Power supply distribution method and device of base station and computer readable storage medium

Abstract

The invention provides a power supply distribution method for a base station, and the method comprises the steps: predicting the power consumption demand of the base station in at least one period in the future, and predicting the power generation amount of green power equipment deployed for the base station in at least one period in the future; according to the generating capacity and power supply parameters of a power supply, determining a power supply distribution strategy with minimum operation consumption of the base station under the condition that the power consumption demand is met; and distributing the power supply quantity of each power supply according to the power supply distribution strategy. The invention further provides a power supply distribution device of the base station and a computer readable storage medium. According to the technical scheme, the energy cost of the mobile base station can be minimized while the normal power supply requirement of the mobile base station is supported, and the operation consumption of the mobile base station is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of communication base stations, and in particular to a power supply distribution method, device and computer-readable storage medium for a base station. Background Art

[0002] With the introduction of more spectrum and larger bandwidth, the energy cost of mobile base stations is increasing. At the same time, with the advancement of smart grids, the introduction of renewable energy, and the application of local power storage equipment in base stations, mobile base stations can use city power, green power and storage power for flexible power supply.

[0003] At present, the mains, green power or storage power supply to the base station is usually provided according to the pre-allocated power supply time or power supply amount. For example, the mains supply is x hours, the green power supply is y hours, and the storage power supply is z hours; or the mains supply is X kilowatts, the green power supply is Y kilowatts, and the storage power supply is Z kilowatts. However, the mains price and the amount of green power generated will vary based on time or environment. If the mains, green power and storage power supply are provided according to a fixed allocation method, it may lead to higher energy costs for mobile base stations, resulting in excessive operation consumption of mobile base stations. Summary of the invention

[0004] In response to the above technical problems, the present application provides a base station power supply distribution method, device and computer-readable storage medium, which aims to optimize (minimize) the energy cost of the mobile base station while adjusting the power supply strategy of each power supply source to the mobile base station so that the mobile base station can be powered normally, thereby reducing the operating cost of the mobile base station.

[0005] In a first aspect, the present application provides a power distribution method for a base station, comprising:

[0006] Predicting the electricity demand of the base station in at least one future cycle, and predicting the power generation of the green power equipment deployed on the base station in at least one future cycle;

[0007] Determine, based on the power generation and the power supply parameters of the power supply source, a power supply allocation strategy that minimizes the power consumption of the base station when the power demand is met;

[0008] The power supply of each of the power supply sources is allocated according to the power supply allocation strategy.

[0009] In some embodiments, the step of determining, based on the power generation and the power supply parameters of the power supply source, a power supply allocation strategy for minimizing the operation consumption of the base station when the power demand is met includes:

[0010] The power generation, the power demand and the power supply parameters of the power supply source are input into a preset linear programming problem model to obtain a power supply allocation strategy with minimum operation consumption of the base station.

[0011] In some embodiments, the power supply source includes city power and green power equipment, the power supply parameters of the city power include the city power price, and the power supply parameters of the green power equipment include the green power supply efficiency factor and the green power grid access price;

[0012] Alternatively, the power supply source includes AC power, green power equipment and power storage equipment, the power supply parameters of the AC power include at least one of the AC power price and the AC power storage efficiency factor, the power supply parameters of the green power equipment include at least one of the green power supply efficiency factor, the green power grid-connected power price and the green power storage efficiency factor, and the power supply parameters of the power storage equipment include at least one of the charging and discharging efficiency factor and the charging and discharging unit depreciation price.

[0013] In some embodiments, the step of inputting the power generation amount and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with the minimum operation consumption of the base station includes:

[0014] The first power supply is provided by the mains and the second power supply is provided by the green power equipment, and a data combination corresponding to the first power supply and the second power supply that meets the power demand is determined based on the constraint conditions of the linear programming problem model; wherein the second power supply is determined according to the green power output amount of the green power equipment to the base station and the green power supply efficiency factor;

[0015] Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply and the second power supply corresponding to the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operating consumption of the base station is minimized; wherein, the expenditure is determined according to the first power supply and the municipal electricity price, and the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output, and the green electricity grid-connected electricity price.

[0016] In some embodiments, the step of inputting the power generation amount and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with the minimum operation consumption of the base station includes:

[0017] Configure a first power supply provided by the city power, a second power supply provided by the green power device, and a third power supply provided by the power storage device, and determine a data combination of the first power supply, the second power supply, and the third power supply that meets the power demand based on the constraint conditions of the linear programming problem model; wherein the second power supply is determined according to the green power output amount of the green power device to the base station and the green power supply efficiency factor, and the third power supply is determined according to the storage power output amount of the power storage device to the base station and the charging and discharging efficiency factor;

[0018] Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply, the second power supply and the third power supply of the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operation consumption of the base station is minimized; wherein, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage equipment, the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output and the green electricity grid-connected electricity price, and the discharge depreciation expenditure of the power storage equipment is determined according to the storage output and the unit depreciation price of charging and discharging.

[0019] In some embodiments, the step of inputting the power generation amount and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with the minimum operation consumption of the base station includes:

[0020] Configure the first power supply provided by the city power, the second power supply provided by the green power device, and the third power supply provided by the power storage device; configure the first power storage provided by the city power and the second power storage provided by the green power device; determine the data combination of the first power supply, the second power supply, the third power supply, the first power storage, and the second power storage that meet the power demand and satisfy the predicted power storage device The storage capacity is less than or equal to the maximum power storage capacity based on the constraint conditions of the linear programming problem model, wherein the second power supply is determined according to the green power output of the green power device to the base station and the green power supply efficiency factor, the third power supply is determined according to the power storage output of the power storage device to the base station and the charging and discharging efficiency factor, the predicted power storage is determined according to the current power storage capacity, the first power storage capacity, the second power storage capacity, and the third power supply of the power storage device, the first power storage capacity is determined according to the output power storage capacity of the city power to the power storage device and the city power storage efficiency factor, and the second power storage capacity is determined according to the output power storage capacity of the green power device to the power storage device and the green power storage efficiency factor;

[0021] Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply, the second power supply and the third power supply of the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operation consumption of the base station is minimized; wherein, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage equipment, the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output and the green electricity grid-connected electricity price, and the discharge depreciation expenditure of the power storage equipment is determined according to the storage output and the unit depreciation price of charging and discharging.

[0022] In some embodiments, the step of predicting the power demand of the base station in at least one future cycle and predicting the power generation of the green power equipment deployed on the base station in at least one future cycle includes:

[0023] Predicting the power demand of the base station in at least one future period based on the historical power consumption of the base station and a time series algorithm;

[0024] The power generation in at least one future cycle is predicted according to the historical power generation of the green power equipment deployed on the base station, the historical environmental parameters of the green power equipment, and the predicted environmental parameters in at least one future cycle.

[0025] In some embodiments, the step of determining, based on the power generation and the power supply parameters of the power supply source, a power supply allocation strategy for minimizing the operation consumption of the base station when the power demand is met includes:

[0026] When the power demand is the total power demand of multiple cycles, the power supply allocation strategy for each cycle with the minimum operating consumption of the base station is determined based on the power generation and the power supply parameters of the power supply source while meeting the total power demand of multiple cycles.

[0027] On the other hand, the present application also provides a power distribution device for a base station, comprising:

[0028] A prediction module is used to predict the power demand of the base station in at least one cycle in the future, and the power generation of the green power equipment deployed in the base station in at least one cycle in the future;

[0029] A power supply allocation processing module, used to determine, based on the power generation amount and the power supply parameters of the power supply source, a power supply allocation strategy that minimizes the operation consumption of the base station while meeting the power demand;

[0030] A power distribution module is used to distribute the power supply of each of the power supply sources according to the power distribution strategy.

[0031] On the other hand, the present application also provides a power distribution device for a base station, comprising:

[0032] processor;

[0033] A storage device stores a program thereon, and when the program is executed by the processor, the processor implements the power supply distribution method for the base station as described above.

[0034] On the other hand, the present application further provides a computer-readable storage medium storing a computer processing program, wherein the computer processing program is called by a processor to execute the power supply distribution method of the base station as described above.

[0035] Compared with the prior art, the embodiments of the present application have the following effects:

[0036] In an embodiment of the present application, by predicting the power demand of the base station in at least one cycle in the future and the power generation of the green power equipment deployed at the base station in at least one cycle in the future, and then combining the power supply parameters of each power supply source, a power supply allocation strategy for the base station in each cycle is configured for each power supply source, and the power supply allocation strategy minimizes the energy cost of the base station. In this way, when the power supply of each power supply source to the base station is allocated according to the power supply allocation strategy, the energy cost of the base station can be reduced, thereby reducing the operating consumption of the base station.

[0037] In addition, if the utility electricity price fluctuates, the present embodiment adjusts the power supply distribution of the base station periodically, and the power supply distribution strategy can be changed as the utility electricity price fluctuates, thereby reducing the energy cost of the base station. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0039] Figure 1 This is a flow chart of a first embodiment of a power distribution method for a base station of the present application;

[0040] Figure 2 This is another implementation flowchart of S130 of the first embodiment of the power distribution method for a base station of the present application;

[0041] Figure 3 This is a flow chart of a second embodiment of a power distribution method for a base station of the present application;

[0042] Figure 4 It is a schematic diagram of the framework of the power distribution device of the base station of the present application.

[0043] The realization of the purpose, functional features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. The above-mentioned drawings have shown clear embodiments of this application, which will be described in more detail later. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0044] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0045] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0046] It should be understood that, although the terms first, second, third, etc. may be used to describe various information in this article, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this article, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination". Furthermore, as used in this article, the singular forms "one", "one" and "the" are intended to also include plural forms, unless there is an opposite indication in the context. It should be further understood that the terms "comprising" and "including" indicate that there are the described features, steps, operations, elements, components, projects, kinds, and / or groups, but do not exclude the existence, occurrence or addition of one or more other features, steps, operations, elements, components, projects, kinds, and / or groups. The terms "or", "and / or", "including at least one of the following" etc. used in this application can be interpreted as inclusive, or mean any one or any combination. For example, “comprising at least one of the following: A, B, C” means “any of the following: A; B; C; A and B; A and C; B and C; A and B and C”, and for another example, “A, B or C” or “A, B and / or C” means “any of the following: A; B; C; A and B; A and C; B and C; A and B and C”. An exception to this definition will only occur when a combination of elements, functions, steps or operations are inherently mutually exclusive in some manner.

[0047] It should be understood that, although the various steps in the flowchart in the embodiment of the present application are displayed in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and it can be performed in other orders. Moreover, at least a portion of the steps in the figure may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and their execution order is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0048] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0049] It should be noted that, in this article, step codes such as S110, S120, etc. are used for the purpose of expressing the corresponding content more clearly and concisely, and do not constitute a substantial limitation on the sequence. When implementing the step codes, those skilled in the art may execute S120 first and then S110, etc., but these should all be within the scope of protection of this application.

[0050] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0052] With the introduction of more spectrum and larger bandwidth, the energy cost of mobile base stations is increasing. At the same time, with the advancement of smart grids, the introduction of renewable energy, and the application of local power storage equipment in base stations, mobile base stations can use city power, green power and storage power for flexible power supply.

[0053] At present, the mains, green power or storage power supply to the base station is usually provided according to the pre-allocated power supply time or power supply amount. For example, the mains supply is x hours, the green power supply is y hours, and the storage power supply is z hours; or the mains supply is X kilowatts, the green power supply is Y kilowatts, and the storage power supply is Z kilowatts. However, the mains price and the amount of green power generated will vary based on time or environment. If the mains, green power and storage power supply are provided according to a fixed allocation method, it may lead to higher energy costs for mobile base stations, resulting in excessively high operating costs for mobile base stations.

[0054] That is, the current base station lacks a method or device for finding an optimal power strategy that can minimize its energy costs, that is, after comprehensively considering factors such as the base station's real-time power demand, real-time city electricity prices, real-time renewable energy generation, and real-time storage capacity, it decides how much city electricity, green electricity, and battery power are currently used for base station power supply, and how much city electricity and green electricity are currently used for battery charging. It can be understood that green electricity refers to electricity generated by renewable energy, which includes but is not limited to solar energy, wind power, biomass energy, geothermal energy, etc.

[0055] In this regard, the present application provides a power supply allocation method for a base station, which combines the prediction of the base station's power consumption and green electricity generation, and configures the base station's power supply allocation strategy according to the power supply parameters of the power supply source, such as electricity price and other information, so that when the base station allocates the power of the power supply source based on the power supply allocation strategy, the operating consumption of the base station is minimized, so as to reduce the energy cost of the base station. In the embodiment of the present application, the operating consumption of the base station refers to the cost during the operation of the base station, including electricity costs and equipment depreciation costs.

[0056] The following describes the implementation of power distribution for base stations in different application scenarios.

[0057] Please refer to Figure 1 , Figure 1 An embodiment of a power distribution method for a base station provided by the present application is shown. In this embodiment, the power distribution method for a base station includes:

[0058] Step S110, obtaining power supply parameters of the power supply of the base station.

[0059] This embodiment is applied to a power supply distribution device of a base station, and is used to control power supply distribution from various power supply sources to the base station.

[0060] In different application scenarios, the power supply distribution control of the base station is different, so the requirements for the power supply parameters of the power supply source are different.

[0061] For example, in one application scenario, the power supply source of the base station includes the mains power and the green power equipment. That is, the base station is powered by the mains power and the green power equipment. In this application scenario, the power supply parameters of the power supply source obtained correspond to the power supply parameters of the mains power and the power supply parameters of the green power equipment. Optionally, the power supply parameters of the mains power include the mains power price, and the power supply parameters of the green power equipment include the green power supply efficiency factor and the green power grid access price.

[0062] Optionally, the mains electricity price refers to the unit price of electricity used by the base station when the base station uses power from the power grid. The mains electricity price can be fixed or time-varying. The mains electricity price is obtained regularly in the manner of the embodiment of the present application, and then the power supply allocation method with the lowest cost of the base station is calculated in combination with the power supply parameters of the green power equipment. The power supply allocation strategy can be changed regularly according to the changes in the mains electricity price, and the optimal power supply method can be selected to achieve the purpose of saving costs. Optionally, the mains electricity price is usually a value greater than 0, and the mains electricity price can be obtained from the power grid through a specific interface.

[0063] Optionally, the green electricity grid-connected price refers to the unit price that can be charged from the power grid company when the electricity generated by the renewable energy equipment (i.e., green electricity equipment, such as solar energy or wind energy, etc.) deployed by the base station is connected to the power grid. The green electricity grid-connected price can be fixed or time-varying, and is usually a value greater than or equal to 0, which is determined according to the power grid agreement. Optionally, the information of the green electricity grid-connected price can be obtained from the power grid through a specific interface.

[0064] Optionally, the green electricity supply efficiency factor refers to the ratio of the actual power supply converted to the base station when green electricity supplies power to the base station to the output power supply of the green electricity device to the base station. When the green electricity device supplies power to the base station, there are usually some losses, such as additional power losses caused by AC / DC conversion and green electricity control units. Therefore, the green electricity power supply conversion rate is less than 100%. Based on this, when green electricity is used for power supply, the actual power supply obtained by the base station is used to allocate the power supply to avoid insufficient power supply to the base station or to avoid non-optimal power supply allocation. Optionally, the green electricity power supply efficiency factor is determined by renewable energy equipment, and different renewable energy equipment has different corresponding green electricity power supply efficiency factors.

[0065] For example, in another application scenario, the power supply source includes AC power, green power equipment and power storage equipment, that is, the base station is powered by AC power, green power equipment and power storage equipment of the base station. In this application scenario, the power supply parameters of the power supply source obtained correspond to the power supply parameters of the AC power, the power supply parameters of the green power equipment and the power supply parameters of the power storage equipment. Optionally, the power supply parameters of the AC power include the AC power price, the power supply parameters of the green power equipment include the green power supply efficiency factor and the green power grid access price, and the power supply parameters of the power storage equipment include the charging and discharging efficiency factor and the charging and discharging unit loss price.

[0066] Optionally, the city electricity price, green electricity grid-connected electricity price, and green electricity supply efficiency factor are the same as those in the above application scenarios, and their acquisition methods are also the same as those in the above application scenarios, which will not be repeated here.

[0067] In this embodiment, the power supply source also includes a power storage device deployed on the base station, that is, the base station is powered by at least three power supplies. In this case, in addition to considering the city electricity price and the green electricity grid price, it is also necessary to consider the depreciation of the power storage device, and then determine the power distribution method with the lowest cost.

[0068] Optionally, the unit depreciation price of charge and discharge refers to the total price of the energy storage device and information such as the number of charge and discharge times and capacity. Energy storage devices usually support a limited number of charge and discharge, so the charge and discharge of energy storage devices are accompanied by losses. These damages can be converted into a unit depreciation price of charge and discharge based on the limited number of charge and discharge times, that is, the unit depreciation price of charge and discharge refers to the depreciation cost of the unit discharge of the energy storage device. When calculating the power supply distribution, the depreciation cost of the energy storage device is combined, and consideration is given to whether the energy storage device is used for power supply, or the power supply or power supply duration of the energy storage device is considered to determine the optimal power supply distribution method. The unit depreciation price of charge and discharge is configured as a fixed value greater than 0.

[0069] The charge and discharge efficiency factor refers to the efficiency of the power storage device in providing power to the base station. When the storage battery supplies power to the base station, there will be some loss. Excluding the loss, the charge and discharge efficiency factor of the power storage device is obtained. The charge and discharge efficiency factor can be configured as a fixed value between 0 and 1. The charge and discharge efficiency factor is determined based on the power storage device, and different power storage devices have different corresponding charge and discharge efficiency factors.

[0070] For example, in another application scenario, the power supply includes AC power, green power equipment and power storage equipment, that is, the base station is powered by AC power, green power equipment and the power storage equipment of the base station. At the same time, the power storage equipment is also stored according to the needs of the power storage equipment. In this application scenario, the power supply parameters obtained correspond to the power supply parameters of the AC power, the power supply parameters of the green power equipment and the power supply parameters of the power storage equipment. Optionally, the power supply parameters of the AC power include the AC power price and the AC power storage efficiency factor, the power supply parameters of the green power equipment include the green power supply efficiency factor, the green power grid price and the green power storage efficiency factor, and the power supply parameters of the power storage equipment include the charging and discharging efficiency factor and the charging and discharging unit loss price.

[0071] Optionally, the city electricity price, green electricity grid-connected electricity price, green electricity supply efficiency factor, charging and discharging unit loss price and charging and discharging efficiency factor are the same as those in the above application scenarios, and the acquisition method is also the same as that in the above application scenarios, which will not be repeated here.

[0072] In this embodiment, the power supply source also includes a power storage device deployed on the base station, that is, the base station is powered by at least three power supplies. In this case, while considering the city electricity price, the green electricity price, the depreciation of the power storage device, the power storage situation of the power storage device is also considered, and then the power supply allocation method with the lowest cost and the best power storage is determined.

[0073] Optionally, when necessary, the city power and green power equipment also need to store electricity in the power storage device. Storing electricity in the power storage device at an appropriate time can also save electricity storage costs.

[0074] When considering electricity storage, it is necessary to combine the mains electricity storage efficiency factor and the green electricity storage efficiency factor, and comprehensively consider the power supply parameters that affect power supply distribution, so as to make the power supply distribution more reasonable and optimized.

[0075] Optionally, the mains power storage efficiency factor refers to the charging efficiency when the mains charges the power storage device. Since the efficiency of the mains charging the power storage device will not reach 100%, there will be some losses. When calculating the power distribution strategy combined with the power storage strategy, considering the mains power storage efficiency factor can make the power distribution strategy more optimized. Optionally, the mains power storage efficiency factor can be a fixed value between 0 and 1, or it can be a variable value. For example, as the number of charge and discharge times of the power storage device increases, the corresponding mains power storage efficiency factor becomes smaller. The mains power storage efficiency factor is determined according to the power storage device.

[0076] The green power storage efficiency factor is also based on the additional loss when the power storage device is charged, and is set based on the loss. Optionally, the green power storage efficiency factor may be different from or the same as the mains power storage efficiency factor. In some applications, the green power storage efficiency factor is less than or equal to the mains power storage efficiency factor.

[0077] This embodiment is based on different application scenarios and obtains power supply parameters of different power supply sources according to requirements.

[0078] Step S120, predicting the power demand of the base station in at least one future cycle, and predicting the power generation of the green power equipment deployed in the base station in at least one future cycle;

[0079] This embodiment configures the future power distribution of the base station by predicting the future power consumption of the base station and the future power generation of the green power equipment, and combining the power supply of the mains power and green power, so as to achieve the minimum operation consumption according to the power distribution.

[0080] Optionally, the power demand of the base station in at least one future cycle refers to the power demand of all base stations within a preset range in at least one future cycle. In this embodiment, the power demand can be predicted based on the historical power consumption of the base station to improve the accuracy of the power demand. For example, based on the recorded historical power consumption (actual power consumption), a time series algorithm is used for prediction. Optionally, the time series algorithm includes but is not limited to LSTM (Long Short-Term Memory) and Prophet prediction algorithms.

[0081] Optionally, the historical power consumption may be the power consumption corresponding to at least one recent historical period of the base station, or may be the power consumption of a historical period corresponding to a time period of at least one future period.

[0082] Optionally, the power generation of the green power device in at least one future cycle refers to the power generation of all green power devices of the corresponding number of steps of all base stations within a preset range in at least one future cycle. In this embodiment, the power generation can also be calculated based on the actual power generation of the green power device in the historical cycle. Alternatively, the power generation in at least one future cycle is predicted based on the historical power generation of the green power devices deployed on the base station, the historical environmental parameters of the green power devices, and the predicted environmental parameters in at least one future cycle. Since the power generation of green power devices changes according to environmental changes, the power generation corresponding to different environments is different. In this embodiment, the power generation is predicted in combination with the predicted environmental parameters in at least one future cycle to improve the accuracy of the power generation. Optionally, the environmental parameters include climate, humidity, temperature, time, weather forecast, etc.

[0083] Step S130, determining a power supply allocation strategy that minimizes the operation consumption of the base station while satisfying the power demand according to the power generation and the power supply parameters of the power supply source;

[0084] Based on the predicted power generation of green power equipment, it is possible to determine the amount of power that green power equipment can provide to the base station in at least one cycle in the future, or the amount of power that green power equipment can be incorporated into the power grid. In this way, it is possible to determine how to allocate the power supply of each power supply source while meeting the power demand, so that the operation consumption of the base station is minimized. If the income of green power such as the power grid is higher (higher than the price of city electricity), the city power supply can be allocated to be greater than the green power supply, and the green power income can be used for city power consumption, which can reduce the total cost of the base station. Alternatively, when the city power price is low, the city power is used to supply power to the base station while storing power in the power storage device. When the city power price is high, the green power is used to supply power to the base station while storing power in the power storage device. Alternatively, when the city power price is high and the green power access price is also high, the power storage device can be used to supply power to the base station to reduce the power supply of the city power and green power.

[0085] It should be noted that the embodiment of the present invention provides a method for determining a power supply allocation strategy. The power supply allocation strategy determined based on the method can always minimize the consumption of base station operation (minimize the expenditure). Even if the electricity price changes, the method for determining the power supply allocation strategy provided by this embodiment can also derive the optimal power supply allocation strategy (optimal means that the base station operation consumption is minimized and the base station operation cost is the lowest).

[0086] Optionally, this embodiment adopts a linear programming problem to obtain a power supply allocation strategy. Figure 2 As shown, the step of determining, based on the power generation amount and the power supply parameters of the power supply source, a power supply allocation strategy with the minimum operation consumption of the base station when the power demand is met includes:

[0087] Step S131, inputting the power generation, the power demand and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with minimum operation consumption of the base station;

[0088] According to the output requirements of the power supply allocation strategy, the constraints and objective function of the linear programming problem model are configured in advance. The constraints are used to constrain the relationship between the input parameters, and the set of all points that meet all the constraints is determined based on the objective function. The optimal solution is the minimum value of the objective function, that is, the minimum value that minimizes the operation consumption of the base station.

[0089] Optionally, the power supply allocation strategy with the minimum operation consumption of the base station can also be obtained by other means. For example, after determining the power generation, power demand, and power supply parameters of the power supply source, a limited set of data combinations are calculated, the power consumption of the base station in each data combination is compared, and the minimum value is taken to determine the power supply allocation strategy. Alternatively, other methods can be used, which are not listed here one by one.

[0090] Optionally, in different application scenarios, the power supply allocation strategy obtained by solving the linear programming problem model may be different. The following describes the method of obtaining the optimal solution of the power supply allocation strategy for each scenario.

[0091] For example, in one application scenario, the base station is powered by a mains supply and a green power device. In this application scenario, the power supply parameters of the power supply source correspond to the power supply parameters of the mains supply and the power supply parameters of the green power device. Optionally, the power supply parameters of the mains supply include the mains power price, and the power supply parameters of the green power device include the green power supply efficiency factor and the green power grid access price.

[0092] In this application scenario, the constraints of the linear programming problem model need to consider the electricity demand, green electricity generation, city electricity supply and green electricity supply.

[0093] Optionally, the step of obtaining a power supply allocation strategy with minimum operation consumption of the base station by solving the linear programming problem model includes:

[0094] The first power supply is provided by the mains and the second power supply is provided by the green power equipment, and a data combination corresponding to the first power supply and the second power supply that meets the power demand is determined based on the constraint conditions of the linear programming problem model; wherein the second power supply is determined according to the green power output amount of the green power equipment to the base station and the green power supply efficiency factor;

[0095] Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid access income in the minimum data combination is solved, and the first power supply and the second power supply corresponding to the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operating consumption of the base station is minimized.

[0096] Optionally, the sum of the first power supply and the second power supply is equal to the power demand as a constraint condition of the linear programming problem model. The difference between the expenditure and the green electricity access income is the objective function. The data combination that meets the constraint conditions is the specific values ​​of the first power supply and the second power supply, and then they are respectively brought into the objective function to calculate the minimum difference. The data group corresponding to the minimum difference includes the first power supply and the second power supply, which are configured as the power supply allocation amount of the power supply source of the power supply allocation strategy.

[0097] Optionally, in this embodiment, the expenditure includes the city electricity consumption, the expenditure is determined according to the first power supply amount and the city electricity price, and the green electricity access income is determined according to the green electricity access price and the access electricity amount, wherein the access electricity amount is the difference between the power generation of the green electricity equipment and the green electricity output electricity. In this embodiment, when calculating the operation consumption of the base station, the green electricity supply efficiency factor is also considered. By combining the loss and the expenditure, the minimum value of the total expenditure is calculated, so that the calculation accuracy of the base station operation consumption is more accurate, thereby optimizing the operation consumption of the base station.

[0098] Take an example to illustrate the principle of solving the optimal solution of the objective function. When the green electricity grid-connected electricity price is higher than the city electricity price, part of the green electricity can be incorporated into the grid to offset part of the city electricity cost to obtain the lowest consumption (lowest electricity cost). If the green electricity grid-connected electricity price is lower than the city electricity price, most of the green electricity can be used to supply power to the base station. If the difference between the green electricity grid-connected electricity price and the city electricity price is small, the city power supply and green electricity power supply can be determined based on actual calculations to obtain the lowest electricity cost. Specifically, the power supply corresponding to the city electricity, green electricity equipment and power storage equipment is determined according to the optimized value of the objective function to form the power supply allocation strategy.

[0099] For example, in another application scenario, the base station is powered by the mains, green power equipment and the power storage equipment of the base station. In this application scenario, the power supply parameters of the power supply source correspond to the power supply parameters of the mains, the power supply parameters of the green power equipment and the power supply parameters of the power storage equipment. Optionally, the power supply parameters of the mains include the mains electricity price, the power supply parameters of the green power equipment include the green power supply efficiency factor and the green power grid access price, and the power supply parameters of the power storage equipment include the charging and discharging efficiency factor and the charging and discharging unit loss price.

[0100] In this application scenario, the constraints of the linear programming problem model take into account the electricity demand, green electricity generation, city power supply, green electricity supply and power supply of power storage equipment.

[0101] The step of obtaining the power supply allocation strategy with the minimum operation consumption of the base station by solving the linear programming problem model comprises:

[0102] Configuring a first power supply provided by the city power, a second power supply provided by the green power device, and a third power supply provided by the power storage device, and determining a data combination of the first power supply, the second power supply, and the third power supply that meets the power demand based on the constraint conditions of the linear programming problem model;

[0103] Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply, the second power supply and the third power supply of the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operation consumption of the base station is minimized; wherein, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage equipment, the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output and the green electricity grid-connected electricity price, and the discharge depreciation expenditure of the power storage equipment is determined according to the storage output and the unit depreciation price of charging and discharging.

[0104] The sum of the first power supply, the second power supply and the third power supply is equal to the power demand, which is a constraint condition of the linear programming problem model. The difference between the expenditure and the green electricity grid access income is the objective function. In this embodiment, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage device, that is, when the power is supplied by the power storage device, the converted consumption of the charging and discharging of the power storage device is considered in this embodiment to improve the accuracy of the expenditure. The data combination that meets the constraint conditions includes the specific values ​​of the first power supply, the second power supply and the third power supply, and then they are respectively brought into the objective function to calculate the minimum difference. The data group corresponding to the minimum difference includes the first power supply and the second power supply, which are configured as the power supply distribution amount of the power supply source of the power supply distribution strategy.

[0105] Optionally, the second power supply is determined according to the green power output of the green power device to the base station and the green power supply efficiency factor, and the third power supply is determined according to the power storage output of the power storage device to the base station and the charge and discharge efficiency factor; the city power consumption expenditure is determined according to the first power supply and the city power price, and the green power access income is determined according to the green power access price and the access power, wherein the access power is the difference between the power generation of the green power device and the green power output. The power storage device discharge depreciation expenditure is determined according to the power storage output of the power storage device and the charge and discharge unit depreciation price. When calculating the operating consumption of the base station, this embodiment also considers the green power supply efficiency factor and the charge and discharge efficiency factor of the power storage device. By combining the green power supply loss, the power storage device power supply loss and the expenditure, the minimum value of the total expenditure is calculated, so that the calculation accuracy of the base station operating consumption is more accurate, and the operating consumption of the base station is more optimized.

[0106] Take an example to illustrate the principle of solving the optimal solution of the objective function. For example, when the green electricity grid-connected price is higher than the mains electricity price, part of the green electricity can be incorporated into the grid to offset part of the mains electricity cost, so as to obtain the minimum consumption of the base station (minimum electricity cost). If the green electricity grid-connected price is lower than the mains electricity price, green electricity equipment and power storage equipment can be used to supply power to the base station. If the green electricity grid-connected price is low, and the mains electricity price is high, the power storage equipment can be mainly used to supply power to the base station, and green electricity and mains electricity can be used as auxiliary power supplies to obtain the lowest electricity cost. Specifically, the power supply corresponding to the mains electricity, green electricity equipment and power storage equipment is determined according to the optimized value of the objective function to form the power supply allocation strategy.

[0107] For example, in another application scenario, the base station is powered by the city power, green power equipment and the power storage equipment of the base station. At the same time, the power storage equipment is also powered according to the needs of the power storage equipment. In this application scenario, the power supply parameters correspond to the power supply parameters of the city power, the power supply parameters of the green power equipment and the power supply parameters of the power storage equipment. Optionally, the power supply parameters of the city power include the city power price and the city power storage efficiency factor, the power supply parameters of the green power equipment include the green power supply efficiency factor, the green power grid price and the green power storage efficiency factor, and the power supply parameters of the power storage equipment include the charging and discharging efficiency factor and the charging and discharging unit loss price.

[0108] In this application scenario, the constraints of the linear programming problem model take into account electricity demand, green electricity generation, city power supply, green electricity supply, power supply of power storage equipment, and storage capacity.

[0109] The step of obtaining the power supply allocation strategy with the minimum operation consumption of the base station by solving the linear programming problem model comprises:

[0110] Configure the first power supply provided by the city power, the second power supply provided by the green power device, and the third power supply provided by the power storage device; configure the first power storage provided by the city power and the second power storage provided by the green power device; determine the data combination of the first power supply, the second power supply, the third power supply, the first power storage, and the second power storage that meet the power demand and satisfy the predicted power storage device The storage capacity is less than or equal to the maximum power storage capacity based on the constraint conditions of the linear programming problem model, wherein the second power supply is determined according to the green power output of the green power device to the base station and the green power supply efficiency factor, the third power supply is determined according to the power storage output of the power storage device to the base station and the charging and discharging efficiency factor, the predicted power storage is determined according to the current power storage capacity, the first power storage capacity, the second power storage capacity, and the third power supply of the power storage device, the first power storage capacity is determined according to the output power storage capacity of the city power to the power storage device and the city power storage efficiency factor, and the second power storage capacity is determined according to the output power storage capacity of the green power device to the power storage device and the green power storage efficiency factor;

[0111] Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply, the second power supply and the third power supply of the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operation consumption of the base station is minimized; wherein, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage equipment, the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output and the green electricity grid-connected electricity price, and the discharge depreciation expenditure of the power storage equipment is determined according to the storage output and the unit depreciation price of charging and discharging.

[0112] The sum of the first power supply, the second power supply and the third power supply is equal to the power demand as the first constraint of the linear programming problem model, and the predicted power storage of the power storage device is less than or equal to the maximum power storage of the power storage device as the second constraint of the linear programming problem model. The difference between the expenditure and the green power access income is the objective function. Among them, the predicted power storage refers to the amount of power that the power storage device will store when the power storage device is charged based on the city power and green power and the power storage device supplies power to the base station in at least one cycle in the future. The predicted power storage is equal to the difference between the sum of the current power storage, the first power storage and the second power storage and the third power supply. In this embodiment, it is limited that the predicted storage power cannot be greater than the maximum power storage of the power storage device. When the predicted power storage is equal to the maximum power storage, the power storage device cannot be charged. At this time, the city power and green power need to stop charging the power storage device, otherwise it will cause energy waste. Therefore, this embodiment combines the second constraint to determine the data combination. The expenditure includes the city power consumption expenditure and the power storage device discharge depreciation expenditure, that is, this embodiment considers the charging and discharging expenditure of the power storage device when combining the power storage device with the power supply.

[0113] The data combination that meets the constraint conditions is the specific values ​​of the first power supply, the second power supply, the third power supply, the first storage capacity and the second storage capacity. Then the first power supply, the second power supply and the third power supply are respectively substituted into the objective function to calculate the minimum difference. The data group corresponding to the minimum difference includes the first power supply, the second power supply, the third power supply, the first storage capacity and the second storage capacity, which are configured as the power supply distribution amount of the power supply source and the storage distribution amount of the power storage device of the power supply distribution strategy.

[0114] When using the city electricity to charge the energy storage device, it is necessary to pay electricity fees to the power grid, so based on the optimal operating consumption (minimum cost), it is also necessary to combine the charging situation of the energy storage device to find the lowest value of electricity cost. That is, when using energy storage devices for power supply, it is also necessary to calculate how to charge the energy storage device (for subsequent power supply), reserve a certain amount of electricity for the energy storage device, and optimize the cost of the base station (lowest operating consumption).

[0115] Optionally, the second power supply refers to the actual power supply provided by the green power received by the base station, which is determined according to the output power of the green power device and the green power supply efficiency factor. The third power supply refers to the actual power supply provided by the power storage device received by the base station, which is determined according to the output power of the power storage device and the charging and discharging efficiency factor.

[0116] The first storage capacity refers to the actual charging amount of the AC power to the power storage device, which is determined based on the output capacity of the AC power to the power storage device and the AC power storage efficiency factor. The second storage capacity refers to the actual charging amount of the green power device to the power storage device, which is determined based on the output capacity of the green power device to the power storage device and the green power storage efficiency factor.

[0117] The linear programming problem model in this embodiment is explained below in combination with specific formulas (taking the power supply allocation strategy determination method for the next cycle as an example):

[0118] In this embodiment, the objective function of the linear programming problem model is:

[0119]

[0120] The constraints of the linear programming problem model include:

[0121] D=U m +α g U g +α s U s ;

[0122] 0≤S+β m S m +β g S g -U s ≤S max;

[0123] U m ≥0, U g ≥0, U s ≥0, S m ≥0, S g ≥0;

[0124] Among them, P m is the electricity price in the next cycle; P g is the green power grid access price in the next cycle; P s It is the unit depreciation price of charging and discharging, and the unit is ￥ / kWh.

[0125] α g is the green electricity supply efficiency factor; α s is the charge and discharge efficiency factor.

[0126] β m is the utility power storage efficiency factor; β g is the green electricity storage efficiency factor.

[0127] S is the current storage capacity of the power storage device; D is the predicted power demand of the base station in the next cycle; G is the power generation of the green power device in at least one cycle in the future.

[0128] U m U is the amount of electricity delivered by the city power supply to the base station in the next cycle (i.e., the first power supply); g is the amount of green power output from the green power equipment to the base station in the next cycle (U g α g is the second power supply); U s is the amount of electricity output from the energy storage device to the base station in the next cycle (U s α s is the third power supply), and the unit is kWh.

[0129] S m The amount of electricity stored in the power storage device during a cycle (S m β m is the first storage capacity); S g is the amount of storage capacity (S) output by the green power device to the power storage device in one cycle g β g is the second power storage capacity), the unit is kWh.

[0130] (GU g -S g ) is the amount of green electricity connected to the grid in one cycle. The amount of green electricity connected to the grid can be 0 or a value greater than 0, and the unit is kWh.

[0131] S max The maximum storage capacity of the energy storage device is restricted to avoid ineffective charging of the energy storage device by the mains and green power equipment.

[0132] By constraining U m , S m , U g , U s , S g The above constraints are met, and then the minimum value of the objective function is taken from the numerical group that meets the above constraints, so that the power consumption allocation and power storage allocation with minimum operating consumption are obtained. The power consumption allocation and power storage allocation form the power supply allocation strategy.

[0133] Step S140: Allocate power to each of the power sources according to the power distribution strategy.

[0134] After the power supply allocation strategy is determined, the power supply amount of each power supply source to the base station is controlled according to the power supply allocation strategy. The allocation strategy includes the power supply amount, or the power supply amount and power supply time, of each power supply source to the base station in at least one future cycle, and the amount of electricity stored in the power storage device using the mains power and green power equipment.

[0135] Optionally, in this embodiment, a cycle can be one hour, or 30 minutes, or other durations. That is, after determining the power supply allocation strategy for the next cycle, control each power supply source to supply power to the base station according to the power supply allocation strategy, and then repeat the steps of this embodiment to recalculate the power supply allocation strategy for the next cycle.

[0136] In this embodiment, by predicting the power demand of the base station in at least one future cycle and the power generation of the green power equipment deployed at the base station in at least one future cycle, and then combining the power supply parameters of each power supply source, a power supply allocation strategy for the base station in each cycle is configured for each power supply source, and the power supply allocation strategy minimizes the energy cost of the base station. In this way, when the power supply of each power supply source to the base station is allocated according to the power supply allocation strategy, the energy cost of the base station can be reduced, thereby reducing the operating cost of the base station.

[0137] If the utility electricity price fluctuates, this embodiment adjusts the power supply distribution of the base station periodically, and can change the power supply distribution strategy as the utility electricity price fluctuates, so that the energy cost of the base station is lower.

[0138] Furthermore, the power supply allocation strategy of this embodiment takes into account various costs of the power supply source and the cost of green power access to the grid, so that the solved electricity cost is more accurate.

[0139] Please refer to Figure 3 , Figure 3Another embodiment of the power supply allocation method for a base station provided by the present application is shown. Compared with the above embodiment, this embodiment is based on a one-time determination of the power supply allocation strategy for multiple cycles, while the above embodiment is based on a single cycle to determine the power supply allocation strategy. In this embodiment, the power supply allocation method for a base station includes:

[0140] Step S210: obtaining power supply parameters of a power supply of the base station.

[0141] In this embodiment, the applicable scenario of the power supply distribution method of the base station is the same as that of the above embodiment, so the power supply parameters obtained are also different based on different application scenarios, which is the same as the above embodiment. Please refer to step S110 of the above embodiment and will not be repeated here.

[0142] Step S220, predicting the power demand of the base station in multiple future cycles, and predicting the power generation of the green power equipment deployed in the base station in multiple future cycles;

[0143] The power demand in this embodiment refers to the total power demand of the base station in multiple periods, and the power generation is also the power generation of the green power equipment deployed in the base station in multiple periods.

[0144] In this embodiment, the power demand is determined according to the sum of the power demand in each cycle, and the power generation is also determined according to the sum of the power generation in each cycle. The prediction method of the power demand and the power generation in this embodiment is the same as that in the above embodiment, and the details can be referred to step S120 in the above embodiment, which will not be repeated here.

[0145] Step S230, determining, based on the power generation and the power supply parameters of the power supply source, a power supply allocation strategy for each cycle in which the operation consumption of the base station is minimized while satisfying the total power demand of multiple cycles;

[0146] When the power demand is the total power demand of multiple periods, this embodiment solves the power supply allocation strategy with the lowest total power cost of base stations in multiple periods based on the power generation, power demand and power supply parameters of the power supply source in combination with a linear programming problem model.

[0147] The application scenario of this embodiment is the same as the various application scenarios in the above embodiments. In each application scenario, the method for obtaining the power supply allocation strategy can refer to the above embodiments. The difference is that in this embodiment, the power supply allocation strategy is obtained for the minimum total operating consumption of multiple cycles, while the above embodiment obtains the power supply allocation strategy based on the minimum operating consumption of one cycle. Relative to the above embodiments, this embodiment predicts the power demand for multiple cycles and can report the demand to the power grid in advance. In this way, the power grid can prepare the power consumption of the base station in advance based on the power demand obtained in advance. Relatively speaking, the city electricity price can change according to the power demand. If the power demand is large and the power grid can know the power demand in advance, it can supply power to the base station at a lower market price, thereby reducing the cost of city electricity supply.

[0148] Optionally, the multiple cycles may be multiple time periods within a day, such as one cycle including but not limited to 15 minutes.

[0149] The following takes a cycle of 15 minutes as an example to illustrate the power distribution strategy of 15-minute granularity within a day. It should be noted that this embodiment also adopts a linear programming problem model to obtain the power distribution strategy.

[0150] In this embodiment, the objective function of the linear programming problem model is:

[0151]

[0152] The constraints of the linear programming problem model include:

[0153]

[0154]

[0155]

[0156] Among them, P m t is the electricity price of the city electricity in multiple cycles in the future; g t is the green power grid access price for multiple cycles in the future; P s t It is the unit discount price of charging and discharging, and the unit is RMB / kWh, with a granularity of 15 minutes. A day includes 96 cycles t. The city electricity price and green electricity grid-connected electricity price of each cycle can be the same or different.

[0157] α g is the green electricity supply efficiency factor; α s is the charge and discharge efficiency factor.

[0158] β m is the utility power storage efficiency factor; βg is the green electricity storage efficiency factor.

[0159] S t-1 is the current storage capacity of the power storage device; D t Predicted power demand of base stations in multiple future cycles; G t The power generation of green power equipment in multiple cycles in the future.

[0160] U m t U is the amount of electricity delivered by the city power supply to the base station in multiple future cycles (i.e., the first power supply); g t is the amount of green power output that the green power equipment will deliver to the base station in multiple cycles in the future (and U g t α g is the second power supply); U s t is the amount of power output that the power storage device will deliver to the base station in multiple cycles in the future (and U s t α s is the third power supply), and the unit is kWh.

[0161] S m t The output storage capacity (S m t β m is the first storage capacity); S g t The output storage capacity (S g t β g is the second power storage capacity), the unit is kWh.

[0162] (G t -U g t -S g t ) is the amount of electricity that green electricity equipment will connect to the grid in multiple cycles in the future. The amount of electricity that green electricity connects to the grid can be 0 or a value greater than 0, and the unit is kWh.

[0163] S max The maximum power of the energy storage device is set to limit the maximum storage capacity to avoid ineffective charging of the energy storage device by the mains and green power equipment.

[0164] In this embodiment, based on the advance prediction of power demand and power generation in multiple future cycles, when configuring the power supply allocation strategy, the minimum total cost is solved based on the total power supply of each power supply source in multiple cycles.

[0165] By constraining U m t , S m t , U g t , U s t , S g t The above constraints are met, and then the minimum value of the objective function is taken from the numerical group that meets the above constraints, so that the power consumption allocation and power storage allocation with minimum operating consumption are obtained. The power consumption allocation and power storage allocation form the power supply allocation strategy.

[0166] Step S140: Allocate power to each of the power sources according to the power distribution strategy.

[0167] After the power supply allocation strategy is determined, the power supply amount of each power supply source to the base station is controlled according to the power supply allocation strategy. The allocation strategy includes the power supply amount, or the power supply amount and power supply time, of each power supply source to the base station in multiple future cycles, and the amount of electricity stored in the power storage device using the mains power and green power equipment.

[0168] The power distribution strategy obtained by adopting this embodiment reduces the electricity cost of the base station and further reduces the operating cost of the mobile base station (for longer-term power forecasts, agreements with the power grid can be reached in advance to obtain lower city electricity prices).

[0169] The above examples are only reference examples. In order to avoid redundancy, they are not listed one by one here. In actual development or application, they can be flexibly combined according to actual needs, but any combination belongs to the technical solution of this application and is covered within the scope of protection of this application.

[0170] The present application also provides a power distribution device for a base station, comprising:

[0171] A prediction module, used to predict the power demand of the base station in at least one cycle in the future, and the power generation of the green power equipment deployed in the base station in at least one cycle in the future;

[0172] A power supply allocation processing module, used to determine, based on the power generation amount and the power supply parameters of the power supply source, a power supply allocation strategy that minimizes the operation consumption of the base station while meeting the power demand;

[0173] A power distribution module is used to distribute the power supply of each of the power supply sources according to the power distribution strategy.

[0174] Optionally, the power supply allocation processing module is configured with a linear programming problem model, and based on power supply parameters and power generation, solves a power supply allocation strategy with minimum operation consumption of the base station when power demand is met.

[0175] The present application also provides a power distribution device for a base station, comprising:

[0176] processor;

[0177] A storage device stores a program thereon, and when the program is executed by the processor, the processor implements the power supply distribution method for the base station as described above.

[0178] Please refer to Figure 4 , Figure 4 A system framework diagram of a power supply distribution device of a base station is shown, wherein the power supply distribution device also includes a linear programming problem model. The power grid, green power equipment and power storage equipment are connected to the power supply distribution device. The power supply distribution device obtains the city power price, green power grid price and power storage efficiency factor from the power grid, obtains the power supply efficiency factor and power storage efficiency factor from the green power equipment, obtains the charging and discharging loss price, power supply efficiency factor and current storage capacity from the power storage equipment, and uses these parameters as well as the predicted power demand and the power generation of the green power equipment as input parameters of the linear programming problem model. The linear programming module solves the minimum power cost based on the input parameters and outputs a power supply distribution strategy.

[0179] The present application also provides a computer-readable storage medium storing a computer processing program, wherein the computer processing program is called by a processor to execute the power supply distribution method of the base station as described above.

[0180] In the embodiments of the communication device and computer-readable storage medium provided in the present application, all technical features of any of the above-mentioned processing method embodiments may be included, and the expanded and explained contents of the specification are basically the same as those of the embodiments of the above-mentioned methods, and will not be repeated here.

[0181] The embodiment of the present application further provides a computer program product, which includes a computer program code. When the computer program code runs on a computer, the computer executes the methods in the above various possible implementation modes.

[0182] It is understood that the above scenarios are only examples and do not constitute a limitation on the application scenarios of the technical solutions provided in the embodiments of the present application. The technical solutions of the present application can also be applied to other scenarios. For example, it is known to those skilled in the art that with the evolution of the system architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0183] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0184] The steps in the method of the embodiment of the present application can be adjusted in order, combined and deleted according to actual needs.

[0185] The units in the device of the embodiment of the present application can be merged, divided and deleted according to actual needs.

[0186] In the present application, the same or similar terminology concepts, technical solutions and / or application scenario descriptions are generally described in detail only the first time they appear. When they appear again later, they are generally not repeated for the sake of brevity. When understanding the technical solutions and other contents of the present application, for the same or similar terminology concepts, technical solutions and / or application scenario descriptions that are not described in detail later, reference can be made to the previous related detailed descriptions.

[0187] In the present application, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0188] The various technical features of the technical solution of the present application can be arbitrarily combined. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present application.

[0189] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, a controlled terminal, or a network device, etc.) to execute the method of each embodiment of the present application.

[0190] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loading and executing computer program instructions on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integrated. The available medium can be a magnetic medium, (e.g., a floppy disk, a storage disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state storage disk Solid State Disk (SSD)), etc.

[0191] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A power supply distribution method for a base station, characterized in that: include: Predicting the electricity demand of the base station in at least one future cycle, and predicting the power generation of the green power equipment deployed on the base station in at least one future cycle; Determine, based on the power generation and the power supply parameters of the power supply source, a power supply allocation strategy that minimizes the power consumption of the base station when the power demand is met; The power supply of each of the power supply sources is allocated according to the power supply allocation strategy.

2. The power distribution method for a base station according to claim 1, characterized in that: The step of determining, based on the power generation amount and the power supply parameters of the power supply source, a power supply allocation strategy for minimizing the operation consumption of the base station when the power demand is met comprises: The power generation, the power demand and the power supply parameters of the power supply source are input into a preset linear programming problem model to obtain a power supply allocation strategy with minimum operation consumption of the base station.

3. The power supply distribution method of a base station according to claim 1, characterized in that: The power supply source includes mains electricity and green electricity equipment, the mains power supply parameters include mains electricity price, and the green electricity equipment power supply parameters include green electricity power supply efficiency factor and green electricity grid access price; Alternatively, the power supply source includes AC power, green power equipment and power storage equipment, the power supply parameters of the AC power include at least one of the AC power price and the AC power storage efficiency factor, the power supply parameters of the green power equipment include at least one of the green power supply efficiency factor, the green power grid-connected power price and the green power storage efficiency factor, and the power supply parameters of the power storage equipment include at least one of the charging and discharging efficiency factor and the charging and discharging unit depreciation price.

4. The power supply distribution method for a base station according to claim 2 or 3, characterized in that: The step of inputting the power generation amount and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with minimum operation consumption of the base station includes: The first power supply is provided by the mains and the second power supply is provided by the green power equipment, and a data combination corresponding to the first power supply and the second power supply that meets the power demand is determined based on the constraint conditions of the linear programming problem model; wherein the second power supply is determined according to the green power output amount of the green power equipment to the base station and the green power supply efficiency factor; Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply and the second power supply corresponding to the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operating consumption of the base station is minimized; wherein, the expenditure is determined according to the first power supply and the municipal electricity price, and the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output, and the green electricity grid-connected electricity price.

5. The power supply distribution method for a base station according to claim 2 or 3, characterized in that: The step of inputting the power generation amount and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with minimum operation consumption of the base station includes: Configure a first power supply provided by the city power, a second power supply provided by the green power device, and a third power supply provided by the power storage device, and determine a data combination of the first power supply, the second power supply, and the third power supply that meets the power demand based on the constraint conditions of the linear programming problem model; wherein the second power supply is determined according to the green power output amount of the green power device to the base station and the green power supply efficiency factor, and the third power supply is determined according to the storage power output amount of the power storage device to the base station and the charging and discharging efficiency factor; Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply, the second power supply and the third power supply of the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operation consumption of the base station is minimized; wherein, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage equipment, the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output and the green electricity grid-connected electricity price, and the discharge depreciation expenditure of the power storage equipment is determined according to the storage output and the unit depreciation price of charging and discharging.

6. The power supply distribution method for a base station according to claim 2 or 3, characterized in that: The step of inputting the power generation amount and the power supply parameters of the power supply source into a preset linear programming problem model to obtain a power supply allocation strategy with minimum operation consumption of the base station includes: Configure the first power supply provided by the city power, the second power supply provided by the green power device, and the third power supply provided by the power storage device; configure the first power storage provided by the city power and the second power storage provided by the green power device; determine the data combination of the first power supply, the second power supply, the third power supply, the first power storage, and the second power storage that meet the power demand and satisfy the predicted power storage device The storage capacity is less than or equal to the maximum power storage capacity based on the constraint conditions of the linear programming problem model, wherein the second power supply is determined according to the green power output of the green power device to the base station and the green power supply efficiency factor, the third power supply is determined according to the power storage output of the power storage device to the base station and the charging and discharging efficiency factor, the predicted power storage is determined according to the current power storage capacity, the first power storage capacity, the second power storage capacity, and the third power supply of the power storage device, the first power storage capacity is determined according to the output power storage capacity of the city power to the power storage device and the city power storage efficiency factor, and the second power storage capacity is determined according to the output power storage capacity of the green power device to the power storage device and the green power storage efficiency factor; Based on the objective function of the linear programming problem model, the difference between the expenditure and the green electricity grid-connected income in the minimum data combination is solved, and the first power supply, the second power supply and the third power supply of the power supply allocation strategy are determined based on the corresponding relationship between the minimum difference and the data combination, so that the operation consumption of the base station is minimized; wherein, the expenditure includes the municipal electricity expenditure and the discharge depreciation expenditure of the power storage equipment, the green electricity grid-connected income is determined according to the difference between the power generation and the green electricity output and the green electricity grid-connected electricity price, and the discharge depreciation expenditure of the power storage equipment is determined according to the storage output and the unit depreciation price of charging and discharging.

7. The power supply distribution method of a base station according to claim 1, characterized in that: The step of predicting the power demand of the base station in at least one future cycle and predicting the power generation of the green power equipment deployed in the base station in at least one future cycle includes: Predicting the power demand of the base station in at least one future period based on the historical power consumption of the base station and a time series algorithm; The power generation in at least one future cycle is predicted according to the historical power generation of the green power equipment deployed on the base station, the historical environmental parameters of the green power equipment, and the predicted environmental parameters in at least one future cycle.

8. The power supply distribution method of a base station according to claim 1, characterized in that: The step of determining, based on the power generation amount and the power supply parameters of the power supply source, a power supply allocation strategy for minimizing the operation consumption of the base station when the power demand is met comprises: When the power demand is the total power demand of multiple cycles, the power supply allocation strategy for each cycle with the minimum operating consumption of the base station is determined based on the power generation and the power supply parameters of the power supply source while meeting the total power demand of multiple cycles.

9. A power supply distribution device for a base station, characterized in that: include: processor; A storage device having a program stored thereon, wherein when the program is executed by the processor, the processor implements the power supply distribution method for the base station as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: A computer processing program is stored, and the computer processing program is called by a processor to execute the power supply distribution method for a base station according to any one of claims 1 to 8.

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