A method for jointly operating tower base station energy storage and power network

Abstract

The present invention provides a method for the joint operation of tower base station energy storage and power network, comprising the following steps: identifying the power consumption of each device of the base station energy storage; performing energy management on the base station energy storage battery, monitoring the battery group parameter information and the battery group status information; performing dispatchable capacity evaluation on the base station energy storage battery; establishing an optimization scheduling model for the base station backup energy storage aggregator based on the obtained base station energy storage power consumption and the evaluation of the dispatchable capacity of the base station energy storage battery; solving the optimization scheduling model, preliminarily screening out qualified base station energy storage to participate in the demand response market, and recording the actual records of the base station energy storage demand response; then setting different weights based on the actual records to form a market-based evaluation value at the user level, and screening out energy storage base station users who ultimately participate in the demand response market; the present invention can screen out suitable energy storage base station users to participate in the power grid demand response, thereby realizing the joint operation and win-win situation of the communication base station and the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage configuration, and in particular to a method for jointly operating energy storage of a tower base station and a power network. Background Art

[0002] As the construction of Digital China and a cyber-powerful nation deepens, the incremental construction and energy consumption of tower base stations are expected to rise exponentially. These massive base stations represent a typical distributed, flexible resource. While base station electrical equipment offers a certain degree of power consumption adjustment, base station energy storage batteries serve as backup power sources. Under varying operating conditions, these batteries can be used for backup and for flexible scheduling. Therefore, base station energy storage batteries can serve as a time-varying energy storage system, participating in market-based services such as power system demand response.

[0003] Faced with the increasingly severe challenges of power peak and frequency regulation, incorporating base stations into regular power system dispatching and operation can not only improve system operating efficiency but also achieve asset-light operations. For communication systems, base station participation in demand response is a potential way to reduce electricity costs.

[0004] Therefore, there is an urgent need for a method for the joint operation of tower base station energy storage and power network, which can store energy in massive base stations distributed in different areas. While meeting the main responsibilities and main business of communication, it can participate in market services such as grid demand response when the power load is operating at peak and valley times, thereby realizing the joint operation of communication base stations and power grids and a win-win model. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for the joint operation of tower base station energy storage and power network, aiming to solve the technical problems of the traditional model, in which base station energy storage can only meet communication services and cannot participate in grid demand response, resulting in excessively high communication costs.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for jointly operating tower base station energy storage and power network, the steps of which include:

[0007] S1: Identify the power consumption of each device in the base station energy storage;

[0008] S2: Performs energy management on the base station energy storage battery, monitoring parameters such as the battery pack's voltage, current, and power; and monitors real-time battery pack usage, charge and discharge status, battery pack health status, fault point identification, and other status information.

[0009] S3: Based on the base station energy storage battery information obtained in step S2, the dispatchable capacity of the base station energy storage battery is evaluated;

[0010] S4: Based on the base station energy storage power consumption obtained in step S1 and the evaluation of the dispatchable capacity of the base station energy storage battery in step S3; considering the maximization of social benefits, with the base station energy storage aggregator's revenue and the standard deviation of load fluctuation as optimization objectives, an optimization scheduling model for the base station backup energy storage aggregator is established;

[0011] S5: Solving the optimization scheduling model to obtain the base station energy storage with the highest demand response capacity compensation fee and the highest electric energy compensation fee for energy storage users, the lowest electricity purchase cost for energy storage users, and the smallest load standard deviation;

[0012] S6: Filtering out eligible base station energy storage from the base station energy storage obtained in step S5 to participate in the demand response market, and recording actual records of the base station energy storage demand response;

[0013] Then, based on the actual records, different weights are set to form a market-based evaluation value at the user level. Finally, energy storage base station users with many participation times, low electricity purchase costs, long response times, large response capacities, maximum response loads, and small response load fluctuations are prioritized to participate in the demand response market.

[0014] As a further improvement to the above solution, the optimization scheduling model of the base station backup energy storage aggregator is a model that maximizes the demand response benefits, as shown in the following formula:

[0015]

[0016] Where C1 is the annual revenue of energy storage for demand response, in RMB; n is the number of times energy storage is called for demand response per year; C drc is the demand response capacity compensation fee, in yuan; C dre C is the demand response electricity compensation fee, in yuan; e is the electricity purchase cost of energy storage, in yuan; C dra It is the demand response assessment fee, in Yuan.

[0017] As a further improvement to the above solution, when solving the optimization scheduling model, the maximization of demand response benefits is decomposed into two optimization objectives, as shown below:

[0018] Optimization goal 1: To improve the demand response capacity compensation fee and electric energy compensation fee of energy storage users, as shown in formula (2):

[0019] MAXC2=MAX(C drc +C dre ) (2)

[0020] Among them, C2 is the capacity compensation fee, C drc C is the demand response capacity compensation fee for energy storage users, in RMB; dreIt is the demand response electricity energy compensation fee, in Yuan.

[0021] Optimization goal 2: The goal is to minimize the electricity purchase cost and load standard deviation of energy storage users, as shown in formula (7):

[0022] MinF=Min(w2C e +C dra ) (7)

[0023] Among them, C e The electricity purchase cost for energy storage users, C dra is the demand response assessment fee; w2 is C e The weight coefficient of .

[0024] As a further improvement to the above solution, the energy storage user demand response capacity compensation fee is specifically shown in formula (3):

[0025] When the unit price of capacity fee is determined, the only factor affecting the demand response capacity compensation fee for energy storage users is the capacity size of the energy storage user;

[0026] C drc =C rc *P rc (3)

[0027] Where: C rc is the capacity of energy storage users participating in demand response, P rc The unit price of capacity subsidy.

[0028] As a further improvement to the above solution, the demand response electric energy compensation fee is specifically shown in formula (4):

[0029] C dre =w1P wo *P ho *P lc (4)

[0030] Among them, P wo is the discharge power of the base station energy storage battery, P ho is the discharge time of the base station energy storage battery, which must be greater than or equal to the demand response market. lc is the electricity compensation unit price, w1 is the electricity compensation fee and P wo The weight coefficient between .

[0031] As a further improvement to the above scheme, it can be seen from formula (4) that to increase the compensation fee for the response electric energy, it can be achieved by increasing the discharge power of the base station energy storage battery. The discharge power of the base station energy storage battery is shown in formula (6):

[0032] When the demand response time is fixed, the more loads the energy storage participates in the response, the greater the subsidy benefits the user will obtain. According to the battery theoretical discharge time formula (5):

[0033] P ho =[B rc -B c ×(1-B dod )] / P wo ×R o (5)

[0034] Available

[0035] P wo =[B rc -B c ×(1-B dod )] / P ho ×R o (6)

[0036] Where: P ho is the theoretical discharge working time, B rc is the remaining capacity of the battery, B c is the battery capacity, B dod is the battery discharge depth, P wo is the average discharge power, R o Average discharge coefficient.

[0037] As a further improvement to the above solution, the electricity purchase cost of the energy storage user is shown in formula (8):

[0038]

[0039] Where: c t is the time-of-use electricity price provided by the power grid to users at time t, P et is the load value at time t, T is the charging time span of the energy storage user, which is composed of multiple small t, and the time-of-use electricity price at each small t is different.

[0040] As a further improvement to the above scheme, the demand response assessment fee is shown in formula (9):

[0041] C dra =w3f(P) (9)

[0042] Where f(P) is the load standard deviation of the load curve, and w3 is the weight coefficient of f(P).

[0043] As a further improvement of the above solution, the load standard deviation of the load curve is shown in formula (10):

[0044]

[0045] Among them, P a is the average load value after the load curve demand response, P e,t is the value of the electricity load in period t after demand response, P e,ES,t is the grid load value after the energy storage system participates in the output, P s,t It is the fixed load in period t, i.e. the load that does not participate in demand response.

[0046] As a further improvement to the above solution, in step S6, when eligible base station energy storage is selected to participate in the demand response market,

[0047] The base station energy storage operating voltage needs to meet the requirements of formula (12), and the specific formula (12) is as follows:

[0048] V i ≥V alert (12)

[0049] Where: V i is the base station energy storage operating voltage, V alert It is the out-of-service alarm voltage;

[0050] According to formula (12), all base station energy storage sets that meet the base station energy storage operating voltage requirements are screened out as shown in S1: S1 = {[Sv]};

[0051] The base station energy storage operation also needs to meet different factors for participating in the joint operation of the power network. The base station energy storage set that can participate in demand response is screened according to different factors as shown in S2:

[0052] S2={[Stq],[Sjj],[Sqy],[Sbg]}

[0053] Wherein: [Stq] is the set of base station energy storage that can participate in demand response under various weather factors, [Sjj] is the set of base station energy storage that can participate in demand response under various seasonal factors, [Sqy] is the set of base station energy storage that can participate in demand response under various regional factors, and [Sbg] is the set of key supply-guaranteed base station energy storage that can participate in demand response.

[0054] As a further improvement to the above scheme, in step S6, when screening energy storage base station users to participate in the demand response market, the total score of energy storage users participating in the demand response of the screened energy storage base stations is calculated according to the calculation formula for the total score of energy storage users participating in the demand response as shown in formula (13). The specific formula (13) is as follows:

[0055] TOsco=w4CSsco+w5CBsco+w6SCsco+w7RLsco+w8FHsco+w9BDsco (13)

[0056] Among them, CSsco is the participation score, CBsco is the electricity purchase cost score; SCsco is the response time score; RLsco is the response capacity score; FHsco is the response load score; BDsco is the load fluctuation score; TOsco is the total score; w4~w9 are the weight coefficients of each score respectively;

[0057] Then, the energy storage users are sorted in descending order according to their total scores in participating in demand response, and the top N energy storage users are selected to participate in demand response based on actual needs.

[0058] In a second aspect, the present invention further provides a device comprising a memory for storing computer program instructions and a processor for executing computer program instructions, wherein, when the computer program instructions are executed by the processor, the device is triggered to execute a method for jointly operating tower base station energy storage and power network provided in the first aspect.

[0059] In a third aspect, the present invention further provides a storage medium storing a computer program, wherein when the program is running, the device where the storage medium is located is controlled to execute a method for jointly operating tower base station energy storage and power network provided in the first aspect.

[0060] Since the present invention adopts the above technical solution, the beneficial effects of this application are:

[0061] The present invention provides a method for the joint operation of energy storage in a tower base station and a power network, the steps of which include: S1: identifying the power consumption of each energy storage device in the base station; S2: performing energy management on the energy storage battery of the base station, monitoring the voltage, current, power and other parameter information of the battery pack; and real-time monitoring of the battery pack usage, charge and discharge status, battery pack health status, fault point identification and other status information; S3: based on the base station energy storage battery information obtained in step S2, evaluating the dispatchable capacity of the base station energy storage battery; S4: based on the base station energy storage power consumption obtained in step S1 and the dispatchable capacity of the base station energy storage battery in step S3, evaluating the dispatchable capacity of the base station energy storage battery. Considering the maximization of social benefits, taking the base station energy storage aggregator's income and load fluctuation standard deviation as the optimization target, an optimization scheduling model for the base station standby energy storage aggregator is established; S5: Solving the optimization scheduling model to obtain the base station energy storage with the highest demand response capacity compensation fee and the highest electric energy compensation fee for energy storage users, the lowest electricity purchase cost for energy storage users and the smallest load standard deviation; S6: Screening out the base station energy storage that meets the conditions from the base station energy storage obtained in step S5 to participate in the demand response market, and recording the actual record of the base station energy storage demand response; then setting according to the actual record Different weights are used to form a market-based evaluation value at the user level, and finally, energy storage base station users with many participation times, low electricity purchase costs, long response times, large response capacities, maximum response loads, and small response load fluctuations are prioritized to participate in the demand response market. In the present invention, basic information of base station energy storage and various factors affecting the participation of base station energy storage in demand response operations are first considered, and an optimization scheduling model is established to obtain base station energy storage with the highest demand response capacity compensation fee and the highest electric energy compensation fee for energy storage users, the lowest electricity purchase costs for energy storage users, and the smallest load standard deviation. From the obtained base station energy storage, those base station energy storages that can maximize demand response benefits are preliminarily screened, and finally, energy storage base station users with many participation times, low electricity purchase costs, long response times, large response capacities, maximum response loads, and small response load fluctuations are prioritized to participate in the demand response market. The method provided by the present invention can maximize the benefits of tower base stations when participating in demand response market services while meeting the main business requirements of tower base stations, achieving a win-win situation for both supply and demand sides, thereby solving the technical problem of high communication costs caused by the traditional model where base station energy storage can only meet communication services and cannot participate in grid demand response. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 the structures shown in these drawings without paying any creative work.

[0063] Figure 1 A schematic flow chart of a method for jointly operating energy storage in a tower base station and a power network provided by the present invention.

[0064] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0065] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0066] The technical solutions between the various embodiments of the present invention can be combined with each other, but they must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0067] Example 1:

[0068] See also Figure 1 In this example, a tower base station aggregator selects qualified base stations to participate in response to the invitation requirements, such as the summer peak demand response and the winter peak demand response in a certain province. The present invention provides a method for the joint operation of tower base station energy storage and power network, which includes the following steps:

[0069] S0: First, the basic information of the base station energy storage under its jurisdiction is sorted out, including base station capacity, location, float charge voltage, and battery life. Then, factors affecting the energy storage are identified based on weather, season, region, key power supply base stations, and base station failures. Based on recent weather conditions, the following base stations are eliminated: 1. Base stations with inconvenient transportation; 2. Key power supply base stations; 3. Faulty base stations; 4. Base stations with insufficient capacity or float charge voltage.

[0070] S1: Identify the power consumption of each device in the base station energy storage. Specifically, it is necessary to identify the power consumption of the main equipment, air conditioning equipment, power supply equipment, other equipment, and lighting within the base station energy storage, and clearly define the type of power consumption, influencing factors, and whether each type of power consumption can be interrupted. The power consumption of the main equipment is mainly related to factors such as equipment configuration, manufacturer, location, and holidays. The power consumption of air conditioning equipment is mainly related to the site area and weather. The power consumption of power supply equipment is mainly determined by equipment efficiency. The power consumption of other equipment and lighting is mainly determined by line loss, monitoring equipment, and lighting power consumption.

[0071] S2: Performs energy management on the base station energy storage battery, monitoring parameters such as the battery pack's voltage, current, and power; and monitors real-time battery pack usage, charge and discharge status, battery pack health status, fault point identification, and other status information.

[0072] S3: Based on the base station energy storage battery information obtained in step S2, the dispatchable capacity of the base station energy storage battery is evaluated. The dispatchable capacity depends on the maximum power outage time and power load curve of the base station energy storage. The power outage time is not affected by regional attributes, but the power load has significant spatiotemporal characteristics (tidal effect). The steps and methods for evaluating the dispatchable capacity of the base station energy storage battery are as follows:

[0073] Data collection: Collect historical heat map data of different types of areas (residential areas, commercial areas, and office areas) and calculate historical crowd gathering data;

[0074] Data prediction: Considering differences in regional attributes and weekday attributes, different neural network models are trained to predict crowd concentration;

[0075] Data evaluation: Calculate the power load of the base station energy storage based on the predicted crowd density, set the maximum power outage time based on the base station energy storage reliability index and battery reliability rate, and then calculate the dispatchable capacity of the base station energy storage backup battery;

[0076] S4: Based on the base station energy storage power consumption obtained in step S1 and the evaluation of the dispatchable capacity of the base station energy storage battery in step S3; considering the maximization of social benefits, with the base station energy storage aggregator's revenue and the standard deviation of load fluctuation as optimization objectives, an optimization scheduling model for the base station backup energy storage aggregator is established;

[0077] Specifically, the optimization scheduling model of the base station backup energy storage aggregator is a model that maximizes the demand response benefits, as shown in the following formula:

[0078]

[0079] Where C1 is the annual revenue of energy storage for demand response, in RMB; n is the number of times energy storage is called for demand response per year; C drc is the demand response capacity compensation fee, in yuan; C dre C is the demand response electricity compensation fee, in yuan; e is the electricity purchase cost of energy storage, in yuan; C dra is the demand response assessment fee, in Yuan;

[0080] S5: Solving the optimization scheduling model to obtain the base station energy storage with the highest demand response capacity compensation fee and the highest electric energy compensation fee for energy storage users, the lowest electricity purchase cost for energy storage users, and the smallest load standard deviation;

[0081] S6: Filtering out base station energy storage that meets the conditions from the base station energy storage obtained in step S5 to participate in the demand response market, and recording actual records of the base station energy storage demand response;

[0082] Then, based on the actual records, different weights are set to form a market-based evaluation value at the user level. Finally, energy storage base station users with a high number of participations, low electricity purchase costs, long response times, large response capacities, maximum response loads, and small response load fluctuations are prioritized for participation in the demand response market.

[0083] In the present invention, the basic information of base station energy storage and various factors affecting the participation of base station energy storage in demand response operations are first considered, and an optimization scheduling model is established to obtain the base station energy storage with the highest demand response capacity compensation fee and the highest electric energy compensation fee for energy storage users, the lowest electricity purchase cost for energy storage users, and the smallest load standard deviation. From the obtained base station energy storage, those base station energy storages that can maximize the demand response benefits are preliminarily screened out, and finally energy storage base station users with many participation times, low electricity purchase costs, long response times, large response capacities, maximum response loads, and small response load fluctuations are preferentially screened to participate in the demand response market. The method provided by the present invention can maximize the benefits of iron tower base stations when participating in demand response market services while meeting the main business requirements of iron tower base stations, thereby achieving a win-win situation for both supply and demand sides, thereby solving the technical problem of the traditional model in which base station energy storage can only meet communication services and cannot participate in grid demand response, resulting in excessively high communication costs.

[0084] As a preferred embodiment, when solving the optimization scheduling model, the maximization of demand response benefits is decomposed into two optimization objectives, as shown below:

[0085] Optimization goal 1: To improve the demand response capacity compensation fee and electric energy compensation fee of energy storage users, as shown in formula (2):

[0086] MAXC2=MAX(C drc +C dre )(2)

[0087] Among them, C2 is the capacity compensation fee, C drc C is the demand response capacity compensation fee for energy storage users, in RMB; dre The demand response electricity energy compensation fee, in yuan;

[0088] Specifically, the energy storage user demand response capacity compensation fee is as shown in formula (3):

[0089] When the unit price of capacity fee is determined, the only factor affecting the demand response capacity compensation fee for energy storage users is the capacity size of the energy storage user;

[0090] Cdrc =C rc *P rc (3)

[0091] Where: C rc is the capacity of energy storage users participating in demand response, P rc is the unit price of capacity subsidy;

[0092] The demand response electric energy compensation fee is specifically shown in formula (4):

[0093] C dre =w1P wo *P ho *P lc (4)

[0094] Among them, P wo is the discharge power of the base station energy storage battery, P ho is the discharge time of the base station energy storage battery, which must be greater than or equal to the demand response market. lc is the electricity compensation unit price, w1 is the electricity compensation fee and P wo The weight coefficient between

[0095] From formula (4), it can be seen that to increase the compensation cost of the response electric energy, it can be achieved by increasing the discharge power of the base station energy storage battery. The discharge power of the base station energy storage battery is shown in formula (6):

[0096] When the demand response time is fixed, the more loads the energy storage participates in the response, the greater the subsidy benefits the user will obtain. According to the battery theoretical discharge time formula (5):

[0097] P ho =[B rc -B c ×(1-B dod )] / P wo ×R o (5)

[0098] Available

[0099] P wo =[B rc -B c ×(1-B dod )] / P ho ×R o (6)

[0100] Where: P ho is the theoretical discharge working time, B rc is the remaining capacity of the battery, B c is the battery capacity, B dod is the battery discharge depth, P wois the average discharge power, R o Average discharge coefficient.

[0101] Optimization goal 2: The goal is to minimize the electricity purchase cost and load standard deviation of energy storage users, as shown in formula (7):

[0102] MinF=Min(w2C e +C dra ) (7)

[0103] Among them, C e The electricity purchase cost for energy storage users, C dra is the demand response assessment fee; w2 is C e The weight coefficient of

[0104] Specifically, the electricity purchase cost of the energy storage user is shown in formula (8):

[0105]

[0106] Where: c t is the time-of-use electricity price provided by the power grid to users at time t, P et is the load value at time t, T is the charging time span of the energy storage user, which is composed of multiple small t, and the time-of-use electricity price at each small t is different.

[0107] The demand response assessment fee is shown in formula (9):

[0108] C dra =w3f(P) (9)

[0109] Where f(P) is the load standard deviation of the load curve, and w3 is the weight coefficient of f(P).

[0110] The load standard deviation of the load curve is shown in formula (10):

[0111]

[0112] Among them, P a is the average load value after the load curve demand response, P e,t is the value of the electricity load in period t after demand response, P e,ES,t is the grid load value after the energy storage system participates in the output, P s,t It is the fixed load in period t, i.e. the load that does not participate in demand response.

[0113] As a preferred embodiment, when using energy storage to participate in the demand response market, the minimum voltage requirement for normal operation of the base station, i.e., the out-of-service alarm voltage, must be ensured to be higher than the out-of-service alarm voltage requirement. Users whose energy storage discharge does not meet the requirements cannot participate in the demand response market.

[0114] In step S6, when eligible base station energy storage is selected to participate in the demand response market, the base station energy storage operating voltage needs to meet the requirements of formula (12), and the specific formula (12) is as follows:

[0115] V i ≥V alert (12)

[0116] Where: V i is the base station energy storage operating voltage, V alert It is the out-of-service alarm voltage;

[0117] According to formula (12), all base station energy storage sets that meet the base station energy storage operating voltage requirements are screened out as shown in S1: S1 = {[Sv]};

[0118] The base station energy storage operation also needs to meet different factors for participating in the joint operation of the power network. The base station energy storage set that can participate in demand response is screened according to different factors as shown in S2:

[0119] S2={[Stq],[Sjj],[Sqy],[Sbg]}

[0120] Wherein: [Stq] is the set of base station energy storage that can participate in demand response under various weather factors, [Sjj] is the set of base station energy storage that can participate in demand response under various seasonal factors, [Sqy] is the set of base station energy storage that can participate in demand response under various regional factors, and [Sbg] is the set of key supply-guaranteed base station energy storage that can participate in demand response.

[0121] As a preferred embodiment, within the scope of Sets S1 and S2, eligible base station energy storage units are continuously screened to participate in the demand response market, and actual records of demand responses are recorded, including the number of participations, electricity purchase costs, response time, response capacity, response load, load fluctuation, etc. Based on these actual records, different weights are set to form a user-level market-based evaluation value table, as shown in Table 1. Finally, energy storage base station users with high participation times, low electricity purchase costs, long response times, large response capacities, the largest response loads, and small response load fluctuations are prioritized for participation in the demand response market.

[0122] Table 1: Market evaluation value table of base station energy storage

[0123]

[0124] Specifically, in step S6, when selecting energy storage base station users to participate in the demand response market, the total score of energy storage users participating in the demand response of the selected energy storage base stations is calculated according to the calculation formula for the total score of energy storage users participating in the demand response as shown in formula (13). The specific formula (13) is as follows:

[0125] TOsco=w4CSsco+w5CBsco+w6SCsco+w7RLsco+w8FHsco+w9BDsco(13)

[0126] Among them, w4~w9 are the weight coefficients of each score respectively; then the energy storage users are sorted in descending order according to their total scores participating in demand response, and the top N energy storage users are selected to participate in demand response according to actual needs.

[0127] By adopting the method for jointly operating the tower base station energy storage and the power network provided by the present invention, and utilizing intelligent regulation between the load aggregation platform and the base station battery energy storage, the stable power supply of the base station is ensured while participating in peak shaving and valley filling of the power grid, effectively stimulating the potential energy of the backup power on the base station side, and while reducing the electricity cost of the base station, providing flexible resources for the power system, thus realizing the scale effect and economic effect of "accumulating sand into a tower" of massive base station energy storage.

[0128] Example 2:

[0129] The present invention further provides a device, comprising a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to execute some or all of the steps in Example 1;

[0130] A processor may include one or more processing units, for example, an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU). Different processing units may be independent devices or integrated into one or more processors.

[0131] The controller can be the nerve center and command center of the electronic device. The controller can generate operation control signals based on instruction operation codes and timing signals to complete the control of instruction fetching and execution.

[0132] The processor may also include a memory for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. This memory can store instructions or data that the processor has just used or is reusing. If the processor needs to use the instruction or data again, it can directly call it from the memory. This avoids repeated accesses, reduces processor latency, and thus improves system efficiency.

[0133] Example 3:

[0134] The present invention also provides a storage medium having a computer program stored thereon, wherein when the program is running, the device where the storage medium is located is controlled to execute part or all of the steps in Example 1.

[0135] The storage medium may include a high-speed RAM memory, and may also include a nonvolatile memory, such as at least one disk storage. It is understood that the storage medium can be a random access memory (RAM), a magnetic disk, a hard disk, a solid state disk (SSD), or a nonvolatile memory, and other machine-readable media that can store program code.

[0136] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods or storage media. Therefore, embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. All equivalent structural transformations made using the contents of the present description and drawings under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included in the patent protection scope of the present invention.

Claims

1. A method for the joint operation of tower base station energy storage and power network, characterized in that: The steps include: S1: Identify the power consumption of each device in the base station energy storage; S2: Perform energy management on the base station energy storage battery, monitor battery pack parameter information, including voltage, current, and power; and monitor battery pack status information in real time, including usage, charge and discharge status, battery pack health status, and fault point identification; S3: Based on the base station energy storage battery information obtained in step S2, the dispatchable capacity of the base station energy storage battery is evaluated; S4: Based on the base station energy storage power consumption obtained in step S1 and the evaluation of the dispatchable capacity of the base station energy storage battery in step S3; considering the maximization of social benefits, with the base station energy storage aggregator's revenue and the standard deviation of load fluctuation as optimization objectives, an optimization scheduling model for the base station backup energy storage aggregator is established; S5: Solving the optimization scheduling model to obtain the base station energy storage with the highest demand response capacity compensation fee and the highest electric energy compensation fee for energy storage users, the lowest electricity purchase cost for energy storage users, and the smallest load standard deviation; S6: Preliminarily screening out eligible base station energy storages from the base station energy storages obtained in step S5 to participate in the demand response market, and recording actual records of the base station energy storage demand responses; Then, based on the actual records, different weights are set to form a market-based evaluation value at the user level. Finally, energy storage base station users with many participation times, low electricity purchase costs, long response times, large response capacities, maximum response loads, and small response load fluctuations are prioritized to participate in the demand response market.

2. A method for jointly operating tower base station energy storage and power network according to claim 1, characterized in that: The optimal scheduling model of the base station backup energy storage aggregator is a model that maximizes the demand response benefits, as shown in the following formula: Where C1 is the annual revenue of energy storage for demand response, in RMB; n is the number of times energy storage is called for demand response per year; C drc is the demand response capacity compensation fee, in yuan; C dre C is the demand response electricity compensation fee, in yuan; e is the cost of purchasing electricity for energy storage, in yuan; C dra It is the demand response assessment fee, in Yuan.

3. A method for jointly operating tower base station energy storage and power network according to claim 2, characterized in that: When solving the optimization scheduling model, the maximization of demand response benefits is decomposed into two optimization objectives, as shown below: Optimization goal 1: To improve the demand response capacity compensation fee and electric energy compensation fee of energy storage users, as shown in formula (2): MAXC2=MAX(C drc +C dre ) (2) Among them, C2 is the capacity compensation fee, C drc C is the demand response capacity compensation fee for energy storage users, in RMB; dre The demand response electricity energy compensation fee, in yuan; Optimization goal 2: The goal is to minimize the electricity purchase cost and load standard deviation of energy storage users, as shown in formula (7): MinF=Min(w2C e +C dra ) (7) Among them, C e The electricity purchase cost for energy storage users, C dra is the demand response assessment fee; w2 is C e The weight coefficient of .

4. A method for jointly operating tower base station energy storage and power network according to claim 3, characterized in that: The energy storage user demand response capacity compensation fee is specifically shown in formula (3): When the unit price of capacity fee is determined, the only factor affecting the demand response capacity compensation fee for energy storage users is the capacity size of the energy storage user; C drc =C rc *P rc (3) Where: C rc is the capacity of energy storage users participating in demand response, P rc The unit price of capacity subsidy.

5. The method for jointly operating the tower base station energy storage and the power network according to claim 3, characterized in that: The demand response electric energy compensation fee is specifically shown in formula (4): C dre =w1P wo *P ho *P lc (4) Among them, P wo is the discharge power of the base station energy storage battery, P ho is the discharge time of the base station energy storage battery, which must be greater than or equal to the demand response market. lc is the electricity compensation unit price, w1 is the electricity compensation fee and P wo The weight coefficient between .

6. A method for jointly operating tower base station energy storage and power network according to claim 5, characterized in that: The discharge power of the base station energy storage battery is calculated by formula (6), and the specific formula (6) is as follows: P wo =[B rc -B c ×(1-B dod )] / P ho ×R o (6) Where: P ho is the theoretical discharge working time, B rc is the remaining capacity of the battery, B c is the battery capacity, B dod is the battery discharge depth, P wo is the average discharge power, R o Average discharge coefficient.

7. A method for jointly operating tower base station energy storage and power network according to claim 3, characterized in that: The electricity purchase cost of energy storage users is shown in formula (8): Where: c t is the time-of-use electricity price provided by the power grid to users at time t, P et is the load value at time t, and T is the charging time span of the energy storage user.

8. A method for jointly operating tower base station energy storage and power network according to claim 7, characterized in that: The demand response assessment fee is shown in formula (9): C dra =w3f(P) (9) Where f(P) is the load standard deviation of the load curve, and w3 is the weight coefficient of f(P).

9. A method for jointly operating tower base station energy storage and power network according to any one of claims 1 to 8, characterized in that: In step S6, when eligible base station energy storage is selected to participate in the demand response market, The base station energy storage operating voltage needs to meet the requirements of formula (12), and the specific formula (12) is as follows: In i ≥V alert (12) Where: V i is the base station energy storage operating voltage, V alert It is the out-of-service alarm voltage; According to formula (12), all base station energy storage sets that meet the base station energy storage operating voltage requirements are screened out as shown in S1: S1 = {[Sv]}; The base station energy storage operation also needs to meet different factors for participating in the joint operation of the power network. The base station energy storage set that can participate in demand response is screened according to different factors as shown in S2: S2={[Stq],[Sjj],[Sqy],[Sbg]} Wherein: [Stq] is the set of base station energy storage that can participate in demand response under various weather factors, [Sjj] is the set of base station energy storage that can participate in demand response under various seasonal factors, [Sqy] is the set of base station energy storage that can participate in demand response under various regional factors, and [Sbg] is the set of key supply-guaranteed base station energy storage that can participate in demand response.

10. A method for jointly operating tower base station energy storage and power network according to any one of claims 1 to 8, characterized in that: In step S6, when selecting energy storage base station users to participate in the demand response market, the total score of energy storage users participating in the demand response of the selected energy storage base stations is calculated according to the total score calculation formula of energy storage users participating in the demand response as shown in formula (13). The specific formula (13) is as follows: TOsco=w4CSsco+w5CBsco+w6SCsco+w7RLsco+w8FHsco+w9BDsco(13) Among them, CSsco is the participation score, CBsco is the electricity purchase cost score; SCsco is the response time score; RLsco is the response capacity score; FHsco is the response load score; BDsco is the load fluctuation score; TOsco is the total score; w4~w9 are the weight coefficients of each score respectively; Then, the energy storage users are sorted in descending order according to their total scores in participating in demand response, and the top N energy storage users are selected to participate in demand response based on actual needs.

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