Communication base station energy system, capacity planning method and related equipment

Abstract

The invention provides a communication base station energy system, a capacity planning method and related equipment, and belongs to the technical field of communication infrastructures. The system comprises a direct-current light stacking system, a storage battery pack, a hydrogen fuel cell, a hydrogen storage bottle group, an intelligent combiner box and a switching power supply, wherein the hydrogen storage bottle group is connected with the hydrogen fuel cell and is used for providing hydrogen for the hydrogen fuel cell; the hydrogen fuel cell and the direct current light stacking system are respectively connected with the intelligent combiner box, and the hydrogen fuel cell and the direct current light stacking system supply power to equipment of a communication base station through the intelligent combiner box; the intelligent combiner box and the storage battery pack are merged into a switching power supply together, and the switching power supply is used for controlling the intelligent combiner box and the storage battery pack to supply power to equipment of the communication base station.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of communication infrastructure, and in particular, to a communication base station energy system, a capacity planning method and related devices. Background Art

[0002] In order to support the normal operation of the devices of a communication base station, it is necessary to deploy a communication base station energy system to supply power to the devices of the communication base station. In the related art, the communication base station energy system mainly consists of a photovoltaic panel, a battery pack, a switching power supply, etc., to provide clean energy storage for the devices of the communication base station through optical storage. This structure will affect the operation reliability of the communication base station.

[0003] In the related art, the capacity planning methods for communication base station energy systems are mainly divided into two categories. The first category is the capacity planning method based on rated power, and the second category is the capacity planning method for constructing an optimal energy consumption target. Among them, the capacity planning method based on rated power plans the battery through simple operations according to the energy storage duration and rated power. The capacity planning based on the optimal energy consumption target usually sets the minimization of energy consumption as the objective function and plans and designs the energy storage capacity based on historical load information. The planning accuracy of these capacity planning methods is relatively poor. Summary of the Invention

[0004] The embodiments of the present invention provide a communication base station energy system, a capacity planning method and related devices to solve the technical problems that the operation reliability of the communication base station is relatively low when the communication base station energy system supplies power to the communication base station, and the planning accuracy is relatively poor when the communication base station energy system conducts capacity planning in the prior art.

[0005] In a first aspect, the embodiments of the present invention provide a communication base station energy system, the system includes: a DC superposition optical system, a battery pack, a hydrogen fuel cell, a hydrogen storage bottle group, an intelligent busbar trunking system and a switching power supply; wherein,

[0006] The hydrogen storage bottle group is connected to the hydrogen fuel cell and is used to provide hydrogen for the hydrogen fuel cell;

[0007] The hydrogen fuel cell and the DC superposition optical system are respectively connected to the intelligent busbar trunking system, and the hydrogen fuel cell and the DC superposition optical system supply power to the devices of the communication base station through the intelligent busbar trunking system;

[0008] The intelligent busbar trunking system and the battery pack are incorporated into the switching power supply together, and the switching power supply is used to control the intelligent busbar trunking system and the battery pack to supply power to the devices of the communication base station.

[0009] Second aspect, an embodiment of the present invention provides a capacity planning method, which is applied to a communication base station energy system. The communication base station energy system includes a DC-overlight system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group. The communication base station energy system powers the devices of the communication base station through the DC-overlight system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The method includes:

[0010] Obtain the historical operation parameter data of the communication base station energy system;

[0011] Based on the historical operation parameter data, construct the target operation parameter data of the communication base station energy system under K extreme climate scenarios, where K is a positive integer;

[0012] Based on the target operation parameter data and a pre-constructed first capacity planning model, plan the configuration capacity group of the communication base station energy system. The configuration capacity group includes the configuration capacities of the DC-overlight system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group;

[0013] Wherein, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function with the minimization of the annualized cost of the communication base station energy system as the objective. The annualized cost is related to the configuration capacity group of the communication base station energy system. The first constraint function is used to indicate the balance between the power consumption of the communication base station under extreme scenarios and the power supply of the communication base station energy system. The second constraint function is used to indicate that the difference in the reserve amounts of the energy storage group in adjacent time periods under extreme scenarios is equal to the consumption amount of the energy storage group. The energy storage group includes the hydrogen storage bottle group and the battery pack.

[0014] Third aspect, an embodiment of the present invention provides a capacity planning device, which is applied to a communication base station energy system. The communication base station energy system includes a DC-overlight system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group. The communication base station energy system powers the devices of the communication base station through the DC-overlight system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The device includes:

[0015] An acquisition module, configured to obtain the historical operation parameter data of the communication base station energy system;

[0016] A scenario construction module, configured to construct the target operation parameter data of the communication base station energy system under K extreme climate scenarios based on the historical operation parameter data, where K is a positive integer;

[0017] A planning module, configured to plan the configuration capacity group of the communication base station energy system based on the target operation parameter data and a pre-constructed first capacity planning model. The configuration capacity group includes the configuration capacities of the DC-overlight system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group;

[0018] Among them, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function aiming at minimizing the annualized cost of the communication base station energy system. The annualized cost is related to the configured capacity group of the communication base station energy system. The first constraint function is used to indicate that the power consumption of the communication base station in an extreme scenario is balanced with the power supply of the communication base station energy system. The second constraint function is used to indicate that the difference in the reserve amount of the energy storage group in adjacent time periods in an extreme scenario is equal to the consumption amount of the energy storage group. The energy storage group includes the hydrogen storage bottle group and the battery group.

[0019] In a fourth aspect, an embodiment of the present invention provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above capacity planning method are implemented.

[0020] In a fifth aspect, an embodiment of the present invention provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above capacity planning method are implemented.

[0021] In a sixth aspect, an embodiment of the present invention provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the steps of the above capacity planning method are implemented.

[0022] In the embodiment of the present invention, the communication base station energy system supplies power to the devices of the communication base station through the cooperation of two energy storages, namely the hydrogen storage bottle group and the battery, which can improve the flexibility, stability, and robustness of the communication base station energy system, thereby improving the operation reliability of the communication base station. Moreover, in the capacity planning method of the communication base station energy system, the target operation parameter data in an extreme climate scenario is constructed through historical operation parameter data, and based on the target operation parameter data and the pre-constructed first capacity planning model, the capacity planning of the energy storage devices in the communication base station energy system is carried out, which can improve the power supply capacity of the communication base station energy system to the communication base station devices in an extreme climate scenario, thereby improving the operation reliability of the communication base station energy system in an extreme climate scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 is one of the structural schematic diagrams of the communication base station energy system provided by the embodiment of the present invention;

[0025] Figure 2 It is the second structural schematic diagram of the communication base station energy system provided by the embodiment of the present invention;

[0026] Figure 3 It is the flow schematic diagram of the capacity planning method provided by the embodiment of the present invention;

[0027] Figure 4 It is the flow schematic diagram of the capacity planning method of a specific example;

[0028] Figure 5 It is the structural schematic diagram of the capacity planning device provided by the embodiment of the present invention;

[0029] Figure 6 It is the structural schematic diagram of the electronic device provided by the embodiment of the present invention. Specific Embodiments

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0031] It should be noted that the communication base station energy system provided by the embodiment of the present invention relates to the fields of communication infrastructure and information technology (IT) support.

[0032] A communication base station is an important infrastructure for wireless network communication, and a stable base station energy supply is crucial for the regional wireless communication quality. At present, the communication base station energy system can use batteries, photovoltaic, fuel cells, etc. as the energy supply for the communication base station. At the structural level, if batteries are used as energy storage, there are problems such as energy attenuation and low battery life. Photovoltaic devices are limited by the volatility of light conditions and usually adopt a conservative strategy to discard part of the power, resulting in a low degree of renewable energy consumption. The fuel cell system has low integration and intelligence levels, and the ramp power is limited by the internal chemical reaction rate and cannot independently undertake the energy supply of the communication base station energy system.

[0033] In the related art, the communication base station energy system is mainly composed of photovoltaic panels, battery packs, switching power supplies, etc. to achieve clean energy storage and supply for the equipment of the communication base station. Although some energy systems have added fuel cells as power sources, they do not consider the capacity configuration of the unified hydrogen storage tank, which will affect the scenario applicability and reliability of the base station.

[0034] Since the energy system of communication base stations is usually installed outdoors, in some remote areas, the distance between the energy system of communication base stations and the substation is too far, making wiring difficult. The energy system needs to achieve energy storage and off-grid operation. Hydrogen energy is suitable for long-term and large-capacity storage. Therefore, in the embodiments of the present invention, a hydrogen-electricity dual-emphasis base station energy system can be formed by coordinating hydrogen fuel cells, photovoltaic power, and storage batteries, and further achieve stable power supply for the base station. However, in this energy system, renewable energy varies greatly with regions, and the operating parameters of the equipment included in the fuel cell are complex. Reasonable planning of the installed capacity of the equipment is crucial for the reliable operation of the communication base station energy system.

[0035] In related technologies, the capacity planning methods for communication base station energy systems are mainly divided into two categories. The first category is the capacity configuration method based on rated power, and the second category is the capacity configuration method that constructs an optimal energy consumption target. Among them, the capacity configuration method based on rated power configures the storage battery through simple operations according to the energy storage duration and rated power. The capacity configuration based on the optimal energy consumption target usually sets the minimization of energy consumption as the objective function and plans and designs the energy storage capacity based on historical load information.

[0036] However, the capacity configuration method based on rated power and energy storage duration has excessive redundancy and design errors in practical applications. The capacity configuration method based on optimal energy consumption is usually too ideal and difficult to ensure reliable operation in extreme scenarios. Therefore, how to achieve the capacity configuration of the hydrogen-electricity dual-emphasis communication base station energy system is a key technology to improve energy utilization efficiency and achieve stable power supply.

[0037] First, the communication base station energy system provided in the embodiments of the present invention will be introduced below.

[0038] Figure 1 is one of the structural schematic diagrams of the communication base station energy system provided in the embodiments of the present invention. As Figure 1 shown, the system includes: a DC superimposed photovoltaic system 101, a storage battery pack 102, a hydrogen fuel cell 103, a hydrogen storage bottle group 104, an intelligent busbar trunking system 105, and a switching power supply 106; among them,

[0039] The hydrogen storage bottle group 104 is connected to the hydrogen fuel cell 103 and is used to supply hydrogen to the hydrogen fuel cell 103;

[0040] The hydrogen fuel cell 103 and the DC superimposed photovoltaic system 101 are respectively connected to the intelligent busbar trunking system 105, and the hydrogen fuel cell 103 and the DC superimposed photovoltaic system 101 supply power to the equipment of the communication base station through the intelligent busbar trunking system 105;

[0041] The intelligent busbar trunking system 105 and the storage battery pack 102 are incorporated into the switching power supply 106 together, and the switching power supply 106 is used to control the intelligent busbar trunking system 105 and the storage battery pack 102 to supply power to the equipment of the communication base station.

[0042] Among them, the hydrogen fuel cell is connected to the intelligent busbar trunking box to supply power to the communication base station.

[0043] In this embodiment, by integrating the hydrogen fuel cell and the DC optical superposition system into the intelligent busbar trunking box, and integrating the intelligent busbar trunking box and the battery pack into the switching power supply together, the DC optical superposition system, the battery pack and the hydrogen fuel cell can be controlled to jointly supply power to the equipment of the communication base station, realizing equal emphasis on hydrogen and electricity.

[0044] In this embodiment, the energy system of the communication base station supplies power to the equipment of the communication base station through the cooperation of two energy storages, namely the hydrogen storage bottle group and the battery, which can improve the flexibility, stability and robustness of the energy system of the communication base station, thereby enhancing the operation reliability of the communication base station.

[0045] In some embodiments, Figure 2 FIG. 2 is a second schematic structural diagram of the energy system of the communication base station provided by the embodiment of the present invention. The system further includes a cooling tower 107 and a plate heat exchanger 108; among them,

[0046] The plate heat exchanger 108 is connected to the hydrogen fuel cell 103 for heat exchange with the hydrogen fuel cell 103;

[0047] One side of the plate heat exchanger 108 is connected to the hydrogen fuel cell 103, and the other side is connected to the cooling tower 107;

[0048] The cooling tower 107 is respectively connected to the plate heat exchanger 108, the switching power supply 106 and the battery pack 102 for cooling the plate heat exchanger 108, the switching power supply 106 and the battery pack 102.

[0049] In this embodiment, the energy system of the communication base station may include a DC optical superposition system, a hydrogen fuel cell, a hydrogen storage bottle group, an intelligent busbar trunking box, a battery pack, a switching power supply, a cooling tower and a plate heat exchanger. Among them, the hydrogen fuel cell is connected to the plate heat exchanger for heat exchange. One side of the plate heat exchanger is connected to the hydrogen fuel cell, and the other side is connected to the cooling tower, so that the cooling of the hydrogen fuel cell can be realized. In this embodiment, the structure of the energy system of the communication base station takes into account the heat recovery problem of the equipment in the energy system of the communication base station, and can improve the energy utilization rate of the system.

[0050] In some embodiments, as Figure 2 shown, the energy system of the communication base station may further include commercial power. The DC optical superposition system is connected to the intelligent busbar trunking box, and the intelligent busbar trunking box, commercial power and the battery pack are integrated into the switching power supply together to supply power to the equipment of the communication base station.

[0051] In some embodiments, as Figure 2As shown, the communication base station energy system may further include a voltage regulating device 109, which is arranged between the hydrogen storage bottle group and the hydrogen fuel cell and is used to regulate the gas pressure of the hydrogen storage bottle group.

[0052] In some embodiments, the communication base station energy system may further include a water pump, which may be integrated in the generator set and is used to provide power during the power generation process of the generator set and can dissipate heat for the hydrogen fuel cell. Among them, the generator set may generate electricity through a DC superposition optical system and hydrogen fuel, as Figure 2 shown, devices such as the DC superposition optical system, the hydrogen storage bottle group, the hydrogen fuel cell, the intelligent busbar trunking system, and the plate heat exchanger constitute the generator set.

[0053] In some embodiments, the communication base station energy system may further include a control host computer, and the control host computer may perform real-time control and early warning on the communication base station energy system.

[0054] In some embodiments, as Figure 2 shown, the communication base station energy system may further include some pipelines and valves 110. The hydrogen storage bottle group and the hydrogen fuel cell may be connected through a hydrogen pipeline 111 and valves. The hydrogen fuel cell and the plate heat exchanger may be connected through a hot water pipeline 112 and valves. The plate heat exchanger and the cooling tower may also be connected through a hot water pipeline 112 and valves. The cooling tower, the switching power supply, the battery pack, and the communication base station may be connected through a cold water pipeline 113 and valves. Other devices may be connected through an electrical line 114. Among them, the valves can control the opening, closing, and flow control of the pipelines.

[0055] The capacity planning method of the communication base station energy system provided in the embodiments of the present invention will be introduced below.

[0056] Figure 3 is a schematic flow chart of the capacity planning method provided in the embodiments of the present invention. As Figure 3 shown, the method is applied to a communication base station energy system, and the communication base station energy system includes a DC superposition optical system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group. The communication base station energy system supplies power to the devices of the communication base station through the DC superposition optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The method includes:

[0057] Step 301, obtaining the historical operation parameter data of the communication base station energy system;

[0058] Step 302, based on the historical operation parameter data, constructing the target operation parameter data of the communication base station energy system under K extreme climate scenarios, where K is a positive integer;

[0059] Step 303: Based on the target operation parameter data and the pre-constructed first capacity planning model, plan the configured capacity groups of the communication base station energy system, where the configured capacity groups include the configured capacities of the DC combined optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group.

[0060] Among them, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function with the goal of minimizing the annualized cost of the communication base station energy system. The annualized cost is related to the configured capacity groups of the communication base station energy system. The first constraint function is used to indicate the balance between the power consumption of the communication base station in extreme scenarios and the power supply of the communication base station energy system. The second constraint function is used to indicate that the difference in the reserve amounts of the energy storage group in adjacent time periods in extreme scenarios is equal to the consumption amount of the energy storage group, and the energy storage group includes the hydrogen storage bottle group and the battery pack.

[0061] In step 301, the historical operation parameter data can indicate the historical operation conditions of the DC combined optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group in the communication base station energy system.

[0062] The historical operation parameter data may include the historical light data of the DC combined optical system, the hydrogen supply situation near the communication base station, the hydrogen price, the mains power supply situation near the communication base station, the mains power price, etc., which are not specifically limited here.

[0063] In some embodiments, the historical operation parameter data of the communication base station energy system can be determined according to the longitude and latitude coordinates of the communication base station location and the base station location conditions such as communication conditions. For example, the hydrogen supply situation and hydrogen price near the communication base station can be determined according to the communication conditions of the communication base station location. For another example, the mains power supply situation and mains power price near it can be determined according to the longitude and latitude coordinates of the communication base station location and the communication base station conditions.

[0064] In some embodiments, the historical light data of the DC combined optical system can be determined according to the historical outdoor climate data of the communication base station throughout the year. In some embodiments, the historical operation parameter data of the communication base station energy system can also be obtained by acquiring the recorded data, such as acquiring the recorded historical light data of the DC combined optical system.

[0065] In step 302, the extreme climate scenario can refer to the operation scenario of the communication base station energy system under extreme climate conditions. The extreme climate scenario can be related to the climate of the communication base station, that is, the extreme climate scenario can be related to the light of the DC combined optical system.

[0066] The historical operating parameter data may include historical light intensity data. In some embodiments, based on the historical light intensity data for each month, an operating scenario for a period of abnormal light intensity can be selected therefrom as an extreme climate scenario. Herein, K can be preset or obtained by dividing the total number of days of the historical light intensity data by 30 and rounding up.

[0067] In some embodiments, the time scale of each extreme climate scenario can be one day, or the time dimension can be set according to actual circumstances, which is not specifically limited herein.

[0068] In some embodiments, step 302 specifically includes:

[0069] Clustering the historical light intensity data of the DC superposition light system in the historical operating parameter data to obtain the target light intensity data of the DC superposition light system under K extreme climate scenarios corresponding to K clusters;

[0070] Based on the historical operating parameter data, constructing the target operating parameter data of the DC superposition light system under K extreme climate scenarios corresponding to the K clusters, where the target operating parameter data includes the target light intensity data.

[0071] In this embodiment, historical operating parameter data can be collected. The collected historical operating parameter data may include the historical light intensity data of the DC superposition light system in the communication base station energy system. The historical light intensity data can be collected in units of days and with a time granularity of 1 hour for at least 365 days and 8760 hours. The clustering method is used to cluster the historical light intensity data to obtain K clusters, and these K clusters correspond to K types of extreme climate scenarios. Herein, K can be obtained by dividing the total number of days of the historical light intensity data by 30 and rounding up, and the time scale of each extreme climate scenario is one day.

[0072] In the case of obtaining K clusters, the target light intensity data of the DC superposition light system under K extreme climate scenarios corresponding to the K clusters can be constructed according to the historical light intensity data under each cluster. The light intensity data of the DC superposition light system under each extreme climate scenario can be obtained by averaging the historical light intensity data under the corresponding cluster, or can be the light intensity data at the middle position in the historical light intensity data under the corresponding cluster. Herein, the target light intensity data of the DC superposition light system under each extreme climate scenario may include the light intensity time-sharing data within 24 hours of a day in this extreme climate scenario.

[0073] In the case of obtaining K clusters, it is also possible to construct target operating parameter data for K extreme climate scenarios corresponding to the K clusters based on the historical operating parameter data under each cluster. The target operating parameter data for each extreme climate scenario can be obtained by averaging the historical operating parameter data under the corresponding cluster, or can be the operating parameter data in the middle position of the historical operating parameter data under the corresponding cluster. The target operating parameter data can also include the market hydrogen supply volume and the grid power consumption within 24 hours of a day under extreme climate scenarios.

[0074] In this embodiment, by clustering to construct extreme climate scenarios for the operation of the communication base station energy system, the construction accuracy and robustness of the extreme climate scenarios for the operation of the communication base station energy system can be improved.

[0075] In step 303, the first capacity planning model can be an optimal capacity allocation model including an economically optimal objective function, system state constraints, and state transition constraints. The capacity planning method in the embodiments of the present invention aims to construct an objective that minimizes the sum of the annualized investment cost and the operating cost. Therefore, the first objective function can be as shown in the following formula (1):

[0076]

[0077] Among them, λ h 、 respectively represent the hydrogen purchase price and the mains electricity price in the i-th time period; respectively represent the market hydrogen supply volume and the grid power consumption in the i-th time period under the d-th extreme climate scenario. Among them, hydrogen is calculated in kilograms (kg), and electricity is calculated in kilowatt-hours (kWh). Limited by the hydrogen supply chain, the hydrogen supply operation is carried out on a daily basis.

[0078] CAPEX is the annualized investment cost of the communication base station energy system, mainly including the investment costs of hydrogen fuel cells, battery packs, DC optical superposition systems, and hydrogen storage bottle groups. Among them, C FC , C BS , C PV , C HS respectively represent the annualized investment unit prices of hydrogen fuel cells, battery packs, DC optical superposition systems, and hydrogen storage bottle groups, and P FC , P BS , P PV , H HS respectively represent the configured capacities of the planned hydrogen fuel cells, battery packs, DC optical superposition systems, and hydrogen storage bottle groups.

[0079] N can be the time scale of the extreme climate scenario, which can be one day, that is, 24 hours.

[0080] The system state constraint, that is, the first constraint function, is the energy supply and demand balance Among them respectively represent the power consumption of the power grid, the power generation of photovoltaic power generation, the power generation of hydrogen fuel cells, the power consumption or power storage of the battery pack, and the service power consumption of the communication base station during the i-th time period under the d-th extreme climate scenario.

[0081] The state transfer constraint, that is, the second constraint function, includes the state transfer of two types of energy storage, hydrogen storage and electricity storage. represents the state transfer of hydrogen storage, where respectively represent the current hydrogen storage volume of the hydrogen storage bottle group and the hydrogen consumption of the hydrogen fuel cell, represents the hydrogen storage volume of the hydrogen storage bottle group at the next moment. represents the state transfer of the battery pack, where respectively represent the current power storage volume and power consumption of the battery pack, represents the power storage volume of the battery pack at the next moment.

[0082] The target operating parameter data can be substituted into the first capacity planning model, and the first capacity planning model can be solved, so that the configuration capacity group of the communication base station energy system can be obtained by solving.

[0083] In this embodiment, by constructing the target operating parameter data under the extreme climate scenario based on the historical operating parameter data, and based on the target operating parameter data and the pre-constructed first capacity planning model, the capacity planning of the energy storage device in the communication base station energy system can improve the power supply capacity of the communication base station energy system to the communication base station equipment under the extreme climate scenario, improve the scenario applicability, and improve the operating reliability of the communication base station energy system under the extreme climate scenario.

[0084] In some embodiments, step 303 specifically includes:

[0085] Construct a third constraint function and a fourth constraint function. The third constraint function indicates that the first capacity group of the communication base station energy system is the same as the configuration capacity group of the communication base station energy system under the extreme climate scenario. The fourth constraint function is used to indicate that the second capacity group of the communication base station energy system within one time period under the extreme climate scenario is less than or equal to the first capacity group. The second capacity planning model of the communication base station energy system includes a first objective function, a first constraint function, a second constraint function, a third constraint function, and a fourth constraint function;

[0086] Based on the target operating parameter data and the second capacity planning model, plan the configuration capacity group of the communication base station energy system.

[0087] In this embodiment, based on the extreme climate scenario, the equipment capacity under the extreme climate scenario can be introduced to construct the operation optimization sub-problem under different extreme climate scenarios. Specifically, the equipment capacity under the extreme climate scenario can be introduced They are respectively expressed as the planned capacities of the hydrogen fuel cell, battery pack, DC optical superposition system, and hydrogen storage bottle group within the d-th extreme climate scenario. Subsequently, the capacity constraint under the extreme climate scenario, that is, the third constraint function, is introduced as indicating that the capacity planning under the extreme climate scenario should be the same as the configured capacity of the communication base station energy system.

[0088] Moreover, the upper limit constraint of equipment operation within the extreme climate scenario, that is, the fourth constraint function, is introduced as This constraint ensures that the equipment operation logic within each extreme climate scenario satisfies the equipment capacity constraint within the current extreme climate scenario.

[0089] Substitute the target operation parameter data into the second capacity planning model and solve the first capacity planning model, so as to obtain the configured capacity group of the communication base station energy system. By introducing the third constraint function and the fourth constraint function, the capacity planning model can be optimized, making the capacity planning of the communication base station energy system more accurate.

[0090] In some embodiments, planning the configured capacity group of the communication base station energy system based on the target operation parameter data and the second capacity planning model includes:

[0091] Based on the second capacity planning model, construct a third capacity planning model. The third capacity planning model includes a second objective function with the minimum annualized cost of the communication base station energy system as the goal, the first constraint function, the second constraint function, and the fourth constraint function. The second objective function is the Lagrangian function under the third constraint function;

[0092] Based on the target operation parameter data and the third capacity planning model, plan the configured capacity group of the communication base station energy system.

[0093] In this embodiment, in order to accelerate the solution process, a Lagrange multiplier can be introduced Relax the third constraint function into the first objective function to form an augmented Lagrangian optimization problem, and obtain the third capacity planning model. The third capacity planning model can include a second objective function, as shown in the following formula (2):

[0094]

[0095] The target operation parameter data can be substituted into the third capacity planning model and the third capacity planning model can be solved, so as to obtain the configured capacity group of the communication base station energy system.

[0096] In this embodiment, by relaxing the scenario capacity constraint between the equipment capacity in the extreme climate scenario and the finally planned equipment capacity, introducing Lagrange multipliers, and constructing an augmented Lagrangian objective function, the augmented Lagrangian function method is used to form the main planning problem, that is, the second objective function, and the decoupled operation sub-problems of multiple extreme climate scenarios, that is, the model lower constraint functions. This can accelerate the solution process of the capacity planning model, thereby improving the efficiency of capacity configuration calculation, and avoiding reliability problems caused by insufficient capacity planning and redundancy problems caused by excessive capacity planning.

[0097] In some embodiments, planning the configured capacity group of the communication base station energy system based on the target operating parameter data and the third capacity planning model includes:

[0098] Initializing the Lagrange multiplier group in the second objective function, where the Lagrange multiplier group includes Lagrange multipliers respectively related to the DC superposed optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The first Lagrange multiplier related to the DC superposed optical system is initialized to the photovoltaic power generation of the DC superposed optical system in the extreme climate scenario, and the photovoltaic power generation is determined based on the target illumination data of the DC superposed optical system in the target operating parameter data. Other Lagrange multipliers in the Lagrange multiplier group except the first Lagrange multiplier are initialized to 0;

[0099] Substituting the target operating parameter data into the third capacity planning model, sequentially solving the solutions of the configured capacity group in the third capacity planning model, and updating the Lagrange multiplier group based on the error between the obtained configured capacity group and the first capacity group;

[0100] When the obtained configured capacity group satisfies the third constraint function, output the configured capacity group of the communication base station energy system.

[0101] In this embodiment, the process of solving the third capacity planning model can first initialize the Lagrange multipliers. The first Lagrange multiplier related to the DC superposed optical system, that is, is initialized to the total photovoltaic power generation within the d-th extreme climate scenario, and the remaining multipliers are initialized to 0.

[0102] In some embodiments, the photovoltaic power generation within the d-th extreme climate scenario can be the sum of the photovoltaic power generations in 24 hours within the d-th extreme climate scenario. Since the target illumination data includes the time-sharing data within the d-th extreme climate scenario, therefore, the photovoltaic power generation per hour within the d-th extreme climate scenario can be determined based on the time-sharing data, and the photovoltaic power generations in 24 hours are summed up, so that the total photovoltaic power generation within the d-th extreme climate scenario can be obtained.

[0103] After initializing the Lagrange multipliers, the augmented Lagrangian optimization problem can be solved to obtain the relaxed solution for the current iteration round, that is, a set of configured capacity groups. It can be determined whether the obtained configured capacity groups satisfy the device capacity scenario constraint, i.e., the third constraint function. If so, the configured capacity groups are directly output. If not, the initialized Lagrange multipliers are updated based on the error between the obtained configured capacity groups and the first capacity group.

[0104] In some embodiments, the Lagrange multiplier groups can be updated according to the following equations (3), (4), (5), and (6).

[0105]

[0106] After that, based on the updated Lagrange multiplier groups, the third capacity planning model is solved again until the scenario device capacity constraint, i.e., the third constraint function, is satisfied, and finally a set of configured capacity groups is output.

[0107] In this embodiment, through the initialization of Lagrange multipliers, the convergence speed of the algorithm can be improved, thereby further improving the efficiency of capacity configuration calculation for the communication base station energy system.

[0108] The following details the specific process of the capacity planning method of this embodiment with an example.

[0109] Figure 4 is a schematic flowchart of the capacity planning method of a specific example. As Figure 4 shown, the capacity planning method of this embodiment includes the following steps:

[0110] Step 401: Construct the first capacity planning model and collect the historical operation parameter data of the communication base station energy system.

[0111] Step 402: Cluster the historical light data of the DC superimposed light system in the historical operation parameter data to obtain the target light data of the DC superimposed light system under K extreme climate scenarios corresponding to K clusters; and based on the historical operation parameter data, construct the target operation parameter data under K extreme climate scenarios corresponding to K clusters.

[0112] Step 403: Introduce the first capacity group of the communication base station energy system under extreme climate scenarios and the second capacity group of the communication base station energy system within a time period under extreme climate scenarios, and construct the third constraint function and the fourth constraint function to construct the second capacity planning model.

[0113] Step 404: Introduce Lagrange multipliers and construct the third capacity planning model based on the second capacity planning model; substitute the target operation parameter data into the third capacity planning model and initialize the Lagrange multipliers.

[0114] Step 405: Solve the Lagrangian function to obtain a set of configured capacity groups;

[0115] Step 406: Whether the configured capacity group satisfies the third constraint function;

[0116] Step 407: If not, calculate the error between the configured capacity group and the first capacity group, update the Lagrange multiplier based on the error, and re-solve the Lagrangian function;

[0117] Step 408: If so, output the configured capacity group as the capacity plan of the communication base station system.

[0118] The capacity planning device provided by the embodiment of the present invention will be described below.

[0119] See Figure 5 , which shows a schematic structural diagram of the capacity planning device provided by the embodiment of the present invention. The device is applied to a communication base station energy system, and the communication base station energy system includes a DC superimposed optical system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group. The communication base station energy system powers the devices of the communication base station through the DC superimposed optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. As Figure 5 shown, the capacity planning device 500 includes:

[0120] An acquisition module 501, configured to acquire the historical operation parameter data of the communication base station energy system;

[0121] A scenario construction module 502, configured to construct the target operation parameter data of the communication base station energy system under K extreme climate scenarios based on the historical operation parameter data, where K is a positive integer;

[0122] A planning module 503, configured to plan the configured capacity group of the communication base station energy system based on the target operation parameter data and a pre-constructed first capacity planning model. The configured capacity group includes the configured capacities of the DC superimposed optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group;

[0123] Wherein, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function with the goal of minimizing the annualized cost of the communication base station energy system. The annualized cost is related to the configured capacity group of the communication base station energy system. The first constraint function is used to indicate the balance between the power consumption of the communication base station in the extreme scenario and the power supply of the communication base station energy system. The second constraint function is used to indicate that the difference in the reserve amount of the energy storage group in adjacent time periods in the extreme scenario is equal to the consumption amount of the energy storage group. The energy storage group includes the hydrogen storage bottle group and the battery pack.

[0124] Optionally, the planning module 503 includes:

[0125] A model construction unit for constructing a third constraint function and a fourth constraint function. The third constraint function indicates that in an extreme climate scenario, a first capacity group of the communication base station energy system is the same as a configured capacity group of the communication base station energy system. The fourth constraint function is used to indicate that in an extreme climate scenario, a second capacity group of the communication base station energy system within a period is less than or equal to the first capacity group. The second capacity planning model of the communication base station energy system includes a first objective function, a first constraint function, a second constraint function, a third constraint function, and a fourth constraint function;

[0126] A planning unit for planning the configured capacity group of the communication base station energy system based on the target operating parameter data and the second capacity planning model.

[0127] Optionally, the planning unit is specifically configured to:

[0128] Based on the second capacity planning model, construct a third capacity planning model. The third capacity planning model includes a second objective function with the minimum annualized cost of the communication base station energy system as the target, the first constraint function, the second constraint function, and the fourth constraint function. The second objective function is a Lagrangian function under the third constraint function;

[0129] Based on the target operating parameter data and the third capacity planning model, plan the configured capacity group of the communication base station energy system.

[0130] Optionally, the planning unit is further configured to:

[0131] Initialize the Lagrangian multiplier group in the second objective function. The Lagrangian multiplier group includes Lagrangian multipliers respectively related to the DC superimposed optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The first Lagrangian multiplier related to the DC superimposed optical system is initialized to the photovoltaic power generation of the DC superimposed optical system in an extreme climate scenario. The photovoltaic power generation is determined based on the target illumination data of the DC superimposed optical system in the target operating parameter data. Other Lagrangian multipliers in the Lagrangian multiplier group except the first Lagrangian multiplier are initialized to 0;

[0132] Substitute the target operating parameter data into the third capacity planning model, sequentially solve the solution of the configured capacity group in the third capacity planning model, and update the Lagrangian multiplier group based on the error between the obtained configured capacity group and the first capacity group;

[0133] When the obtained configured capacity group satisfies the third constraint function, output the configured capacity group of the communication base station energy system.

[0134] Optionally, the scenario construction module 502 is specifically configured to:

[0135] Cluster the historical light intensity data of the DC superposed light system in the historical operation parameter data to obtain the target light intensity data of the DC superposed light system under K extreme climate scenarios corresponding to K clusters;

[0136] Based on the historical operation parameter data, construct the target operation parameter data of the communication base station energy system under K extreme climate scenarios corresponding to the K clusters, where the target operation parameter data includes the target light intensity data.

[0137] The capacity planning device 500 can implement each process implemented in the above-mentioned capacity planning method embodiment and achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0138] See Figure 6 , which shows the structural schematic diagram of the electronic device provided by the embodiment of the present invention. As Figure 6 shown, the electronic device 600 includes: a processor 601, a memory 602, a user interface 603, and a bus interface 604.

[0139] The processor 601 is configured to read the program in the memory 602 and execute the following processes:

[0140] Obtain the historical operation parameter data of the communication base station energy system; the communication base station energy system includes a DC superposed light system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group, and the communication base station energy system supplies power to the devices of the communication base station through the DC superposed light system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group;

[0141] Based on the historical operation parameter data, construct the target operation parameter data of the communication base station energy system under K extreme climate scenarios, where K is a positive integer;

[0142] Based on the target operation parameter data and a pre-constructed first capacity planning model, plan the configuration capacity group of the communication base station energy system, where the configuration capacity group includes the configuration capacities of the DC superposed light system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group;

[0143] Among them, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function aiming at minimizing the annualized cost of the communication base station energy system. The annualized cost is related to the configured capacity group of the communication base station energy system. The first constraint function is used to indicate the balance between the power consumption of the communication base station in extreme scenarios and the power supply of the communication base station energy system. The second constraint function is used to indicate that the difference in the reserve quantity of the energy storage group in adjacent time periods in extreme scenarios is equal to the consumption quantity of the energy storage group. The energy storage group includes a hydrogen storage bottle group and a battery group.

[0144] In Figure 6 it, the bus architecture may include any number of interconnected buses and bridges, specifically, various circuits represented by one or more processors represented by the processor 601 and a memory represented by the memory 602 are linked together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, and thus will not be further described herein. The bus interface 604 provides an interface. For different user devices, the user interface 603 can also be an interface capable of externally connecting or internally connecting required devices, and the connected devices include but are not limited to a keypad, a display, a speaker, a microphone, a joystick, etc.

[0145] The processor 601 is responsible for managing the bus architecture and general processing, and the memory 602 can store the data used by the processor 601 when performing operations.

[0146] Optionally, the processor 601 is further configured to:

[0147] Construct a third constraint function and a fourth constraint function. The third constraint function indicates that the first capacity group of the communication base station energy system is the same as the configured capacity group of the communication base station energy system in extreme climate scenarios. The fourth constraint function is used to indicate that the second capacity group of the communication base station energy system in a time period in extreme climate scenarios is less than or equal to the first capacity group. The second capacity planning model of the communication base station energy system includes a first objective function, a first constraint function, a second constraint function, a third constraint function, and a fourth constraint function;

[0148] Based on the target operation parameter data and the second capacity planning model, plan the configured capacity group of the communication base station energy system.

[0149] Optionally, the processor 601 is further configured to:

[0150] Based on the second capacity planning model, a third capacity planning model is constructed. The third capacity planning model includes a second objective function aiming at minimizing the annualized cost of the communication base station energy system, the first constraint function, the second constraint function, and the fourth constraint function. The second objective function is the Lagrangian function under the third constraint function;

[0151] Based on the target operating parameter data and the third capacity planning model, the configured capacity group of the communication base station energy system is planned.

[0152] Optionally, the processor 601 is further configured to:

[0153] Initialize the Lagrangian multiplier group in the second objective function. The Lagrangian multiplier group includes Lagrangian multipliers respectively related to the DC optical superposition system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The first Lagrangian multiplier related to the DC optical superposition system is initialized to the photovoltaic power generation of the DC optical superposition system in the extreme climate scenario. The photovoltaic power generation is determined based on the target illumination data of the DC optical superposition system in the target operating parameter data. The other Lagrangian multipliers in the Lagrangian multiplier group except the first Lagrangian multiplier are initialized to 0;

[0154] Substitute the target operating parameter data into the third capacity planning model, and sequentially solve the solutions of the configured capacity group in the third capacity planning model. Based on the error between the obtained configured capacity group and the first capacity group, update the Lagrangian multiplier group;

[0155] When the obtained configured capacity group satisfies the third constraint function, output the configured capacity group of the communication base station energy system.

[0156] Optionally, the processor 601 is further configured to:

[0157] Cluster the historical illumination data of the DC optical superposition system in the historical operating parameter data to obtain the target illumination data of the DC optical superposition system in K extreme climate scenarios corresponding to K clusters;

[0158] Based on the historical operating parameter data, construct the target operating parameter data of K extreme climate scenarios corresponding to the K clusters. The target operating parameter data includes the target illumination data.

[0159] Preferably, an embodiment of the present invention further provides an electronic device 600, including a processor 601, a memory 602, and a computer program stored on the memory 602 and executable on the processor 601. When the computer program is executed by the processor 601, it implements each process of the above-described embodiment of the capacity planning method and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0160] An embodiment of the present invention further provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each process of the above-described embodiment of the capacity planning method and can achieve the same technical effect. To avoid repetition, it will not be elaborated here. Among them, the readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0161] An embodiment of the present application further provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, they implement each process of the above-described embodiment of the capacity planning method and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0162] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0163] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated here.

[0164] In the embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of devices or units can be in an electrical, mechanical, or other form.

[0165] The unit described as a separation component may or may not be physically separated. The component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present invention.

[0166] In addition, in each embodiment of the present invention, each functional unit may be integrated in a processing unit, may exist physically separately for each unit, or two or more units may be integrated in one unit.

[0167] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0168] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A communication base station energy system, characterized in that, The system includes: a DC superposition optical system, a battery pack, a hydrogen fuel cell, a hydrogen storage bottle group, an intelligent busbar trunking system, and a switching power supply; wherein, The hydrogen storage bottle group is connected to the hydrogen fuel cell and is used to supply hydrogen to the hydrogen fuel cell; The hydrogen fuel cell and the DC superposition optical system are respectively connected to the intelligent busbar trunking system, and the hydrogen fuel cell and the DC superposition optical system supply power to the equipment of the communication base station through the intelligent busbar trunking system; The intelligent busbar trunking system and the battery pack are incorporated into the switching power supply together, and the switching power supply is used to control the intelligent busbar trunking system and the battery pack to supply power to the equipment of the communication base station.

2. The system according to claim 1, characterized in that, The system further includes a cooling tower and a plate heat exchanger; wherein, The plate heat exchanger is connected to the hydrogen fuel cell and is used to perform heat exchange with the hydrogen fuel cell; One side of the plate heat exchanger is connected to the hydrogen fuel cell, and the other side is connected to the cooling tower; The cooling tower is respectively connected to the plate heat exchanger, the switching power supply, and the battery pack, and is used to cool the plate heat exchanger, the switching power supply, and the battery pack.

3. A capacity planning method, characterized in that, The method is applied to a communication base station energy system, which includes a DC superposition optical system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group. The communication base station energy system supplies power to the equipment of the communication base station through the DC superposition optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The method includes: Obtaining historical operation parameter data of the communication base station energy system; Based on the historical operation parameter data, constructing target operation parameter data of the communication base station energy system under K extreme climate scenarios, where K is a positive integer; Based on the target operation parameter data and a pre-constructed first capacity planning model, planning the configuration capacity group of the communication base station energy system, and the configuration capacity group includes the configuration capacities of the DC superposition optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group; Wherein, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function with the minimum annualized cost of the communication base station energy system as the goal. The annualized cost is related to the configuration capacity group of the communication base station energy system. The first constraint function is used to indicate the balance between the power consumption of the communication base station in the extreme scenario and the power supply of the communication base station energy system. The second constraint function is used to indicate that the difference in the reserve amount of the energy storage group in adjacent time periods in the extreme scenario is equal to the consumption amount of the energy storage group, and the energy storage group includes the hydrogen storage bottle group and the battery pack.

4. The method according to claim 3, characterized in that, The planning of the configuration capacity group of the communication base station energy system based on the target operation parameter data and the pre-constructed first capacity planning model includes: Construct a third constraint function and a fourth constraint function. The third constraint function indicates that the first capacity group of the communication base station energy system is the same as the configured capacity group of the communication base station energy system under extreme climate scenarios. The fourth constraint function is used to indicate that the second capacity group of the communication base station energy system within a time period is less than or equal to the first capacity group under extreme climate scenarios. The second capacity planning model of the communication base station energy system includes a first objective function, a first constraint function, a second constraint function, a third constraint function, and a fourth constraint function; Based on the target operation parameter data and the second capacity planning model, plan the configured capacity group of the communication base station energy system.

5. The method according to claim 4, wherein The planning of the configured capacity group of the communication base station energy system based on the target operation parameter data and the second capacity planning model includes: Based on the second capacity planning model, construct a third capacity planning model. The third capacity planning model includes a second objective function with the minimum annualized cost of the communication base station energy system as the target, the first constraint function, the second constraint function, and the fourth constraint function. The second objective function is the Lagrangian function under the third constraint function; Based on the target operation parameter data and the third capacity planning model, plan the configured capacity group of the communication base station energy system.

6. The method according to claim 5, wherein The planning of the configured capacity group of the communication base station energy system based on the target operation parameter data and the third capacity planning model includes: Initialize the Lagrangian multiplier group in the second objective function. The Lagrangian multiplier group includes Lagrangian multipliers related to the DC superimposed optical system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group respectively. The first Lagrangian multiplier related to the DC superimposed optical system is initialized to the photovoltaic power generation of the DC superimposed optical system under extreme climate scenarios. The photovoltaic power generation is determined based on the target illumination data of the DC superimposed optical system in the target operation parameter data. The other Lagrangian multipliers in the Lagrangian multiplier group except the first Lagrangian multiplier are initialized to 0; Substitute the target operation parameter data into the third capacity planning model, and sequentially solve the solution of the configured capacity group in the third capacity planning model. Based on the error between the obtained configured capacity group and the first capacity group, update the Lagrangian multiplier group; When the obtained configured capacity group satisfies the third constraint function, output the configured capacity group of the communication base station energy system.

7. The method according to claim 3, wherein The construction of the target operation parameter data of the communication base station energy system under K extreme climate scenarios based on the historical operation parameter data includes: Cluster the historical illumination data of the DC superimposed optical system in the historical operation parameter data to obtain the target illumination data of the DC superimposed optical system under K extreme climate scenarios corresponding to K clusters; Based on the historical operation parameter data, construct the target operation parameter data of the K extreme climate scenarios corresponding to the K clusters. The target operation parameter data includes the target illumination data.

8. A capacity planning device, characterized in that, The device is applied to the energy system of a communication base station. The energy system of the communication base station includes a DC optical superposition system, a battery pack, a hydrogen fuel cell, and a hydrogen storage bottle group. The energy system of the communication base station powers the devices of the communication base station through the DC optical superposition system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group. The device includes: An acquisition module, configured to acquire historical operation parameter data of the energy system of the communication base station; A scenario construction module, configured to construct target operation parameter data of the energy system of the communication base station under K extreme climate scenarios based on the historical operation parameter data, where K is a positive integer; A planning module, configured to plan the configuration capacity group of the energy system of the communication base station based on the target operation parameter data and a pre-constructed first capacity planning model. The configuration capacity group includes the configuration capacities of the DC optical superposition system, the battery pack, the hydrogen fuel cell, and the hydrogen storage bottle group; Wherein, the first capacity planning model includes a first objective function, a first constraint function, and a second constraint function with the minimization of the annualized cost of the energy system of the communication base station as the target. The annualized cost is related to the configuration capacity group of the energy system of the communication base station. The first constraint function is used to indicate the balance between the power consumption of the communication base station in an extreme scenario and the power supply of the energy system of the communication base station. The second constraint function is used to indicate that the difference in the reserve amount of the energy storage group in adjacent time periods in an extreme scenario is equal to the consumption amount of the energy storage group. The energy storage group includes the hydrogen storage bottle group and the battery pack.

9. An electronic device, characterized in that, The electronic device includes a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the capacity planning method according to any one of claims 3 to 7 are implemented.

10. A readable storage medium, characterized in that, A computer program is stored on the readable storage medium. When the computer program is executed by a processor, the steps of the capacity planning method according to any one of claims 3 to 7 are implemented.

11. A computer program product, characterized in that, It includes computer instructions. When the computer instructions are executed by a processor, the steps of the capacity planning method according to any one of claims 3 to 7 are implemented.

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