Communication base station energy storage scheduling method and device based on quantitative evaluation of backup demand

Abstract

The present invention relates to the technical field of power distribution and utilization optimization scheduling, and specifically to a communication base station energy storage scheduling method and device based on quantitative evaluation of backup demand. The method first establishes a quantitative calculation model for the power supply availability of the communication base station; based on the model, the backup demand of the energy storage battery under the condition of reliable power supply of the communication base station in each period is estimated; then, a day-ahead scheduling model for the energy storage battery is established, and the model is solved to obtain the day-ahead scheduling strategy for the energy storage battery. The present invention can realize the day-ahead scheduling of the energy storage battery of the communication base station, and on the premise of meeting the power supply reliability requirements of the communication base station, by optimizing the operation strategy of the energy storage battery, participate in the interactive regulation of supply and demand of the power system, and reduce the operating cost of the communication base station while serving the power system to ensure power supply and promote the consumption of new energy.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution optimization scheduling, and in particular to a communication base station energy storage scheduling method and device based on quantitative evaluation of standby demand. Background Art

[0002] Wireless communication networks are an important infrastructure of contemporary human society. With the continuous improvement of the information level of modern society, wireless communication technology is increasingly playing an increasingly important role in people's daily production and life. The emergence of the fifth generation of mobile communication technology (5G communication) has far higher performance than 4G communication in terms of transmission rate, delay and other indicators, and has achieved rapid development.

[0003] In order to achieve wireless communication network coverage, a large number of communication base stations are currently being built. The equipment in the communication base station can be divided into two categories, one is the communication equipment and the other is the power supply equipment. The communication equipment realizes wireless network communication, and the power supply equipment provides a reliable power supply for the communication equipment. The power supply equipment includes power supply equipment for converting AC to DC and energy storage batteries for emergency backup. When the power supply network fails, the communication equipment of the communication base station is powered by the energy storage battery to ensure the reliability of the communication of the communication base station.

[0004] In communication base stations, the power consumption of communication equipment is positively correlated with the communication load. It has greater power consumption when the communication load is large and less power consumption when the communication load is small. In order to achieve the same communication reliability during busy communication periods and idle communication periods, different battery backup requirements are required. While ensuring that the communication reliability meets the index requirements, the surplus communication base station energy storage battery capacity is applied to the day-ahead scheduling, and the peak-valley electricity price difference of the distribution network can be used to achieve arbitrage and reduce the total electricity purchase cost of the base station; by optimizing the energy storage battery operation strategy and participating in the interactive scheduling of supply and demand of the power system, while reducing the operating costs of communication base stations, it serves the power system to ensure power supply and promote the consumption of new energy.

[0005] However, different communication base stations are located in different locations in the distribution network, have different power load curves, and have different requirements for energy storage battery backup capacity, which leads to the risk of being too radical or conservative in existing scheduling methods and devices. It is necessary to realize the day-ahead scheduling of communication base station energy storage batteries based on the quantitative evaluation of energy storage battery backup demand. Summary of the invention

[0006] In order to solve the above technical problems, the purpose of the present invention is to provide a communication base station energy storage scheduling method and device based on quantitative evaluation of backup demand. The technical solutions adopted are as follows:

[0007] Establish a power supply availability calculation model for communication base stations;

[0008] Quantitatively evaluate the backup demand for energy storage batteries in each period;

[0009] A communication base station energy storage battery day-ahead scheduling model considering backup demand is established, wherein the communication base station energy storage battery day-ahead scheduling model consists of two parts: an objective function and constraint conditions;

[0010] The communication base station energy storage battery day-ahead scheduling model is solved by using an optimization solver to obtain an optimal strategy for charging and discharging the communication base station energy storage battery; and the optimal strategy is sent to an energy storage battery energy management module of the communication base station.

[0011] Preferably, the establishing of a power supply availability calculation model for a communication base station includes:

[0012] Obtaining information of all lines on the power supply path from the distribution transformer to the communication base station from the distribution network; wherein the line information includes: the failure rate and repair rate of the line;

[0013] Constructing a random process that characterizes the power supply status of a communication base station;

[0014] Establish the state transition density matrix corresponding to the random process;

[0015] Dividing the state transfer density matrix into blocks;

[0016] According to the divided state transfer density matrix, a power supply availability calculation model for communication base stations is established.

[0017] Preferably, the establishment of a power supply availability calculation model for a communication base station according to the divided state transfer density matrix includes:

[0018] The power supply availability calculation model is:

[0019] ;

[0020] in, is the power supply availability; p is the size of 1×2 with the first element being 1 and the rest being 0 M vector; T is an integer greater than 100000; I is a vector with a scale of (2 M -1)×(2 M -1) unit matrix; D is the backup time of the communication base station energy storage battery; e is a natural constant; A is the state transfer density matrix; The scale is (2 M -1) × 1 block matrix of the state transition density matrix; For a scale of 1×(2 M -1) the block matrix of the state transition density matrix; The scale is (2 M -1)×(2 M-1) is a block matrix of the state transition density matrix; M is the number of all lines on the power supply path from the distribution transformer to the communication base station obtained from the distribution network.

[0021] Preferably, the quantitative evaluation of the backup demand of the energy storage battery in each time period includes:

[0022] Quantitatively evaluate the minimum energy storage backup time required for communication base stations to meet availability requirements;

[0023] In combination with the minimum energy storage backup time, a communication base station energy storage battery backup demand model for each time period is established.

[0024] Preferably, the quantitative evaluation of the minimum energy storage backup time for the communication base station to meet the availability requirement includes:

[0025] The power supply availability formula of the communication base station is expressed as a function of the energy storage backup time: ,set up , given the initial backup time ;

[0026] Calculate the backup time as Power supply availability of communication base stations under ;

[0027] Calculate the update amount of backup time, the formula is as follows:

[0028] ;

[0029] in, The power supply availability that meets the availability requirements for communication base stations, For function The derivative of

[0030] if ,but , k=k+1, return and calculate the backup time again Power supply availability of communication base stations under ; Otherwise, output the minimum energy storage backup time .

[0031] Preferably, the minimum energy storage backup time is combined to establish a communication base station energy storage battery backup demand model for each time period, including:

[0032] Establish the backup requirements of energy storage batteries for communication base stations in each period Calculation method:

[0033] ;

[0034] in, Indicates the time period number. The communication base station is in the time period The communication power consumption, Indicates rounding down.

[0035] Preferably, the step of establishing a communication base station energy storage battery day-ahead scheduling model taking into account backup demand includes:

[0036] Based on the daily power data of the communication base station, the objective function of the day-ahead dispatch model of the energy storage battery of the communication base station is constructed;

[0037] According to the charging and discharging power, charging and discharging efficiency, rated capacity of the energy storage battery and the rated power of the communication base station, the constraint conditions of the day-ahead scheduling model of the communication base station energy storage battery are constructed; wherein the constraint conditions include: energy balance constraint, safety constraint and backup demand constraint.

[0038] Preferably, the objective function of the day-ahead scheduling model of the energy storage battery of the communication base station is constructed according to the single-day power data of the communication base station, including:

[0039] ;

[0040] in, is the total daily operation cost of the base station; T is the total number of time slots in a single day; is the electricity price in time period t; is the purchased power in period t; where, Electricity price information is obtained from the power system.

[0041] Preferably, the constraint conditions of the day-ahead scheduling model of the energy storage battery of the communication base station are constructed according to the charge and discharge power, charge and discharge efficiency, rated capacity of the energy storage battery and the rated power of the communication base station, including:

[0042] Energy balance constraints:

[0043] ;

[0044] ;

[0045] in, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the state of charge of the energy storage battery, is the charging efficiency, is the discharge efficiency, The communication base station is in the time period Communication power consumption;

[0046] Safe operation constraints:

[0047]

[0048]

[0049]

[0050] in, is the rated capacity of the energy storage battery; The communication base station is in the time period Communication power consumption; is the rated power of the communication base station power supply, Is a 0-1 variable, when the energy storage battery is charged , when the energy storage battery is discharged ;

[0051] Alternative demand constraints:

[0052] ;

[0053] in, Energy storage battery backup requirements for communication base stations in each time period.

[0054] A communication base station energy storage dispatching device based on quantitative evaluation of standby demand, the device comprising the following modules: an energy storage battery energy management module, an energy storage battery day-ahead dispatching decision module, a power system information reading module and a communication base station communication power consumption reading module;

[0055] The output ends of the power system information reading module and the communication base station communication power consumption reading module are respectively connected to the input end of the energy storage battery day-ahead scheduling decision module; the output end of the energy storage battery day-ahead scheduling decision module is connected to the energy storage battery energy management module; the power system information reading module is used to read the distribution network parameter information and the power system electricity price information and send them to the energy storage battery day-ahead scheduling decision module; the communication base station communication power consumption reading module is used to read the communication power consumption information of the communication base station and send it to the energy storage battery day-ahead scheduling decision module;

[0056] The energy storage battery day-ahead scheduling decision module is used to receive power system information and communication power consumption information of the communication base station; establish a power supply availability calculation model for the communication base station, quantitatively evaluate the backup demand of the energy storage battery in each time period, and establish a communication base station energy storage battery day-ahead scheduling model that takes into account the backup demand. The communication base station energy storage battery day-ahead scheduling model consists of two parts: an objective function and constraint conditions; and use an optimization solver to solve the communication base station energy storage battery day-ahead scheduling model to obtain the optimal strategy for charging and discharging the communication base station energy storage battery, and send the optimal strategy to the energy storage battery energy management module of the communication base station; the energy storage battery energy management module receives the optimal charging and discharging strategy of the energy storage battery day-ahead scheduling decision module, converts it into a charging and discharging control signal for the energy storage battery, and controls the energy storage battery to operate according to the optimal strategy.

[0057] The embodiments of the present invention have at least the following beneficial effects:

[0058] The present invention can realize the day-ahead scheduling of energy storage batteries for communication base stations. On the premise of meeting the power supply reliability requirements of the base stations, it can quantitatively evaluate the backup capacity requirements of the energy storage batteries in each time period, combine the power system electricity price information and interaction requirements, optimize the energy storage battery operation strategy, and reduce the base station operation cost.

[0059] The present invention can effectively reduce operating costs while taking into account the reliability of communication base stations, and participate in the supply guarantee and consumption interaction needs of the power system. The present invention has strong applicability and can be applied to communication base stations with different distribution points and different load characteristics in the distribution network; the optimization model established by the method of the present invention is a linear model, which can ensure the optimality of the operation strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A method flow chart of a communication base station energy storage scheduling method based on quantitative evaluation of standby demand provided by one embodiment of the present invention;

[0062] Figure 2 An overall flow chart of a communication base station energy storage scheduling method based on quantitative evaluation of standby demand provided by one embodiment of the present invention;

[0063] Figure 3 A schematic diagram of the structure of a communication base station energy storage scheduling device based on quantitative evaluation of backup demand provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the communication base station energy storage scheduling method and device based on the quantitative evaluation of backup demand proposed by the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0065] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0066] The embodiment of the present invention provides a specific implementation method of a communication base station energy storage scheduling method and device based on quantitative evaluation of backup demand, which is applicable to the communication base station energy storage battery scheduling scenario. In this scenario, in order to fill the gaps in the existing technology, a communication base station energy storage scheduling method and device based on quantitative evaluation of backup demand is proposed. The present invention can realize the day-ahead scheduling of communication base station energy storage batteries. On the premise of meeting the power supply reliability requirements of the communication base station, according to the backup demand of the energy storage battery in each period of the day, combined with the power system electricity price information and the supply and demand interaction requirements, the energy storage battery operation strategy is optimized, while reducing the operating costs of the communication base station, serving the power system to ensure power supply and promote the consumption of new energy.

[0067] The specific scheme of the communication base station energy storage scheduling method and device based on the quantitative evaluation of backup demand provided by the present invention is described in detail below with reference to the accompanying drawings.

[0068] Embodiment 1:

[0069] See also Figure 1 , which shows a flowchart of a communication base station energy storage scheduling method based on quantitative evaluation of standby demand provided by an embodiment of the present invention, the method comprising the following steps:

[0070] Step S100: establishing a power supply availability calculation model for a communication base station.

[0071] Step S110, obtaining information of all lines on the power supply path from the distribution transformer to the communication base station from the distribution network.

[0072] The line information includes: the failure rate and repair rate of the line; assuming that there are M lines in total, each line is numbered 1, 2, ..., m, ..., M. The information obtained is the failure rate of each line and repair rate .

[0073] Step S120: construct a random process X(t) that characterizes the power supply state of the communication base station.

[0074] X(t) is a random process with continuous time and discrete state space. The states in its state space have Each state in the state space is represented by a binary number of length M. The mth bit of the binary number represents whether the mth line is faulty, 0 represents a normal line, and 1 represents a line fault.

[0075] Step S130, establishing a state transition density matrix A corresponding to the random process X(t).

[0076] The state transition density matrix A is a matrix of size A square matrix where the off-diagonal elements are given as follows:

[0077] Case 1: If the binary numbers corresponding to state i and state j are the same except for the mth bit; and the mth bit of the binary number corresponding to state i is 0, and the mth bit of the binary number corresponding to state j is 1, then .

[0078] Case 2: If the binary numbers corresponding to state i and state j are the same except for the mth bit; and the mth bit of the binary number corresponding to state i is 1, and the mth bit of the binary number corresponding to state j is 0, then .

[0079] Case 3: If the binary numbers corresponding to state i and state j are different by two or more digits, then .

[0080] The diagonal elements of the state transition density matrix A are given as follows: .

[0081] Step S140, dividing the state transition density matrix into blocks.

[0082] The specific method is:

[0083] ;

[0084] in, is a block matrix of the state transition density matrix of size 1×1; The scale is (2 M -1) × 1 block matrix of the state transition density matrix; For a scale of 1×(2 M -1) the block matrix of the state transition density matrix; The scale is (2 M -1)×(2 M -1) is a block matrix of the state transition density matrix.

[0085] Step S150, establishing a power supply availability calculation model for the communication base station according to the divided state transition density matrix.

[0086] The power supply availability calculation model is:

[0087] ;

[0088] in, is the power supply availability; p is the size of 1×2 with the first element being 1 and the rest being 0 Mvector; T is an integer greater than 100000; I is a vector with a scale of (2 M -1)×(2 M -1) unit matrix; D is the backup time of the communication base station energy storage battery; e is a natural constant; A is the state transition density matrix; The scale is (2 M -1) × 1 block matrix of the state transition density matrix; For a scale of 1×(2 M -1) the block matrix of the state transition density matrix; The scale is (2 M -1)×(2 M -1) is a block matrix of the state transition density matrix; M is the number of all lines on the power supply path from the distribution transformer to the communication base station obtained from the distribution network.

[0089] Step S200, quantitatively evaluating the backup demand of the energy storage battery in each time period.

[0090] Step S210, quantitatively evaluating the minimum energy storage backup time for the communication base station to meet the availability requirement, the steps adopted are as follows:

[0091] Step S211, the power supply availability formula of the communication base station is expressed as a function of the energy storage backup time: ,set up , given the initial backup time .

[0092] Step S212, calculate the standby time as Power supply availability of communication base stations under .

[0093] Step S213, calculating the update amount of the standby time, the formula is as follows:

[0094] ;

[0095] in, The power supply availability that meets the availability requirements for communication base stations, For function The derivative function of .

[0096] Step S214, if ,but , k=k+1, return to step S212; otherwise, output the minimum energy storage backup time .

[0097] Step S220, combining the minimum energy storage backup time, establish a communication base station energy storage battery backup demand model for each time period.

[0098] Establish the backup requirements of energy storage batteries for communication base stations in each period Calculation method:

[0099] ;

[0100] in, Indicates the time period number. The communication base station is in the time period The communication power consumption, Indicates rounding down.

[0101] Step S300, establishing a communication base station energy storage battery day-ahead scheduling model that takes into account backup demand, wherein the communication base station energy storage battery day-ahead scheduling model consists of two parts: an objective function and constraint conditions.

[0102] Step S310, constructing the objective function of the day-ahead scheduling model of the energy storage battery of the communication base station according to the single-day power data of the communication base station.

[0103] The objective function of the day-ahead scheduling model for energy storage batteries in communication base stations is constructed as follows:

[0104] ;

[0105] in, is the total daily operation cost of the base station; T is the total number of time slots in a single day; is the electricity price in time period t; is the purchased power in period t. Among them, Electricity price information is obtained from the power system.

[0106] Step S320, constructing the constraint conditions of the day-ahead scheduling model of the energy storage battery of the communication base station according to the charge and discharge power, charge and discharge efficiency, rated capacity of the energy storage battery and the rated power of the communication base station; wherein the constraint conditions include: energy balance constraint, safety constraint and backup demand constraint.

[0107] (1) Energy balance constraints:

[0108] ;

[0109] ;

[0110] in, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the state of charge of the energy storage battery, is the charging efficiency, is the discharge efficiency.

[0111] (2) Safe operation constraints:

[0112]

[0113]

[0114]

[0115] in, is the rated capacity of the energy storage battery; The communication base station is in the time period Communication power consumption; is the rated power of the communication base station power supply, Is a 0-1 variable, when the energy storage battery is charged , when the energy storage battery is discharged .

[0116] (3) Reserve demand constraints:

[0117] ;

[0118] in, Energy storage battery backup requirements for communication base stations in each time period.

[0119] Step S400, using an optimization solver to solve the communication base station energy storage battery day-ahead scheduling model, obtain the optimal strategy for charging and discharging the communication base station energy storage battery; and send the optimal strategy to the energy storage battery energy management module of the communication base station to achieve day-ahead scheduling of the communication base station energy storage battery.

[0120] See also Figure 2 , Figure 2 The figure is an overall flow chart of the communication base station energy storage scheduling method based on the quantitative evaluation of backup demand.

[0121] Embodiment 2:

[0122] The embodiment of the present invention provides a communication base station energy storage scheduling device based on quantitative evaluation of standby demand, and its structure is as follows: Figure 3 As shown, the device includes the following modules:

[0123] Energy storage battery energy management module, energy storage battery day-ahead dispatch decision module, power system information reading module and communication base station communication power consumption reading module;

[0124] The output ends of the power system information reading module and the communication base station communication power consumption reading module are respectively connected to the input end of the energy storage battery day-ahead scheduling decision module; the output end of the energy storage battery day-ahead scheduling decision module is connected to the energy storage battery energy management module; the power system information reading module is used to read the distribution network parameter information and the power system electricity price information and send them to the energy storage battery day-ahead scheduling decision module; the communication base station communication power consumption reading module is used to read the communication power consumption information of the communication base station and send it to the energy storage battery day-ahead scheduling decision module;

[0125] The energy storage battery day-ahead scheduling decision module is used to receive power system information and communication power consumption information of the communication base station; establish a power supply availability calculation model for the communication base station, quantitatively evaluate the backup demand of the energy storage battery in each time period, and establish a communication base station energy storage battery day-ahead scheduling model that takes into account the backup demand. The communication base station energy storage battery day-ahead scheduling model consists of two parts: an objective function and constraints; and use an optimization solver to solve the communication base station energy storage battery day-ahead scheduling model to obtain the optimal strategy for charging and discharging the communication base station energy storage battery, and send the optimal strategy to the energy storage battery energy management module of the communication base station; the energy storage battery energy management module receives the optimal charging and discharging strategy of the energy storage battery day-ahead scheduling decision module, converts it into a charging and discharging control signal for the energy storage battery, and controls the energy storage battery to operate according to the optimal strategy;

[0126] The power system information reading module is used to read the distribution network parameter information and the power system electricity price information; the power system information reading module is connected to the dispatching automation system, data acquisition and monitoring control system, power market clearing pricing system, etc. in the power system, and can read the network topology information, line parameter information and electricity price information of the distribution network where the communication base station is located; after the information is read, the power system information reading module transmits the distribution network parameter information and the power system electricity price information to the energy storage battery day-ahead dispatching decision module;

[0127] The communication base station communication power consumption reading module is used to read the communication power consumption information of the communication base station. The communication base station communication power consumption reading module is connected to the baseband equipment, optical fiber equipment, antenna equipment and other power-consuming equipment in the communication base station, and can read the power consumption data of various types of equipment in the communication base station; after reading the information, the communication base station communication power consumption reading module transmits the communication power consumption information of the communication base station to the energy storage battery day-ahead scheduling decision module;

[0128] The energy storage battery day-ahead scheduling decision module is used to calculate the day-ahead scheduling decision plan for the communication base station energy storage battery; the energy storage battery day-ahead scheduling decision module establishes a power supply availability calculation model for the communication base station based on the parameters provided by the power system information reading module and the communication base station communication power consumption reading module, quantitatively evaluates the backup demand of the energy storage battery in each time period, establishes a day-ahead scheduling model for the communication base station energy storage battery considering the backup demand, and applies an optimization solver to solve it, thereby obtaining the optimal strategy for charging and discharging the communication base station energy storage battery; after the solution is completed, the module transmits the optimal strategy for charging and discharging the communication base station energy storage battery to the energy management module of the energy storage battery;

[0129] The energy storage battery energy management module is used to control the charging and discharging behavior of the communication base station energy storage battery; the energy storage battery energy management module receives the optimal strategy for charging and discharging the communication base station energy storage battery transmitted by the energy storage battery energy management module, and converts it into charging and discharging control signals for the energy storage battery, thereby controlling the energy storage battery to operate according to the strategy formulated by the energy storage battery day-ahead scheduling decision module.

[0130] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0131] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A communication base station energy storage scheduling method based on quantitative evaluation of backup demand, characterized in that: The method comprises the following steps: Establish a power supply availability calculation model for communication base stations; Quantitatively evaluate the backup demand for energy storage batteries in each period; A communication base station energy storage battery day-ahead scheduling model considering backup demand is established, wherein the communication base station energy storage battery day-ahead scheduling model consists of two parts: an objective function and constraint conditions; Using an optimization solver to solve the communication base station energy storage battery day-ahead scheduling model, to obtain an optimal strategy for charging and discharging the communication base station energy storage battery; sending the optimal strategy to the energy storage battery energy management module of the communication base station; Among them, the power supply availability calculation model is: ； in, is the power supply availability; p is the size of 1×2 with the first element being 1 and the rest being 0 M vector; T is an integer greater than 100000; I is a vector with a scale of (2 M -1)×(2 M -1) unit matrix; D is the backup time of the communication base station energy storage battery; e is a natural constant; A is the state transition density matrix; The scale is (2 M -1) × 1 block matrix of the state transition density matrix; For a scale of 1×(2 M -1) the block matrix of the state transition density matrix; The scale is (2 M -1)×(2 M -1) is a block matrix of the state transition density matrix; M is the number of all lines on the power supply path from the distribution transformer to the communication base station obtained from the distribution network; Among them, the power supply availability formula of the communication base station is expressed as a function of the energy storage backup time: ,set up , given the initial backup time ; Calculate the backup time as Power supply availability of communication base stations under ; Calculate the update amount of backup time, the formula is as follows: ； in, The power supply availability that meets the availability requirements for communication base stations, For function The derivative of if ,but , k=k+1, return and calculate the backup time again Power supply availability of communication base stations under ; Otherwise, output the minimum energy storage backup time ; Among them, establish the backup demand for energy storage batteries of communication base stations in each period Calculation method: ； in, Indicates the time period number. The communication base station is in the time period The communication power consumption, Indicates rounding down.

2. The communication base station energy storage scheduling method based on the quantitative evaluation of backup demand according to claim 1 is characterized in that: The step of establishing a power supply availability calculation model for a communication base station includes: Obtaining information of all lines on the power supply path from the distribution transformer to the communication base station from the distribution network; wherein the line information includes: the failure rate and repair rate of the line; Constructing a random process that characterizes the power supply status of a communication base station; Establish the state transition density matrix corresponding to the random process; Dividing the state transfer density matrix into blocks; According to the divided state transfer density matrix, a power supply availability calculation model for communication base stations is established.

3. The communication base station energy storage scheduling method based on the quantitative evaluation of backup demand according to claim 1 is characterized in that: The method of establishing a day-ahead scheduling model for energy storage batteries of communication base stations considering backup demand includes: Based on the daily power data of the communication base station, the objective function of the day-ahead dispatch model of the energy storage battery of the communication base station is constructed; According to the charging and discharging power, charging and discharging efficiency, rated capacity of the energy storage battery and the rated power of the communication base station, the constraint conditions of the day-ahead scheduling model of the communication base station energy storage battery are constructed; the constraint conditions include: energy balance constraint, safe operation constraint and backup demand constraint.

4. The communication base station energy storage scheduling method based on the quantitative evaluation of backup demand according to claim 3 is characterized in that: The objective function of the day-ahead scheduling model of the energy storage battery of the communication base station is constructed according to the single-day power data of the communication base station, including: ； in, is the total daily operation cost of the base station; T is the total number of time slots in a single day; is the electricity price in time period t; is the purchased power in period t; where, Electricity price information is obtained from the power system.

5. The communication base station energy storage scheduling method based on the quantitative evaluation of backup demand according to claim 3 is characterized in that: According to the charging and discharging power, charging and discharging efficiency, rated capacity of the energy storage battery and the rated power of the communication base station, the constraint conditions of the day-ahead scheduling model of the energy storage battery of the communication base station are constructed, including: Energy balance constraints: ； ； in, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the state of charge of the energy storage battery, is the charging efficiency, is the discharge efficiency, The communication base station is in the time period Communication power consumption; Safe operation constraints: in, is the rated capacity of the energy storage battery; The communication base station is in the time period Communication power consumption; is the rated power of the communication base station power supply, Is a 0-1 variable, when the energy storage battery is charged , when the energy storage battery is discharged ; Alternative demand constraints: 。 6. A communication base station energy storage scheduling device based on quantitative evaluation of backup demand, characterized in that: The device is used to implement a communication base station energy storage scheduling method based on quantitative evaluation of backup demand as described in claim 1, and the device includes the following modules: an energy storage battery energy management module, an energy storage battery day-ahead scheduling decision module, a power system information reading module and a communication base station communication power consumption reading module; The output ends of the power system information reading module and the communication base station communication power consumption reading module are respectively connected to the input end of the energy storage battery day-ahead dispatch decision module; the output end of the energy storage battery day-ahead dispatch decision module is connected to the energy storage battery energy management module; The power system information reading module is used to read the distribution network parameter information and the power system electricity price information and send them to the energy storage battery day-ahead scheduling decision module; The communication base station communication power consumption reading module is used to read the communication power consumption information of the communication base station and send it to the energy storage battery day-ahead scheduling decision module; The energy storage battery day-ahead scheduling decision module is used to receive power system information and communication power consumption information of the communication base station; establish a power supply availability calculation model for the communication base station, quantitatively evaluate the backup demand of the energy storage battery in each time period, and establish a communication base station energy storage battery day-ahead scheduling model that takes into account the backup demand. The communication base station energy storage battery day-ahead scheduling model consists of two parts: an objective function and constraints; and use an optimization solver to solve the communication base station energy storage battery day-ahead scheduling model to obtain the optimal strategy for charging and discharging the communication base station energy storage battery, and send the optimal strategy to the energy storage battery energy management module of the communication base station; the energy storage battery energy management module receives the optimal charging and discharging strategy of the energy storage battery day-ahead scheduling decision module, converts it into a charging and discharging control signal for the energy storage battery, and controls the energy storage battery to operate according to the optimal strategy.

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