A 5G base station energy storage control method considering the base station communication load state

Abstract

The present invention discloses a 5G base station energy storage control method that takes into account the base station communication load state and belongs to the field of energy storage charge and discharge control technology. The present invention first analyzes the 5G base station energy storage and communication load state, and determines whether the base station energy storage can be regulated according to the city power supply state, the base station load state and the energy storage charge and discharge times; then determines the dispatchable capacity that these base station energy storage participating in the coordinated interaction of the power grid can provide to the power grid according to the base station communication load; finally, the variance of the minimized load curve is used as the optimization objective function to establish a 5G base station energy storage participating in the peak shaving and valley filling model of the power grid, and formulates a 5G base station energy storage control strategy based on the optimization results to control the base station energy storage participating in the coordinated interaction of the power grid. This method can smooth out power grid power fluctuations, reduce peak-to-valley differences, and delay the upgrade of power grid facilities; the base station energy storage participating in the peak shaving and valley filling of the power grid can also use peak-to-valley arbitrage to reduce the operator's electricity costs, without affecting the base station communication service quality and 5G user experience. The premise achieves mutual benefit and win-win results between the power grid and the communication operator.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy storage charging and discharging control, and in particular relates to a 5G base station energy storage control method taking into account the communication load state of the base station. Background Art

[0002] In the past two years, my country has clearly proposed on many occasions to accelerate the development of "new infrastructure". As a representative of new infrastructure, the construction of 5G base stations is steadily advancing. The 5G communication frequency band is higher. Under the same power, the transmission distance decreases, and the coverage range of a single 5G base station is smaller than that of a 4G base station. At the same time, because 5G uses a larger array antenna and higher bandwidth, the energy consumption of the base station is significantly higher than that of the original 3G and 4G base stations. In the 5G era, due to the significant increase in power consumption, operators will face very large pressure on electricity bills. Major operators are actively exploring models and methods to reduce operating costs in response to the country's requirements for reducing tariffs. 5G base stations usually configure energy storage as a backup power supply to ensure the uninterrupted power supply needs of the base station. According to the Ministry of Industry and Information Technology, the demand for backup batteries for 5G base stations will reach 31.8Gwh in 2023, which is a very large adjustable energy storage resource. As my country's distribution network becomes stronger and more reliable, the probability of power outages in the city is getting lower and lower, and the power outage time is getting shorter and shorter. When the power system is powered normally, the battery energy storage inside the communication base station has been idle, resulting in a waste of resources.

[0003] In view of the above situation of 5G base stations, the technologies studied at home and abroad for energy saving and consumption reduction of 5G base stations include:

[0004] Technology 1: 5G base station energy-saving technology

[0005] At present, the research on energy saving and consumption reduction of 5G base stations at home and abroad focuses on base station dormancy technology. Foreign researchers have long proposed that the energy consumption of base stations can be reduced by dormancy. By proposing a 5G base station dormancy technology model, different power consumption values ​​are given for different types of base stations, and the power consumption values ​​of base stations are analyzed through the composition of various components of the base station. Generally speaking, whether a base station is active or idle depends on whether the base station is currently transmitting. In addition, the base station can also be in different modes, including active mode, dormant mode, and off mode. At the same time, the communication load state of the base station will also affect the power consumption of the base station. Some literature suggests that using base station dormancy under low load conditions can effectively reduce system power consumption. Therefore, the research on 5G base station energy-saving technology is intended to reduce the energy consumption of base stations from the source, thereby achieving the purpose of saving electricity bills and reducing the operating costs of operators. However, this method is often accompanied by disadvantages such as impaired communication service quality of operators and reduced user experience of 5G communication.

[0006] Technology 2: Power system energy storage control technology

[0007] On the power generation side, the energy storage system can cooperate with the output of conventional steam turbine units to play a role in frequency regulation and voltage regulation. In addition, the energy storage system can also cooperate with wind and solar automatic power generation control systems to improve the regulation capacity of the power system and reduce wind and solar abandonment. On the transmission side, the energy storage system can assist the grid frequency regulation, improve the network's power flow distribution and grid stability. On the distribution side, the energy storage system is usually used to store energy during low load periods and generate electricity during peak load periods, smooth the load curve, delay equipment expansion, and improve the economic efficiency of grid operation. On the user side, energy storage currently has limited profit margins as a means of demand response. For users who adopt a two-part electricity price, it is possible to achieve a break-even by reducing the basic electricity fee through the energy storage system, and then profiting from the peak-to-valley difference and optimizing the user's own operation. However, with the gradual advancement of 5G base station construction, base station energy storage has become an adjustable energy storage resource that cannot be ignored. As a new energy storage configuration subject, 5G base stations participate in the coordinated dispatching with the distribution network, which can achieve mutual benefit and win-win results for the power grid and communication operators. At present, there is no research on the participation of 5G base station energy storage in grid coordinated dispatching. In addition, due to the communication service characteristics of 5G base stations themselves, the research results of other forms of energy storage regulation cannot be fully adapted to 5G base station energy storage regulation.

[0008] First, due to the high energy consumption and large electricity consumption of 5G base stations, it is necessary to explore new ideas and methods to reduce operators' electricity bills. Research on the participation of 5G base station energy storage in the coordinated dispatching of the power grid can use the low storage and high generation of energy storage to achieve peak-valley arbitrage, thereby achieving the purpose of reducing operators' electricity bills without affecting the quality of communication services and user experience. Secondly, with the improvement of the reliability of the distribution network, the probability of power outages in the city is getting lower and lower, and the power outage time is getting shorter and shorter. When the power system is supplying power normally, the battery energy storage inside the communication base station has been idle, resulting in a waste of resources. Research on the participation of 5G base station energy storage in the coordinated dispatching of the power grid can activate the idle base station energy storage resources and enable them to participate in the optimized operation of the power grid, so as to achieve the purpose of smoothing the power fluctuations of the power grid and reducing the peak-valley difference, and realize the mutual benefit and win-win situation between the power grid and the communication operators. Summary of the invention

[0009] The object of the present invention is to provide a 5G base station energy storage control method taking into account the communication load state of the base station, characterized in that the 5G base station energy storage control steps are as follows:

[0010] Step 1: Base station energy storage group identification

[0011] At present, four indicators have been selected for the identification of 5G base station energy storage groups, namely: city power supply status, base station load status, energy storage charge status and energy storage charge and discharge times status; according to various indicators, base station energy storage is divided into adjustable base station energy storage group and unadjustable base station energy storage group, and the adjustable base station energy storage group is further subdivided into adjustable charging energy storage group and adjustable discharging energy storage group;

[0012] Step 2: Calculation of dispatchable capacity of base station energy storage

[0013] When regulating the energy storage of base stations, its original purpose as a backup power source for base stations should be considered to determine its dispatchable capacity for participating in the coordinated interaction of power grids. The backup power demand of base stations is affected by the energy consumption of base stations. The greater the energy consumption, the greater the energy storage capacity required to meet the backup power demand. At the same time, the energy consumption of base stations is proportional to the communication traffic load state of the base stations. Therefore, the heavier the communication load state of the base station, the smaller the dispatchable capacity of its energy storage.

[0014] Step 3: Establishment of 5G base station energy storage peak-shaving and valley-filling model under base station communication load status

[0015] According to the adjustable capacity of base station energy storage, the variance of the load curve is minimized as the optimization objective function to establish a model for 5G base station energy storage to participate in power grid peak shaving and valley filling. The energy consumption state of the base station should be used as a constraint, including: considering the charging and discharging state constraints of the base station energy storage, calculating the charging and discharging power constraints and the power grid constraints based on the dispatchable capacity of the energy storage. The solution is optimized using an intelligent algorithm, and a control strategy for the base station energy storage to participate in power grid peak shaving and valley filling is formulated based on the solution results.

[0016] The basis for determining the energy storage groups of 5G base stations in step 1 is as follows:

[0017] 1) Mains power supply status: The regulation of 5G base station energy storage in the above research is based on the condition that the energy storage is idle. If the mains power fails, the base station energy storage must fulfill its original function of backup power; therefore, the mains power supply status is the first state quantity to be considered;

[0018] 2) Base station load status: Different base stations have different traffic loads at different times. Zero load, light load, and heavy load labels can be added to them according to the different traffic load levels of the base stations. For heavy-load base stations with excessively high traffic loads, the demand for backup power reliability of base station energy storage will also increase because they carry a large number of users and many services. Therefore, it is considered not to regulate the energy storage of heavy-load base stations, so that they can focus on backup power.

[0019] 3) Energy storage charge state: According to the different energy storage charge states, it is decided whether to be included in the charging energy storage group or the discharging energy storage group, and the charge and discharge depth of the energy storage can be limited by setting a certain charge state limit value;

[0020] 4) Energy storage charge and discharge times: The energy storage charge and discharge times are directly related to the life of the energy storage system. Therefore, a limit on the charge and discharge times is set to avoid the problem of energy storage service life being reduced due to frequent charging and discharging under grid regulation. For base station energy storage whose energy storage charge and discharge times reach the upper limit, no further regulation will be considered.

[0021] The method for dividing the base station communication load state in step 2 is specifically as follows:

[0022] Assume the base station communication load status indicator:

[0023] Where L represents the current load of the base station, L all Indicates the maximum load that the base station can bear, the base station load status indicator λ load It is defined as the ratio of the current load of the base station to the maximum load of the base station, which reflects the current load level of the base station. Since overload is not allowed when users access the base station, load ∈[0,1]. According to λ load The size of the base station load state is divided into the following categories: zero load state, λ load =0; normal state, λ load ∈(0,0.8]; heavy load state, λ load ∈(0.8,1];

[0024] The specific method for calculating the dispatchable capacity of base station energy storage participating in the grid coordination interaction in step 2 is:

[0025] Let S min and S max They are the upper and lower limits of energy storage charging and discharging SOC set considering the load status of the base station.

[0026]

[0027] The above formula relates the lower limit of the discharge SOC of the base station energy storage to the base station load state. When the base station load state indicator λ load When the value increases, the lower limit of the discharge SOC of the energy storage min As it increases, the energy storage stops discharging when it reaches the restricted SOC value, thereby maximizing the backup power reliability of the energy storage.

[0028] The upper limit constraint of base station energy storage charging is not as strict as the lower limit constraint of discharging. max The default setting is S max =S up .

[0029] Taking into account the two constraints of energy storage SOC, the upper and lower limits of the final charge and discharge SOC of base station i are obtained:

[0030] S i,min =max{S down ,S min}

[0031] S i,max =S max =S up

[0032] According to the real-time SOC status of the energy storage at base station i and the upper and lower limits of the charge and discharge SOC, the upward chargeable capacity and downward dischargeable capacity of the energy storage can be calculated:

[0033]

[0034]

[0035] in, and are the upward charge capacity and downward discharge capacity, S i (t) is the SOC value of the energy storage of base station i at time t, S i,max and S i,min are the upper and lower limits of the energy storage charging and discharging SOC of base station i, and E is the rated capacity of the energy storage.

[0036] According to the rechargeable capacity and dischargeable capacity of energy storage, the maximum charging power and maximum discharging power of energy storage of base station i within a scheduling time interval Δt can be calculated:

[0037]

[0038]

[0039] in, is the maximum charging power of the energy storage of base station i, It is the maximum charging power limit of the energy storage battery.

[0040] Assuming that the number of base stations in the charging base station energy storage group is M, the maximum charging power of the charging energy storage group at time t is:

[0041]

[0042] Similarly, when the energy storage is discharged:

[0043]

[0044] in, is the maximum discharge power of the energy storage of base station i, It is the maximum discharge power limit of the energy storage battery.

[0045] Assuming that the number of base stations in the charging base station energy storage group is N, the maximum discharge power of the discharge energy storage group at time t is:

[0046]

[0047] The 5G base station energy storage peak-shaving and valley-filling model taking into account the base station communication load state in step 3 is specifically:

[0048] (1) Objective function

[0049] Use minimizing the variance of the load curve as the optimization objective function:

[0050]

[0051] Where D(t) is the load demand of the power grid at time t, P ch (t), P diss (t) is the total charging and discharging power of the 5G base station energy storage at time t, and P ch (t) = ∑P i,ch (t), P diss (t) = ∑P i,diss (t).

[0052] (2) Constraints

[0053] Charge and discharge state constraints:

[0054]

[0055] Among them, β ch , β diss is the energy storage charging and discharging state variable.

[0056] Charge and discharge equation constraints:

[0057]

[0058] Among them, E i,t is the energy storage capacity at time t, η ch is the energy storage charging coefficient, η diss is the energy storage discharge coefficient, and E is the rated capacity of the energy storage.

[0059] Charge and discharge power constraints:

[0060]

[0061] Among them, P i,ch (t) is the charging power of energy storage i at time t, P i,diss (t) is the discharge power of energy storage i at time t.

[0062] Grid power constraints:

[0063]

[0064] in, They are respectively the upper and lower limits of the transmission power allowed by the current regional power grid.

[0065] The beneficial effects of the present invention are:

[0066] The present invention first analyzes the energy storage status of the 5G base station to determine whether the base station energy storage is regulated, and formulates a 5G base station energy storage regulation strategy based on the optimization results to control the base station energy storage to participate in the coordinated interaction of the power grid; it has the following characteristics:

[0067] 1) Base station energy storage grouping identification method, based on the city power supply status, base station load status and energy storage charge and discharge times status, to determine whether the base station can be included in the adjustable base station energy storage group to participate in the grid coordination interaction. This grouping identification method can reduce the impact of base station energy storage on its backup power function due to participation in grid coordination interaction, and by controlling the charge and discharge times of energy storage within a fixed time, it can avoid excessive loss of energy storage life.

[0068] 2) The calculation method of the dispatchable capacity of base station energy storage is to determine the dispatchable capacity of the base station energy storage participating in the coordinated interaction of the power grid according to the communication load status of the base station. The heavier the communication load of the base station, the smaller the dispatchable capacity of the energy storage. This ensures that if the external power supply is suddenly cut off, the base station energy storage still has more energy storage capacity to meet the backup power demand of the base station, waiting for the power supply to be restored or the load to be transferred.

[0069] 3) The 5G base station energy storage peak-shaving and valley-filling model that takes into account the base station communication load status can enrich the grid's controllable distributed energy storage resources, smooth out grid power fluctuations, reduce peak-to-valley differences, and delay grid facility upgrades. For operators, base station energy storage participating in grid peak-shaving and valley-filling can also use peak-to-valley arbitrage to reduce operators' electricity costs, thereby achieving mutual benefit and win-win results for the grid and communication operators without affecting the base station communication service quality and 5G user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is a flow chart for identifying energy storage groups for 5G base stations. DETAILED DESCRIPTION

[0071] The present invention provides a 5G base station energy storage control method taking into account the communication load state of the base station, and the present invention is described below with reference to the accompanying drawings.

[0072] Step 1: Base station energy storage group identification

[0073] First, we need to determine which base station energy storage can be regulated and which cannot be regulated, as well as which energy storage is suitable for charging and which is suitable for discharging. Currently, four indicators for 5G base station energy storage grouping are selected, which are:

[0074] 1) Mains power supply status: This is the first state quantity that needs to be considered. The regulation of 5G base station energy storage that we studied is based on the condition that the energy storage is idle. If the mains power fails, the base station energy storage must fulfill its original purpose of backup power.

[0075] 2) Base station load status: Different base stations have different traffic loads at different times. We can add zero load, light load, and heavy load labels to them according to the different traffic load levels of the base stations. For heavy-load base stations with excessive traffic loads, because they carry a large number of users and many services, the demand for backup power reliability of base station energy storage will also increase. We consider not regulating the energy storage of heavy-load base stations, so that they can focus on backup power.

[0076] 3) Energy storage charge state: The energy storage is divided into a charging energy storage group or a discharging energy storage group according to its charge state, and the charge and discharge depth of the energy storage can be limited by setting a certain charge state limit value.

[0077] 4) Energy storage charge and discharge times: The energy storage charge and discharge times are directly related to the life of the energy storage system. Setting a limit on the charge and discharge times can avoid the problem of energy storage's service life being reduced due to frequent charge and discharge under grid regulation. For base station energy storage whose energy storage charge and discharge times have reached the upper limit, no further regulation will be considered.

[0078] According to various indicators, the base station energy storage is divided into adjustable base station energy storage group and unadjustable base station energy storage group, and the adjustable base station energy storage group is further divided into adjustable charging energy storage group and adjustable discharging energy storage group; the specific grouping process is as follows: Figure 1 .

[0079] Step 2: Calculation of dispatchable capacity of base station energy storage

[0080] After determining which base station energy storage can participate in the grid optimization operation, it is also necessary to determine how much dispatchable capacity these base station energy storage participating in the grid coordination interaction can provide to the grid; when regulating the base station energy storage, its original intention as a backup power supply for the base station should be considered to determine its dispatchable capacity for participating in the grid coordination interaction. The backup power demand of the base station is affected by the energy consumption of the base station. The greater the energy consumption, the greater the energy storage capacity required to meet the backup power demand; at the same time, the energy consumption of the base station is proportional to the communication traffic load state of the base station. Therefore, the heavier the communication load state of the base station, the smaller the dispatchable capacity of its energy storage; the most important function of 5G base station energy storage is to serve as a backup power supply to ensure the uninterrupted power supply needs of the base station. Therefore, the formulation of the 5G base station energy storage charging and discharging plan needs to be based on the urgency of the base station's demand for backup power, and to minimize the impact of sudden outages of external city power on users connected to the base station.

[0081] The communication traffic load state of the base station (base station load) indicates the amount of business currently undertaken by the base station. The base station load state indicator is:

[0082]

[0083] Where L represents the current load of the base station, L allIndicates the maximum load that the base station can bear, the base station load status indicator λ load It is defined as the ratio of the current load of the base station to the maximum load of the base station, which reflects the current load level of the base station. Since overload is not allowed when users access the base station, load ∈[0,1]. According to λ load The base station load status is divided into the following categories according to the size of

[0084] Base station status Base station load status indicators Zero load state <![CDATA[λ load =0]]> Normal state <![CDATA[λ load ∈(0,0.8]]]> Heavy load status <![CDATA[λ load ∈(0.8,1]]]>

[0085] The load state of a base station directly affects the urgency of its demand for backup power. For base stations in a heavy load state, the number of users connected to the base station is large, and the business volume is large. The capacity stability and reliability of the backup power supply are very high. The participation of energy storage regulation in grid interaction will affect its reliability as a backup power supply. Therefore, this article does not consider regulating the energy storage of base stations in a heavy load state. For base stations in a zero load state and a normal state, the urgency of their demand for backup power is relatively low. With the improvement of the reliability of external mains power supply, in order to avoid the waste of resources caused by the long-term idleness of base station energy storage when the mains power supply is normal, it is considered to reasonably regulate the energy storage of such base stations to improve resource utilization.

[0086] In order to improve the rationality of base station energy storage regulation, it is considered to associate the adjustable capacity of base station energy storage with the base station load state by limiting the SOC range of base station energy storage action, so as to minimize the impact of energy storage regulation on the backup power function.

[0087] Let S min and S max They are the upper and lower limits of energy storage charging and discharging SOC set considering the load status of the base station.

[0088]

[0089] The above formula relates the lower limit of the discharge SOC of the base station energy storage to the base station load state. When the base station load state indicator λ load When the value increases, the lower limit of the discharge SOC of the energy storage min As it increases, the energy storage stops discharging when it reaches the restricted SOC value, thereby maximizing the backup power reliability of the energy storage.

[0090] The upper limit constraint on the charging of base station energy storage is not as strict as the lower limit constraint on the discharge, because the sufficient capacity of the base station energy storage is conducive to ensuring the backup power of the base station, so S max The default setting is S max =S up .

[0091] Taking into account the two constraints of energy storage SOC, the upper and lower limits of the final charge and discharge SOC of base station i are obtained:

[0092] S i,min =max{S down ,S min}

[0093] S i,max =S max =S up

[0094] According to the real-time SOC status of the energy storage at base station i and the upper and lower limits of the charge and discharge SOC, the upward chargeable capacity and downward dischargeable capacity of the energy storage can be calculated:

[0095]

[0096]

[0097] in, and are the upward charge capacity and downward discharge capacity, S i (t) is the SOC value of the energy storage of base station i at time t, S i,max and S i,min are the upper and lower limits of the energy storage charging and discharging SOC of base station i, and E is the rated capacity of the energy storage.

[0098] According to the rechargeable capacity and dischargeable capacity of energy storage, the maximum charging power and maximum discharging power of energy storage of base station i within a scheduling time interval Δt can be calculated:

[0099]

[0100]

[0101] in, is the maximum charging power of the energy storage of base station i, It is the maximum charging power limit of the energy storage battery.

[0102] Assuming that the number of base stations in the charging base station energy storage group is M, the maximum charging power of the charging energy storage group at time t is:

[0103]

[0104] Similarly, when the energy storage is discharged:

[0105]

[0106] in, is the maximum discharge power of the energy storage of base station i, It is the maximum discharge power limit of the energy storage battery.

[0107] Assuming that the number of base stations in the charging base station energy storage group is N, the maximum discharge power of the discharge energy storage group at time t is:

[0108]

[0109] Step 3: Establishment of 5G base station energy storage peak-shaving and valley-filling model under base station communication load status

[0110] According to the adjustable capacity of base station energy storage, the variance of the load curve is minimized as the optimization objective function to establish a model for 5G base station energy storage to participate in the peak shaving and valley filling of the power grid. The constraints include: the charging and discharging state constraints of the base station energy storage, the charging and discharging power constraints calculated based on the dispatchable capacity of the energy storage, and the power constraints of the power grid. The intelligent algorithm is used to optimize the solution, and a control strategy for the base station energy storage to participate in the peak shaving and valley filling of the power grid is formulated based on the solution results. The specific model is as follows:

[0111] (1) Energy storage control objective function

[0112] Use minimizing the variance of the load curve as the optimization objective function:

[0113]

[0114] Where D(t) is the load demand of the power grid at time t, which can be obtained from the regional daily load curve; P ch (t), P diss (t) is the total charging and discharging power of the 5G base station energy storage at time t, and P ch (t) = ∑P i,ch (t), P diss (t) = ∑P i,diss (t).

[0115] (2) Energy storage regulation constraints

[0116] 1) Constraints on charging and discharging status of base station energy storage

[0117]

[0118] Among them, β ch , β diss is the energy storage charging and discharging state variable.

[0119] 2) Constraints on the charging and discharging equations of energy storage

[0120]

[0121] Among them, E i,t is the energy storage capacity of base station i at time t, η ch is the energy storage charging coefficient, η diss is the energy storage discharge coefficient, E is the energy storage rated capacity;

[0122] 3) Constraints on charging and discharging power of energy storage

[0123]

[0124] Among them, P i,ch (t) is the charging power of the energy storage of base station i at time t, P i,diss (t) is the discharge power of the energy storage of base station i at time t;

[0125] 4) Grid power constraints

[0126]

[0127] in, They are respectively the upper and lower limits of the transmission power allowed by the current regional power grid.

[0128] According to the objective function and constraints, the genetic algorithm is used to solve the charging and discharging power of the 5G base station energy storage in each optimization period, and a 5G base station energy storage control strategy is formulated based on the optimization results to control the base station energy storage to participate in the coordinated interaction of the power grid.

Claims

1. A 5G base station energy storage control method taking into account the base station communication load state, characterized in that: The 5G base station energy storage control steps are as follows: Step 1: Base station energy storage group identification At present, four indicators have been selected for the identification of 5G base station energy storage groups, namely: city power supply status, base station load status, energy storage charge status and energy storage charge and discharge times status; according to various indicators, base station energy storage is divided into adjustable base station energy storage group and unadjustable base station energy storage group, and the adjustable base station energy storage group is further subdivided into adjustable charging energy storage group and adjustable discharging energy storage group; Step 2: Calculation of dispatchable capacity of base station energy storage When regulating the energy storage of base stations, its original purpose as a backup power source for base stations should be considered to determine its dispatchable capacity for participating in the coordinated interaction of power grids. The backup power demand of base stations is affected by the energy consumption of base stations. The greater the energy consumption, the greater the energy storage capacity required to meet the backup power demand. At the same time, the energy consumption of base stations is proportional to the communication traffic load state of the base stations. Therefore, the heavier the communication load state of the base station, the smaller the dispatchable capacity of its energy storage. Step 3: Establish a 5G base station energy storage peak-shaving and valley-filling model taking into account the base station communication load status According to the adjustable capacity of base station energy storage, the variance of the load curve is minimized as the optimization objective function to establish a model for 5G base station energy storage to participate in power grid peak shaving and valley filling. The constraints include: the charging and discharging state constraints of the base station energy storage, the charging and discharging power constraints calculated based on the dispatchable capacity of the energy storage, and the power constraints of the power grid. The solution is optimized using an intelligent algorithm, and a control strategy for base station energy storage to participate in power grid peak shaving and valley filling is formulated based on the solution results.

2. The 5G base station energy storage control method taking into account the base station communication load state according to claim 1 is characterized in that: The basis for distinguishing the 5G base station energy storage groups in step 1 is: 1) Mains power supply status: The research on the regulation of 5G base station energy storage is based on the idle condition of energy storage. If the mains power fails, the base station energy storage must fulfill its original function of backup power. Therefore, the mains power supply status is the first state quantity to be considered. 2) Base station load status: Different base stations have different traffic loads at different times. Zero load, light load, and heavy load labels can be added to them according to the different traffic load levels of the base stations. For heavy-load base stations with excessively high traffic loads, the demand for backup power reliability of base station energy storage will also increase because they carry a large number of users and many services. Therefore, it is considered not to regulate the energy storage of heavy-load base stations, so that they can focus on backup power. 3) Energy storage charge state: According to the different energy storage charge states, it is decided whether to be included in the charging energy storage group or the discharging energy storage group, and the charge and discharge depth of the energy storage can be limited by setting a certain charge state limit value; 4) Energy storage charge and discharge times: The energy storage charge and discharge times are directly related to the life of the energy storage system. Therefore, a limit on the charge and discharge times is set to avoid the problem of energy storage service life being reduced due to frequent charging and discharging under grid regulation. For base station energy storage whose energy storage charge and discharge times reach the upper limit, no further regulation will be considered.

3. The 5G base station energy storage control method taking into account the base station communication load state according to claim 1 is characterized in that: The method for dividing the base station communication load state in step 2 is specifically as follows: Assume the base station communication load status indicator: Where L represents the current load of the base station, L all Indicates the maximum load that the base station can bear, the base station load status indicator λ load It is defined as the ratio of the current load of the base station to the maximum load of the base station, which reflects the current load level of the base station. Since overload is not allowed when users access the base station, load ∈[0,1]; according to λ load The size of the base station load state is divided into the following categories: zero load state, λ load =0; normal state, λ load ∈(0,0.8]; heavy load state, λ load ∈(0.8,1].

4. The 5G base station energy storage control method taking into account the base station communication load state according to claim 1 is characterized in that: The specific method for calculating the dispatchable capacity of base station energy storage participating in the grid coordination interaction in step 2 is: Let S min and S max They are the upper and lower limits of energy storage charging and discharging SOC set considering the load state of the base station, where: The above formula relates the lower limit of the discharge SOC of the base station energy storage to the base station load state. When the base station load state indicator λ load When the value increases, the lower limit of the discharge SOC of the energy storage min As the SOC increases, the energy storage stops discharging when it reaches the restricted SOC value, thus improving the backup power reliability of the energy storage as much as possible; The upper limit constraint of base station energy storage charging is not as strict as the lower limit constraint of discharging. max The default setting is S max =S up .

5. The 5G base station energy storage control method taking into account the base station communication load state according to claim 4 is characterized in that: Taking into account the two constraints of energy storage SOC, the upper and lower limits of the final charge and discharge SOC of base station i are obtained: S i,min =max{S down ,S min } S i,max =S max =S up According to the real-time SOC status of the energy storage at base station i and the upper and lower limits of the charge and discharge SOC, the upward chargeable capacity and downward dischargeable capacity of the energy storage can be calculated: in, and are the upward charge capacity and downward discharge capacity, S i (t) is the SOC value of the energy storage of base station i at time t, S i,max and S i,min are the upper and lower limits of the energy storage charging and discharging SOC of base station i, and E is the rated capacity of the energy storage; According to the rechargeable capacity and dischargeable capacity of energy storage, the maximum charging power and maximum discharging power of energy storage of base station i within a scheduling time interval Δt can be calculated: in, is the maximum charging power of the energy storage of base station i, It is the maximum charging power limit of the energy storage battery.

6. The 5G base station energy storage control method taking into account the base station communication load state according to claim 5 is characterized in that: Assuming that the number of base stations in the charging base station energy storage group is M, the maximum charging power of the charging energy storage group at time t is: Similarly, when the energy storage is discharged: in, is the maximum discharge power of the energy storage of base station i, is the maximum discharge power limit of the energy storage battery; Assuming that the number of base stations in the charging base station energy storage group is N, the maximum discharge power of the discharge energy storage group at time t is:

7. The 5G base station energy storage control method taking into account the base station communication load state according to claim 1 is characterized in that: The 5G base station energy storage peak-shaving and valley-filling model taking into account the base station communication load state in step 3 is specifically: (1) Objective function Use minimizing the variance of the load curve as the optimization objective function: Where D(t) is the load demand of the power grid at time t, P ch (t), P diss (t) is the total charging and discharging power of the 5G base station energy storage at time t, and P ch (t)=ΣP i,ch (t), P diss (t)=ΣP i,diss (t); (2) Constraints Charge and discharge state constraints: Among them, β ch , β diss is the energy storage charging and discharging state variable; Charge and discharge equation constraints: Among them, E i,t is the energy storage capacity of base station i at time t, η ch is the energy storage charging coefficient, η diss is the energy storage discharge coefficient, E is the energy storage rated capacity; Charge and discharge power constraints: Among them, P i,ch (t) is the charging power of the energy storage of base station i at time t, P i,diss (t) is the discharge power of the energy storage of base station i at time t; Grid power constraints: in, They are respectively the upper and lower limits of the transmission power allowed by the current regional power grid.

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