified management of the power supply of multiple base stations included.

It should be noted that the construction process of the power supply network corresponding to the above-mentioned target area can be varied, and can be based on the power supply line network diagram of the BBU equipment corresponding to each convergence node in the target area obtained above, as well as the power supply network diagram of each BBU The power supply line network diagram of each AAU device corresponding to the device, the line corresponding to the power transmission between the convergence nodes in the target area is used as the main power supply line, and the power supply line of each AAU device corresponding to each BBU device Construct the power supply network in the target area as a power supply aggregation branch line; or, it can also use the power supply line network diagram of multiple BBU equipment corresponding to each aggregation node, and the AAU equipment corresponding to each BBU equipment Power supply line network diagram, construct the regional power supply network of the power supply area corresponding to each aggregation node, and then construct the target area according to the constructed regional power supply network of each power supply area and the distribution area of each aggregation node in the target area The internal power supply network. Alternatively, the power supply network in the target area may also be constructed in other ways, which is not specifically limited in this embodiment of the specification.

In implementation, after constructing a power supply network corresponding to the above-mentioned target area for multiple aggregation nodes included in a certain target area, the server can obtain the target aggregation nodes in the power supply network within a preset time period through a predetermined interface The power supply required by the corresponding multiple AAU devices.

Specifically, according to the target identification information corresponding to the target aggregation node, the server can search for the historical power supply information of multiple AAU devices corresponding to the target aggregation node corresponding to the target identification information within the historical preset time period, and according to the historical Power supply information, to estimate the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within the preset time period, so that the corresponding information of the target aggregation node in the power supply network within the preset time period can be obtained Amount of power required by multiple AAU devices. Or, the server can also obtain the signaling data of multiple BBU devices attached to the target convergence node in the above-mentioned power supply network according to the target identification information corresponding to the target convergence node, and analyze the signaling data from each BBU The signaling data obtained by the device is used to estimate the required power supply of multiple AAU devices corresponding to the target aggregation node within the preset time period, and then obtain the required power supply of the target aggregation node in the power supply network within the preset time period. The power supply required by the corresponding multiple AAU devices.

In step S104, according to the required power supply of multiple AAU devices, the total required power supply of the target convergence node within a preset time period is determined.

In implementation, after the server obtains the power supply required by the multiple AAU devices corresponding to the target aggregation node in the power supply network within the preset time period through the above-mentioned processing of S102, it can , determine the power supply required by the BBU device that mounts the above-mentioned multiple AAU devices, and then can determine the target sink node according to the determined power supply required by the multiple BBU devices contained in the target sink node The total power demand in the time period.

In step S106, it is judged whether the total power demand of the target aggregation node within a preset time period satisfies a first preset condition.

In implementation, after the server has determined the total power demand of the target convergence node within the preset time period through the above-mentioned processing of S104, it can find out the historical preset time period according to the target identification information of the target convergence node. The historical power consumption information of the target sink node corresponding to the target identification information, and determine whether the total power demand of the target sink node in the preset time period is greater than the historical power consumption of the target sink node in the above-mentioned historical preset time period .

In step S108, when the total power demand of the target sink node within a preset time period satisfies a first preset condition, an electric power scheduling strategy for power scheduling for the target sink node is determined.

In implementation, the server determines to implement the power scheduling strategy for the target sink node when it determines that the total power demand of the target sink node within a preset time period meets the first preset condition through the processing of S106. Wherein, the above power scheduling strategy may be based on the area where the target sink node is located, to determine the scheduling strategy of at least one sink node in the power supply network that performs power scheduling for the target sink node, or it may also be based on the target sink node In the region where the target convergence node is located, at least one convergence node in the power supply network that performs power scheduling for the target convergence node and a scheduling strategy for scheduling preset power from the at least one convergence node can be determined, or it can also be based on where the target convergence node is located. Area, determine at least one convergence node in the power supply network for power scheduling for the target convergence node, schedule preset power from the at least one convergence node, and schedule at least one convergence node to perform power scheduling for the target convergence node Scheduling strategy of scheduling sequence, etc.

Specifically, when the server judges that the total required power supply of the target convergence node within the preset time period is greater than the historical power consumption of the target convergence node within the above historical preset time period through the above S106 processing, it may be determined as The power scheduling strategy for the above-mentioned target convergence node to perform power scheduling.

In step S110, power scheduling is performed for the target sink node according to the power scheduling policy.

In implementation, after the server determines the power scheduling strategy for power scheduling for the target convergence node through the above-mentioned processing of S108, it may perform power scheduling for the target convergence node according to the determined power scheduling strategy.

It can be seen from the above technical solutions provided by the embodiments of the present invention that the embodiments of the present invention obtain the power supply required by multiple AAU devices corresponding to the target convergence node in the power supply network within a preset time period, and according to the power supply required by the multiple AAU devices Determine the total required power supply of the target aggregation node within the preset time period, determine whether the total required power supply of the target aggregation node within the preset time period meets the first preset condition, and When the total required power supply in the segment satisfies the first preset condition, determine the power scheduling strategy for power scheduling for the target sink node, and then perform power scheduling for the target sink node according to the power scheduling strategy. Through the embodiment of the present invention, it is possible to solve the technical problem that the power consumption of the 5G base station is too large to provide backup power guarantee for the AAU-level equipment.

Further, the specific processing process of the above-mentioned step S108 can be varied, and an optional processing process is provided below, for details, please refer to the specific processing process of the following steps 1 to 2.

Step 1: Obtain the actual power supply amount of the target sink node at the current moment.

In implementation, the server may obtain the actual power supply amount of the target convergence node at the current moment according to the target identification information of the target convergence node.

Specifically, since the aggregation node in the embodiment of this specification may be a computer room where BBU equipment is centrally placed in a base station, that is, a BBU pool computer room. The server can obtain the current target ID according to the target identification information of the above-mentioned BBU pool computer room and the current actual power supply of the power supply equipment in the BBU pool computer room (such as the current actual power supply of switching power supply cabinets, AC power distribution cabinets, storage batteries and other equipment) The actual power supply of the target BBU pool equipment room corresponding to the information.

Step 2: According to the actual power supply of the target sink node at the current moment and the total power demand of the target sink node, it is judged whether the total power supply demand of the target sink node within the preset time period is less than the actual power supply of the target sink node at the current moment.

In the implementation, after the server obtains the actual power supply of the target sink node at the current moment through the processing of the above step 1, it can judge the target sink node according to the actual power supply of the target sink node at the current moment and the total power demand of the target sink node Whether the total required power supply within the preset time period is less than the actual power supply of the target sink node at the current moment.

Further, as shown in FIG. 2 , the specific processing procedure of the above-mentioned step S108 may be varied, and an optional processing procedure is provided below, and details may refer to the specific processing procedures of the following steps S1082 to S1084.

In step S1082, if the total power demand of the target convergence node within the preset time period meets the first preset condition, according to the total power demand of the target convergence node within the preset time period and the actual The amount of power supply determines the amount of electricity to be dispatched by the target aggregation node within the preset time period.

In implementation, the server determines that the total power demand of the target convergence node within the preset time period is greater than the historical power consumption of the target convergence node within the preset historical time period through the processing of the above S106, or the server determines through In the processing of S106 above, when it is determined that the total power demand of the target convergence node within the preset time period is less than the actual power supply of the target convergence node at the current moment, the target convergence node can be calculated by calculating the The difference between the total required power supply and the actual power supply at the current moment determines the power to be dispatched by the target sink node within a preset time period. In step S1084, an electric quantity scheduling strategy for performing electric quantity scheduling for the target sink node is determined according to the electric quantity to be dispatched.

Specifically, as shown in FIG. 3 , for the specific processing procedure of the above step S1084, reference may be made to the specific processing procedures of the following step S10842 to step S10848.

In step S10842, according to the electricity to be dispatched and the distribution area of each aggregation node in the power supply network, determine the aggregation node to be dispatched as the target aggregation node for power scheduling.

Wherein, the convergence node to be scheduled may be a convergence node in the power supply network that is relatively close to the area where the target convergence node is located, or may also be a convergence node with sufficient power supply in the power supply network (that is, the convergence node may be In addition to satisfying its own equipment power consumption, it can also provide power for other sink nodes).

In implementation, after the server determines the power to be dispatched by the target sink node within the preset time period through the above-mentioned processing of S1082, it can determine the power consumption of the target sink node according to the power to be dispatched and the distribution area of each sink node in the power supply network. Scheduled aggregation nodes to be scheduled.

In step S10844, it is judged whether the scheduling of the electricity to be dispatched from the convergence node to be dispatched satisfies the second preset condition.

Specifically, as shown in FIG. 4 , for the specific processing process of the above step S10844, refer to the specific processing process of the following step S108442 to step S108444.

In step S108442, according to the areas where the aggregation node to be scheduled and the target aggregation node are located, the power consumption when the aggregation node to be scheduled is scheduled for the target aggregation node is determined.

In step S108444, it is determined whether the power consumption is less than a preset threshold.

In implementation, for example, the above-mentioned preset threshold is 10w. After the server determines the to-be-scheduled converging node for power scheduling as the target converging node through the above-mentioned processing of S10842, according to the areas where the to-be-scheduled converging node and the target converging node are located, determine from When the power consumption to be dispatched by the aggregation node to be dispatched is 10kw for the target aggregation node, it is judged that the power consumption is far greater than the preset threshold (10w), and the power consumption is judged to be greater than the preset threshold, and the second predetermined set conditions. If the server determines through the above processing process that the power consumption when scheduling the power to be dispatched from the sink node to be dispatched as the target sink node is 8w is less than the preset threshold (10w), then it is judged that the power consumption is less than the preset threshold, and then it is determined that the above second preset conditions. In step S10846, if the second preset condition is satisfied, it is determined to execute the power scheduling policy of scheduling the power to be dispatched from the to-be-scheduled converging node to the target converging node for power scheduling. In step S10848, if the second preset condition is not satisfied, it is determined that the execution of the power scheduling policy that schedules the power to be dispatched from the to-be-scheduled convergence node to the target convergence node for power scheduling is prohibited is determined.

Further, before the above step S102, as shown in FIG. 5 , the above method may further include the following processing procedures from step S002 to step S006.

In step S002, the flow data, traffic data, and RRC connection number corresponding to the AAU device within a historical time period are acquired.

In step S004, the required power consumption of the AAU device within a preset time period is determined according to the traffic data, traffic data, and RRC connection number.

In step S006, according to the required power consumption of the AAU devices within the preset time period, the power supply required by the plurality of AAU devices corresponding to each convergence node in the power supply network is determined within the preset time period.

In implementation, the required power consumption of the AAU devices corresponding to each sink node within a preset time period can be determined according to the power distribution model of multiple AAU devices corresponding to each sink node in the pre-built power supply network. Wherein, the above power distribution model can be: y=b ₀ +b ₁ x ₁ +b ₂ x ₂ +b ₃ x ₃ +...b _n x _n , the above b ₀ is an adjustment constant, the above b ₁ , b ₂ , b ₃ , and b _n are the variable coefficients of the power distribution model above, and the above y represents the power that the sink node needs to distribute to the above-mentioned AAU devices within the preset time period (that is, y represents the power of each AAU device corresponding to the sink node within the preset time period. required power consumption of the AAU device).

The above x ₁ , x ₂ , x ₃ , and x _n may be wireless performance data corresponding to each AAU device obtained from the BBU device, for example, traffic data, traffic data, number of RRC connections, etc., wherein the above x _n can also be determined based on the user's interests in the scenario, the business and value of the community in the scenario, seasonal property classification information, competitor information, etc. The user's interest in the above scenario can be determined through the business volume, the value generated by the site, and the consumption habits of individual users in the coverage area. The corresponding evaluation indicators formulated by the comprehensive judgment. The business and value of the above-mentioned scenario community refers to the corresponding scoring rule indicators formulated for different scenarios according to the network coverage scenario. The above-mentioned seasonal property classification information refers to the evaluation indicators of time season and property maintenance difficulty information. , the above competitor information refers to the evaluation indicators formulated based on the obtained competitor’s base station maintenance frequency and emergency power generation frequency.

Taking the calculation of the flow data, traffic data, and RRC connection number obtained in the preset time period as an example in the process of calculating the power supply required by the AAU equipment within the preset time period, x ₁ represents the flow data, x ₂ represents the traffic data, and x ₃ represents the number of RRC connections. The above power distribution model can be: y=b ₀ +b ₁ x ₁ +b ₂ x ₂ +b ₃ x ₃ , which can be obtained through multiple sets of historical time periods in advance The traffic data, traffic data, and RRC connection numbers corresponding to each AAU device in the network, and the historical power consumption of the above-mentioned AAU devices in the historical time period corresponding to the above traffic data, traffic data, and RRC connection data, Correspondingly bring the obtained above data into the above electric power distribution model, the specific data corresponding to b ₁ , b ₂ , b ₃ can be calculated, and then the electric power distribution model of each AAU device corresponding to each sink node can be determined. In this way, after determining the power distribution model of each AAU device corresponding to each sink node, the traffic data, traffic data, and RRC numbers corresponding to the AAU device obtained in the historical time period can be brought into the above-mentioned The determined power distribution model can determine the required power consumption of the AAU device within a preset time period. Furthermore, according to the determined required power consumption of the AAU devices within the preset time period, the power supply required by the plurality of AAU devices corresponding to each convergence node in the power supply network can be determined within the preset time period.

Furthermore, since the power supply of AAU equipment in the current base station is a rigid power supply direct access mode, the power supply status of BBU equipment to AAU equipment cannot be monitored and dynamically allocated. In order to form a power supply mode for intelligent networking and dynamically allocate power resources, And carry out safe and effective supervision on the data of AAU power consumption. The embodiment of this manual also needs to store the power consumption data of AAU equipment in the node server at the edge end for analysis and processing. The above power consumption data can be the current value and voltage value of AAU equipment. , the number of users in the community, user traffic and flow, benefits obtained by scene users, business and value of the scene community, seasonal property classification, competitor information, business scope data, etc., and record the data and processing results in the above server at the same time.

Among them, there are various methods for constructing the above-mentioned power supply network, and an optional construction method for constructing the above-mentioned power supply network is provided below. For the specific construction process, please refer to the following content:

Use the power supply lines of multiple BBU devices corresponding to the multiple convergence nodes contained in the target area as the convergence backbone, and use the power supply lines of multiple AAU devices connected to each BBU device as the convergence branches to construct a power supply network. Among them, The foregoing power supply network may be a herringbone power supply network.

Specifically, as shown in Figure 6, Figure 6 is a constructed fishbone power supply network, wherein the above-mentioned aggregation backbone is the power supply lines of multiple BBU devices corresponding to the multiple aggregation nodes contained in the target area, and the convergence The trunk is the power supply line where multiple AAU devices connected to each BBU device are located.

It can be seen from the above technical solutions provided by the embodiments of the present invention that the embodiments of the present invention obtain the power supply required by multiple AAU devices corresponding to the target convergence node in the power supply network within a preset time period, and according to the power supply required by the multiple AAU devices Determine the total required power supply of the target aggregation node within the preset time period, determine whether the total required power supply of the target aggregation node within the preset time period meets the first preset condition, and When the total required power supply in the segment satisfies the first preset condition, determine the power scheduling strategy for power scheduling for the target sink node, and then perform power scheduling for the target sink node according to the power scheduling strategy. Through the embodiment of the present invention, it is possible to solve the technical problem that the power consumption of the 5G base station is too large to provide backup power guarantee for the AAU-level equipment.

Corresponding to the power scheduling method provided in the above embodiments, based on the same technical concept, the embodiment of the present invention also provides a power scheduling device. FIG. 7 is a schematic diagram of the module composition of the power scheduling device provided in the embodiment of the present invention. The power scheduling device For implementing the power scheduling method described in Figures 1 to 6, as shown in Figure 7, the power scheduling device includes:

The first acquiring module 701 is configured to acquire the power supply required by multiple AAU devices corresponding to the target convergence node in the power supply network within a preset time period;

The first determining module 702 is configured to determine the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices;

A judging module 703, configured to judge whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition;

The second determining module 704 is configured to determine the power scheduling for the target sink node when the total power demand of the target sink node within a preset time period satisfies the first preset condition Power dispatch strategy;

The power scheduling module 705 is configured to perform power scheduling for the target aggregation node according to the power scheduling policy.

Optionally, the judging module includes

an acquisition unit, configured to acquire the actual power supply of the target sink node at the current moment;

A judging unit, configured to judge whether the total required power supply of the target convergence node within a preset time period is less than The actual power supply amount of the target aggregation node at the current moment.

Optionally, the above-mentioned second determination module includes:

The first determining unit is configured to, in the case that the total demanded power of the target convergence node within the preset time period satisfies a first preset condition, According to the total required power supply and the actual power supply at the current moment, determine the power to be dispatched by the target convergence node within the preset time period;

The second determining unit is configured to determine, according to the electricity to be dispatched, a power scheduling strategy for performing power scheduling for the target convergence node.

Optionally, the above-mentioned second determining unit includes:

The first determining subunit is configured to determine a converging node to be dispatched for power scheduling for the target converging node according to the electric quantity to be dispatched and the distribution area of each converging node in the power supply network;

The second determining subunit is used to judge whether the scheduling of the electricity to be dispatched from the aggregation node to be scheduled meets a second preset condition;

The first execution subunit is configured to determine and execute an electric power scheduling strategy for scheduling the power to be dispatched from the converging node to be scheduled to the target converging node for power scheduling when the second preset condition is met;

The second execution subunit is configured to determine that the execution of power scheduling that is prohibited from scheduling the power to be scheduled from the convergence node to be scheduled to the target convergence node for power scheduling is prohibited if the second preset condition is not met. Strategy.

Optionally, the above-mentioned second determining subunit is used for:

According to the area where the aggregation node to be scheduled and the target aggregation node are located, determine the power consumption when the aggregation node to be scheduled is dispatching the electricity to be dispatched for the target aggregation node;

Judging whether the power consumption is less than a preset threshold.

Optionally, the above-mentioned device also includes:

The second acquisition module is used to acquire traffic data, traffic data, and RRC connection numbers corresponding to the AAU equipment in the historical time period;

The third determining module is used to determine the required power consumption of the AAU device within a preset time period according to the traffic data, traffic data, and RRC connection number;

A fourth determining module, configured to determine the power supply required by multiple AAU devices corresponding to each convergence node in the power supply network within the preset time period according to the required power consumption of the AAU device within the preset time period .

Optionally, the target aggregation node includes a BBU pool, the BBU pool includes multiple BBU devices, and multiple AAU devices are connected to the BBU device, and the device further includes:

The networking module is used to use the power supply lines of multiple BBU devices corresponding to the multiple convergence nodes included in the target area as the convergence backbone, and use the power supply lines of the multiple AAU devices connected to each of the BBU devices as the convergence branches Dry construction of power supply network.

It can be seen from the above technical solutions provided by the embodiments of the present invention that the embodiments of the present invention obtain the power supply required by multiple AAU devices corresponding to the target convergence node in the power supply network within a preset time period, and according to the power supply required by the multiple AAU devices Determine the total required power supply of the target aggregation node within the preset time period, determine whether the total required power supply of the target aggregation node within the preset time period meets the first preset condition, and When the total required power supply in the segment satisfies the first preset condition, determine the power scheduling strategy for power scheduling for the target sink node, and then perform power scheduling for the target sink node according to the power scheduling strategy. Through the embodiments of the present invention, it is possible to solve the technical problem that the power consumption of the 5G base station is too large to provide backup power guarantee for AAU-level equipment.

The power scheduling device provided in the embodiment of the present invention can implement each process in the embodiment corresponding to the above power scheduling method, and to avoid repetition, details are not repeated here.

It should be noted that the power scheduling device provided in the embodiment of the present invention and the power scheduling method provided in the embodiment of the present invention are based on the same inventive concept, so the specific implementation of this embodiment can refer to the implementation of the aforementioned power scheduling method, and the repetition is no longer repeat.

Corresponding to the power scheduling method provided in the above-mentioned embodiments, based on the same technical concept, the embodiment of the present invention also provides an electronic device, which is used to execute the above-mentioned power scheduling method. FIG. A schematic structural diagram of an electronic device, as shown in FIG. 8 , the electronic device may have relatively large differences due to different configurations or performances, and may include one or more than one processor 801 and memory 802, and the memory 802 may store one or more More than one stores applications or data. Wherein, the storage 802 may be a short-term storage or a persistent storage. The application program stored in the memory 802 may include one or more modules (not shown), and each module may include a series of computer-executable instructions in the electronic device. Furthermore, the processor 801 may be configured to communicate with the memory 802, and execute a series of computer-executable instructions in the memory 802 on the electronic device. The electronic device may also include one or more power sources 803 , one or more wired or wireless network interfaces 804 , one or more input/output interfaces 805 , and one or more keyboards 806 .

Specifically in this embodiment, the electronic device includes a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory complete communication with each other through the bus; the memory uses for storing computer programs; the processor is used to execute the programs stored in the memory, and realize the following method steps:

Obtain the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period;

determining the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices;

judging whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition;

When the total power demand of the target convergence node within a preset time period satisfies the first preset condition, determine a power scheduling strategy for power scheduling for the target convergence node;

Perform power scheduling for the target sink node according to the power scheduling strategy.

The embodiment of the present application also provides a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, the following method steps are implemented:

Obtain the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period;

determining the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices;

judging whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition;

When the total power demand of the target convergence node within a preset time period satisfies the first preset condition, determine a power scheduling strategy for power scheduling for the target convergence node;

Perform power scheduling for the target sink node according to the power scheduling policy.

It can be seen from the above technical solutions provided by the embodiments of the present invention that the embodiments of the present invention obtain the power supply required by multiple AAU devices corresponding to the target convergence node in the power supply network within a preset time period, and according to the power supply required by the multiple AAU devices Determine the total required power supply of the target aggregation node within the preset time period, determine whether the total required power supply of the target aggregation node within the preset time period meets the first preset condition, and When the total required power supply in the segment satisfies the first preset condition, determine the power scheduling strategy for power scheduling for the target sink node, and then perform power scheduling for the target sink node according to the power scheduling strategy. Through the embodiments of the present invention, it is possible to solve the technical problem that the power consumption of the 5G base station is too large to provide backup power guarantee for AAU-level equipment.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, apparatuses, or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

In a typical configuration, the electronic device includes one or more processors (CPUs), input/output interfaces, network interfaces and memory.

Memory may include non-permanent storage in computer readable media, in the form of random access memory (RAM) and/or nonvolatile memory such as read only memory (ROM) or flash RAM. Memory is an example of computer readable media.

Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can be implemented by any method or technology for storage of information. Information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Flash memory or other memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, Magnetic tape cartridge, tape magnetic disk storage or other magnetic storage device or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media excludes transitory computer-readable media, such as modulated data signals and carrier waves.

It can be understood that the embodiments described in the embodiments of the present invention may be implemented by hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (Application Specific Integrated Circuits, ASIC), digital signal processor (Digital Signal Processing, DSP), digital signal processing device (DSP Device, DSPD), programmable logic Equipment (ProgrammableLogic Device, PLD), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), general-purpose processor, controller, microcontroller, microprocessor, other electronic units for performing the functions described in the present invention or a combination thereof.

For software implementation, the techniques described in the embodiments of the present invention may be implemented through modules (such as procedures, functions, etc.) that execute the functions described in the embodiments of the present invention. Software codes can be stored in memory and executed by a processor. Memory can be implemented within the processor or external to the processor.

It should also be noted that, in this document, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that includes a set of elements includes not only those elements , but also includes other elements not expressly listed, or also includes elements inherent in such process, method, commodity or equipment. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element.

Those skilled in the art should understand that the embodiments of the present application may be provided as methods, devices or computer program products. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The above descriptions are only examples of the present application, and are not intended to limit the present application. For those skilled in the art, various modifications and changes may occur in this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims (8)

1. A power scheduling method, characterized in that the method comprises: Obtain the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period; determining the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices; judging whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition; When the total power demand of the target convergence node within a preset time period satisfies the first preset condition, determine a power scheduling strategy for power scheduling for the target convergence node; performing power scheduling for the target sink node according to the power scheduling strategy; The determination of the power scheduling strategy for the target convergence node to perform power scheduling includes: determining the electricity to be dispatched by the target aggregation node within a preset time period; According to the electricity to be dispatched and the distribution area of each aggregation node in the power supply network, determine the aggregation node to be scheduled for power scheduling for the target aggregation node; According to the area where the aggregation node to be scheduled and the target aggregation node are located, determine the power consumption when the aggregation node to be scheduled is dispatching the electricity to be dispatched for the target aggregation node; judging whether the power consumption is less than a preset threshold; In the case that the power consumption is less than a preset threshold, determine to execute a power scheduling strategy of scheduling the power to be dispatched from the convergence node to be scheduled to the target convergence node for power scheduling; In a case where the power consumption is not less than the preset threshold, it is determined that the execution of the power scheduling policy of scheduling the power to be dispatched from the convergence node to be scheduled to the target convergence node for power scheduling is determined to be prohibited. 2. The method according to claim 1, wherein the judging whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition comprises: Acquiring the actual power supply amount of the target aggregation node at the current moment; According to the actual power supply amount of the target aggregation node at the current moment and the total required power amount of the target aggregation node, it is judged whether the total required power amount of the target aggregation node within a preset time period is less than the target aggregation node. The actual power supply at the current moment. 3. The method according to claim 1, characterized in that, when the total required power supply of the target convergence node within a preset time period satisfies a first preset condition, it is determined as the The power scheduling strategy of the target aggregation node for power scheduling, including: In the case that the total power demand of the target convergence node within the preset time period satisfies the first preset condition, according to the total power demand of the target convergence node within the preset time period and the current The actual power supply at any time, to determine the power to be dispatched by the target convergence node within the preset time period; An electric quantity scheduling strategy for performing electric quantity scheduling for the target convergence node is determined according to the electric quantity to be dispatched. 4. The method according to claim 1, characterized in that, before the acquisition of the power supply required by the multiple AAU devices corresponding to the target convergence node in the power supply network within the preset time period, the method further comprises : Obtain the traffic data, traffic data, and RRC connection number corresponding to the AAU device in the historical time period; Determine the required power consumption of the AAU device within a preset time period according to the traffic data, the traffic data, and the number of RRC connections; According to the required power consumption of the AAU device within the preset time period, the power supply required by the plurality of AAU devices corresponding to each convergence node in the power supply network is determined within the preset time period. 5. The method according to claim 1, wherein the target aggregation node includes a BBU pool, the BBU pool includes multiple BBU devices, and multiple AAU devices are connected to the BBU device; The method also includes: The power supply network of multiple BBU devices corresponding to the multiple convergence nodes included in the target area is used as the convergence backbone, and the power supply lines of the multiple AAU devices connected to each BBU device are used as the convergence branches to construct a power supply network. 6. A power dispatching device, characterized in that the device comprises: The first obtaining module is used to obtain the power supply required by multiple AAU devices corresponding to the target aggregation node in the power supply network within a preset time period; The first determination module is configured to determine the total required power supply of the target aggregation node within a preset time period according to the required power supply of multiple AAU devices; A judging module, configured to judge whether the total required power supply of the target convergence node within a preset time period satisfies a first preset condition; A second determining module, configured to determine the target aggregation node for power scheduling when the total required power supply of the target aggregation node within a preset time period does not meet the first preset condition Power dispatch strategy; A power scheduling module, configured to perform power scheduling for the target convergence node according to the power scheduling policy; The second determination module includes: a first determining unit, configured to determine the electricity to be dispatched by the target convergence node within a preset time period; The first determination subunit is configured to determine a converging node to be dispatched for power scheduling for the target converging node according to the electric quantity to be dispatched and the distribution area of each converging node in the power supply network; The second determining subunit is to determine the power consumption when scheduling the electricity to be dispatched from the convergence node to be scheduled for the target convergence node according to the areas where the convergence node to be scheduled and the target convergence node are located; judging whether the power consumption is less than a preset threshold; A first executing subunit, configured to determine and execute an electric power scheduling strategy for scheduling the electric power to be dispatched from the converging node to be scheduled to the target converging node for electric power scheduling when the power consumption is less than a preset threshold; The second execution subunit is configured to determine that the execution of power scheduling that is prohibited from scheduling the power to be dispatched from the convergence node to be scheduled to the target convergence node for power scheduling is prohibited when the power consumption is not less than a preset threshold value Strategy. 7. An electronic device, characterized in that it includes a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory complete mutual communication through the bus; the memory, It is used to store computer programs; the processor is used to execute the programs stored in the memory, so as to realize the steps of the power scheduling method according to any one of claims 1-5. 8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the electric quantity according to any one of claims 1-5 is realized. Schedule method steps.