Energy storage configuration suggestion generation method, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses an energy storage configuration suggestion generation method, electronic equipment and a storage medium. The method comprises the steps that under the condition that configuration requirement description is obtained, a trained suggestion generation model is obtained, and the configuration requirement description is obtained by describing the configuration requirement of target energy storage to be configured; and inputting the configuration demand description into the suggestion generation model, and generating a target configuration suggestion for configuring the target energy storage according to a model output result output by the suggestion generation model. According to the technical scheme provided by the embodiment of the invention, the energy storage configuration suggestion can be accurately and efficiently generated.

Description

Technical Field

[0001] The present invention relates to the field of energy storage configuration technology, and in particular to a method for generating energy storage configuration suggestions, an electronic device, and a storage medium. Background Technology

[0002] Photovoltaic energy storage systems, through the "photovoltaic power generation + energy storage regulation" model, can realize the spatial and temporal transfer of electricity, improve the renewable energy absorption rate, and reduce the peak-shaving pressure on the power grid. As the advantages of photovoltaic energy storage systems become apparent, they are gradually becoming an important electricity choice for some households and industrial and commercial users.

[0003] The energy storage configuration adopted in a photovoltaic energy storage system directly determines the economic efficiency, safety, and environmental adaptability of the entire life cycle of the photovoltaic energy storage system. Therefore, generating scientific and reasonable energy storage configuration recommendations is a crucial decision-making step for users during the installation of photovoltaic energy storage systems.

[0004] However, the current difficulty in generating accurate and efficient energy storage configuration recommendations urgently needs to be addressed. Summary of the Invention

[0005] This invention provides a method, electronic device, and storage medium for generating energy storage configuration recommendations, so as to achieve accurate and efficient generation of energy storage configuration recommendations.

[0006] According to one aspect of the present invention, a method for generating energy storage configuration recommendations is provided, which may include:

[0007] Given the configuration requirement description, obtain the trained suggestion generation model. The configuration requirement description is obtained by describing the configuration requirements of the target energy storage to be configured.

[0008] The configuration requirements are described and input into the suggestion generation model. Based on the model output, the target configuration suggestions for the target energy storage are generated.

[0009] According to another aspect of the present invention, an electronic device is provided, which may include:

[0010] At least one processor; and

[0011] A memory that is communicatively connected to at least one processor; wherein,

[0012] The memory stores a computer program that can be executed by at least one processor, such that when the at least one processor executes the program, it implements the energy storage configuration suggestion generation method provided in any embodiment of the present invention.

[0013] According to another aspect of the present invention, a computer-readable storage medium is provided having computer instructions stored thereon for causing a processor to execute and implement the energy storage configuration suggestion generation method provided in any embodiment of the present invention.

[0014] The technical solution of this invention, upon obtaining a configuration requirement description of the target energy storage to be configured, acquires a trained suggestion generation model to facilitate the automatic and accurate generation of target configuration suggestions. The configuration requirement description is input into the suggestion generation model, and based on the model output, target configuration suggestions for the target energy storage are automatically generated. This technical solution, by automatically generating target configuration suggestions through a suggestion generation model, avoids the impact of the difficulty and low accuracy of manual analysis on the speed and accuracy of energy storage configuration suggestion generation, thereby achieving accurate and efficient generation of energy storage configuration suggestions.

[0015] It should be understood that the description in this section is not intended to identify key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a method for generating energy storage configuration suggestions according to an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of another method for generating energy storage configuration suggestions according to an embodiment of the present invention;

[0019] Figure 3 This is a flowchart of another energy storage configuration suggestion generation method provided by an embodiment of the present invention;

[0020] Figure 4 This is a structural block diagram of an energy storage configuration suggestion generation device according to an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the energy storage configuration suggestion generation method of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. The same applies to "target," "original," etc., and will not be repeated here. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] Before introducing the embodiments of the present invention, the implementation process of the current scheme for generating energy storage configuration suggestions and the reasons for the difficulty in generating accurate and efficient energy storage configuration suggestions will be explained by way of example, so as to better understand why the scheme proposed in the embodiments of the present invention can achieve accurate and efficient generation of energy storage configuration suggestions.

[0025] Currently, energy storage configuration recommendations are mostly generated manually. For example, professional engineers communicate with users to understand their energy storage configuration needs. Based on the communication with users, the professional engineers use spreadsheet software (Excel) or professional software to manually calculate and analyze the possible energy storage configurations. Then, they generate energy storage configuration recommendations based on the calculated configurations. However, this method has problems such as high communication costs, difficulty in manual analysis, slow speed, and easy to make analysis errors, which makes it difficult to generate accurate and efficient energy storage configuration recommendations.

[0026] To address this, this invention utilizes a suggestion generation model to automatically generate target configuration suggestions. This avoids the impact of the difficulty and low accuracy of manual analysis on the speed and accuracy of energy storage configuration suggestion generation, thereby achieving accurate and efficient generation of energy storage configuration suggestions. This will be explained in detail below.

[0027] Figure 1This is a flowchart illustrating a method for generating energy storage configuration recommendations according to an embodiment of the present invention. This embodiment is applicable to the generation of energy storage configuration recommendations, particularly in the design of distributed photovoltaic energy storage systems for generating energy storage configuration recommendations for the energy storage to be designed. This method can be executed by the energy storage configuration recommendation generation device provided in this embodiment of the present invention. This device can be implemented in software and / or hardware, and can be integrated into an electronic device, which can be various user terminals or servers.

[0028] See Figure 1 The method of this invention specifically includes the following steps:

[0029] S110. Given the configuration requirement description, obtain the trained suggestion generation model, wherein the configuration requirement description is obtained by describing the configuration requirements of the target energy storage to be configured.

[0030] The configuration requirement description can be understood as a description of the configuration requirements of the target energy storage to be configured; the configuration requirement description can exist in the form of natural language.

[0031] Target energy storage can be understood as energy storage to be configured; target energy storage can be combined with target photovoltaic to form a photovoltaic energy storage system.

[0032] In this embodiment of the invention, obtaining the configuration requirement description may involve obtaining the configuration requirement description described by the user in natural language.

[0033] The suggestion generation model can be understood as a model used to generate target configuration suggestions. The suggestion generation model can be a Large Language Model (LLM) obtained after optimization and selection. The suggestion generation model can integrate considerations of at least one of the following: the target photovoltaic capacity and power, power and daily load curves, expected discharge duration, investment constraints (energy storage budget), and grid connection compliance (grid connection form), etc., to generate energy storage suggestions. The suggestion generation model can be a local quantization model to ensure that no data is transmitted during the use of the suggestion generation model, thereby ensuring user privacy. Moreover, the quantization model can output in real time (a progressive output derivation process) to improve user experience.

[0034] In this embodiment of the invention, a suggested generation model can be obtained after obtaining a description of the configuration requirements.

[0035] S120. Input the configuration requirement description into the suggestion generation model, and generate the target configuration suggestion for the target energy storage based on the model output result of the suggestion generation model.

[0036] The model output can be understood as the suggested model output.

[0037] Target configuration recommendations can be understood as recommendations on the configuration parameters of a target energy storage system; target configuration recommendations can be recommendations described in natural language; target configuration recommendations can include configuration parameters such as energy storage type and grid connection mode; target configuration recommendations can be, for example, recommendations that meet preset conditions such as 80 words.

[0038] In this embodiment of the invention, the configuration requirements description can be input into the suggestion generation model, and the target configuration suggestion can be generated based on the model output.

[0039] For example, the configuration requirement is described as "I have a 15kW photovoltaic system and want to use electricity for 4 hours at night." This configuration requirement description is input into the suggestion generation model. The suggestion generation model parses the configuration requirement description through the description parsing module, obtaining a photovoltaic capacity of 15kW and a desired discharge time of 4 hours. Through the type determination module, it obtains the electricity consumption as 3kW and calculates the required energy as 12kWh, thus calculating a recommended battery capacity of 16.3kWh. All candidate energy storage types with supported battery capacities greater than 16.3kWh are selected as potential energy storage types. At least one potential energy storage type is scored, obtaining a score result for each candidate energy storage type. The candidate energy storage type with the highest score among the at least one potential energy storage type is lithium iron phosphate (LiFePO4). (its scoring results) Its score of 0.86 is higher than the 0.73 score of other candidate energy storage types, such as Nickel Manganese Cobalt (NMC). As the target energy storage type, an initial configuration suggestion is generated based on the target energy storage type. This initial configuration suggestion is then output as the model output result, and a target configuration suggestion is generated based on the model output result.

[0040] In this embodiment of the invention, the proposed generation model can not only output the model output results, but also the derivation process of the proposed generation model (such as the formula derivation process and configuration rationale) and the assumptions (at least one of the parameters used in the derivation process of the proposed generation model, such as photovoltaic capacity, expected discharge duration, battery round-trip efficiency, and allowable discharge depth). This is to facilitate the generation of target configuration suggestions based on the model output results, derivation process, and assumptions, or to provide the derivation process and assumptions when providing target configuration suggestions to users, so that users can understand the process of generating target configuration suggestions through an interpretable derivation process and assumptions.

[0041] It should be noted that, based on the solutions of the embodiments of the present invention, a natural language energy storage configuration suggestion generation assistant platform can be built. Through this platform, a question-and-answer service can be provided to users, which automatically outputs target configuration suggestions including energy storage type, recommended battery capacity and grid connection mode based on the user's natural language configuration requirement description.

[0042] The solution in this embodiment of the invention generates energy storage configuration suggestions through a suggestion generation model, which has language understanding and knowledge reasoning capabilities. Therefore, the solution in this embodiment of the invention can not only generate accurate and efficient energy storage configuration suggestions, but also obtain target configuration suggestions including executable configuration parameters based on a conversational description of configuration requirements, and supports personalized generation of energy storage configuration suggestions.

[0043] The technical solution of this invention, upon obtaining a configuration requirement description of the target energy storage to be configured, acquires a trained suggestion generation model to facilitate the automatic and accurate generation of target configuration suggestions. The configuration requirement description is input into the suggestion generation model, and based on the model output, target configuration suggestions for the target energy storage are automatically generated. This technical solution, by automatically generating target configuration suggestions through a suggestion generation model, avoids the impact of the difficulty and low accuracy of manual analysis on the speed and accuracy of energy storage configuration suggestion generation, thereby achieving accurate and efficient generation of energy storage configuration suggestions.

[0044] Figure 2 This is a flowchart of another energy storage configuration suggestion generation method provided in this embodiment of the invention. This embodiment is based on the above-mentioned technical solutions and optimized. In this embodiment, optionally, the target energy storage is powered by the target photovoltaic power generation, and the suggestion generation model includes a description parsing module, a type determination module, and a suggestion generation module; the suggestion generation model generates energy storage configuration suggestions in the following manner: the description parsing module parses the configuration requirement description to obtain the expected discharge duration of the target energy storage; the type determination module determines the target energy storage type from at least one alternative energy storage type based on the expected discharge duration; the suggestion generation module generates an initial configuration suggestion for configuring the target energy storage based on the target energy storage type, and outputs the initial configuration suggestion as the model output result. The explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0045] See Figure 2 The method in this embodiment may specifically include the following steps:

[0046] S210. Given the configuration requirement description, obtain the trained suggestion generation model. The configuration requirement description is obtained by describing the configuration requirements of the target energy storage to be configured. The target energy storage is powered by the target photovoltaic. The suggestion generation model includes a description parsing module, a type determination module, and a suggestion generation module.

[0047] Here, the target photovoltaic (PV) can be understood as the PV that supplies power to the target energy storage; the target PV can be a PV with a determined PV configuration, so that the energy storage configuration suggestion can be generated through the PV configuration of the already configured target PV (which may include PV capacity and other configurations).

[0048] It should be noted that the target energy storage can be powered by the target photovoltaic system, but it can also be powered by the power grid or other sources.

[0049] The description parsing module can be understood as a module used to parse the configuration requirement description.

[0050] The type determination module can be understood as a module used to determine the target energy storage type.

[0051] The suggestion generation module can be understood as a module used to generate initial configuration suggestions.

[0052] S220. Input the configuration requirement description into the suggestion generation model so that the suggestion generation model can generate energy storage configuration suggestions through steps S2201-S2203.

[0053] S2201. The configuration requirement description is parsed through the description parsing module to obtain the expected discharge duration of the target energy storage.

[0054] The expected discharge duration can be understood as the expected duration of the target energy storage discharge. Specifically, the expected discharge duration can be the expected continuous discharge duration. The unit of the expected discharge duration can be, for example, hours (h).

[0055] In this embodiment of the invention, the configuration requirement description can be parsed using a description parsing module to obtain the expected discharge duration. For example, the configuration requirement description can be parsed using the description parsing module to extract the entities in the configuration requirement description, and the expected discharge duration can be determined based on the entities. It should be noted that the entities mentioned above can include not only the expected discharge duration, but also other content such as photovoltaic capacity, energy storage usage scenario (residential or commercial scenario using the target energy storage), battery round-trip efficiency, and allowable depth of discharge, so as to determine the target energy storage type from at least one alternative energy storage type based on other content and the expected discharge duration.

[0056] S2202. Through the type determination module, determine the target energy storage type from at least one alternative energy storage type based on the expected discharge duration.

[0057] Among them, the alternative energy storage type can be understood as the energy storage type that is selected as the target energy storage type.

[0058] The target energy storage type can be understood as the energy storage type recommended for the target energy storage configuration; the essence of the target energy storage type can be the battery type recommended for the target energy storage battery configuration.

[0059] In this embodiment of the invention, a type determination module can determine a target energy storage type from at least one candidate energy storage type based on the desired discharge duration. For example, the type determination module can determine a target energy storage type whose discharge conditions meet the desired discharge duration from at least one candidate energy storage type.

[0060] S2203. Through the suggestion generation module, generate initial configuration suggestions for the target energy storage based on the target energy storage type, and output the initial configuration suggestions as the model output results.

[0061] The initial configuration suggestion can be understood as a configuration suggestion for the target energy storage generated by the suggestion generation module based on the target energy storage type.

[0062] In this embodiment of the invention, a suggestion generation module can generate initial configuration suggestions based on the target energy storage type, and output these initial configuration suggestions as model output results. For example, based on the target energy storage type, a Chinese paragraph at the Common European Framework of Reference for Languages ​​(CEFR) B1 level can be generated as an initial configuration suggestion, and this initial configuration suggestion can be output as model output results.

[0063] S230. Based on the model output results generated by the suggested model, generate target configuration suggestions for the target energy storage.

[0064] In this embodiment of the invention, target configuration suggestions can be generated based on the model output. For example, the initial configuration suggestions in the model output can be directly used as target configuration suggestions.

[0065] The technical solution of this invention involves target energy storage powered by a target photovoltaic system. The proposed energy storage configuration recommendation model includes a description parsing module, a type determination module, and a recommendation generation module. The model generates energy storage configuration recommendations as follows: the description parsing module parses the configuration requirement description to obtain the expected discharge duration of the target energy storage; the type determination module determines the target energy storage type from at least one alternative energy storage type based on the expected discharge duration; and the recommendation generation module generates an initial configuration recommendation for the target energy storage based on the target energy storage type, and outputs this initial configuration recommendation as the model output. This technical solution, by generating energy storage configuration recommendations based on the parsed expected discharge duration, ensures that the discharge duration of the target energy storage configured according to the target configuration recommendation meets user expectations, thereby improving the user experience.

[0066] An optional technical solution involves parsing the configuration requirement description using a description parsing module to obtain the expected discharge duration of the target energy storage. This includes: parsing the configuration requirement description using the description parsing module to obtain the photovoltaic capacity of the target photovoltaic and the expected discharge duration of the target energy storage; generating initial configuration suggestions for configuring the target energy storage based on the target energy storage type, including: obtaining the daily load curve and irradiance curve of the target photovoltaic, and determining the energy storage supply and demand situation of the target energy storage using the target energy storage type based on the photovoltaic capacity, daily load curve, irradiance curve, and target energy storage type; determining the recommended grid connection mode for the target energy storage based on the energy storage supply and demand situation, and generating initial configuration suggestions for configuring the target energy storage based on the target energy storage type and grid connection mode.

[0067] Photovoltaic capacity can be understood as the capacity of the target photovoltaic system, and it can also refer to the installed power of the target photovoltaic system; the unit of photovoltaic capacity can be kW.

[0068] In this embodiment of the invention, the configuration requirement description can be parsed by the description parsing module to obtain the photovoltaic capacity and the expected discharge duration.

[0069] The daily load curve can be understood as the curve of how the power of the electricity load served by the target photovoltaic system changes over time within a 24-hour period of a day.

[0070] The irradiance curve can be understood as the curve showing how the power of solar radiation received by the target photovoltaic unit changes over time.

[0071] In this embodiment of the invention, daily load curves and irradiance curves can be obtained. For example, the photovoltaic location information of the target photovoltaic unit can be determined, and the daily load curve and irradiance curve can be obtained based on the photovoltaic location information. Specifically, for example, the photovoltaic location information of the target photovoltaic unit can be determined, the region index z of the region to which the photovoltaic location information belongs can be determined, and the daily load curve corresponding to the region can be determined from a typical daily load curve library based on z. Furthermore, based on z, the corresponding irradiance curve for the region is determined from the typical irradiance curve library. .

[0072] Energy storage supply and demand can be understood as the supply and demand of electricity for the target energy storage using the target energy storage type. That is, if the energy storage supply and demand is greater than 0, it means that the target energy storage can supply electricity. If the energy storage supply and demand is less than 0, it means that electricity needs to be purchased to supply electricity to the target energy storage. Energy storage supply and demand can also be understood as the net power of the target energy storage in 24 hours of a day. For example, the energy storage supply and demand can include the net power of the target energy storage at each time of day in 24 hours.

[0073] In this embodiment of the invention, the energy storage supply and demand situation can be determined based on photovoltaic capacity, daily load curve, irradiance curve, and target energy storage type. For example, the battery charging power curve and battery discharging power curve of the energy storage battery corresponding to the target energy storage type can be determined (e.g., the battery discharging power curve corresponding to the target energy storage type is determined based on at least one of the daily load curve, expected discharge duration, and electricity consumption, and the battery charging power curve corresponding to the target energy storage type is determined based on the irradiance curve); the energy storage supply and demand situation is determined based on photovoltaic capacity, daily load curve, irradiance curve, battery charging power curve, and battery discharging power curve.

[0074] In this embodiment of the invention, an example is given of the process of determining the energy storage supply and demand situation based on photovoltaic capacity, daily load curve, irradiance curve, battery charging power curve, and battery discharging power curve. For example, the energy storage supply and demand situation can be determined based on photovoltaic capacity, daily load curve, irradiance curve, battery charging power curve, and battery discharging power curve using formulas. To determine the supply and demand situation of energy storage, among which, The net power at time t (the net power at each time point constitutes the energy storage supply and demand situation). The output power of the target photovoltaic at time t is determined by the photovoltaic capacity and irradiance curves. The load power at time t (the load power at time t in the daily load curve); Let t be the battery discharge power at time t (the battery discharge power at time t in the battery discharge power curve). This refers to the battery charging power at time t (the battery charging power at time t in the battery charging power curve). It should be noted that the above... It can be estimated based on the photovoltaic capacity versus normalized irradiance curve, that is... (This formula gives the approximate output power of the target photovoltaic array under different irradiation conditions.) For photovoltaic capacity, The relative irradiance of the target photovoltaic at time t is the value between 0 and 1 (the irradiance at time t in the irradiance curve). As the photovoltaic capacity increases, the maximum output power of the target photovoltaic during the peak irradiance period also increases.

[0075] The grid connection method can be understood as the recommended grid connection method for the target energy storage.

[0076] The technical solution of this invention can parse the configuration requirement description through a description parsing module to obtain the photovoltaic capacity and expected discharge duration, then obtain the daily load curve and irradiance curve, and determine the energy storage supply and demand situation based on the photovoltaic capacity, daily load curve, irradiance curve and target energy storage type. Finally, based on the energy storage supply and demand situation, the grid connection mode is determined, and an initial configuration suggestion is generated based on the target energy storage type and grid connection mode, thereby improving the comprehensiveness of the generated initial configuration suggestion.

[0077] Based on the above scheme, another optional technical solution is to determine the grid connection mode recommended for the target energy storage according to the energy storage supply and demand situation, including: determining the rated power of the inverter for the target energy storage using the target energy storage type according to the energy storage supply and demand situation; and determining the grid connection mode recommended for the target energy storage according to the rated power of the inverter.

[0078] The rated power of an inverter can be understood as the rated power of the inverter used in the target energy storage; the unit of rated power of an inverter can be kW.

[0079] It is understandable that the inverter's rated power must cover the maximum net power that the target energy storage may experience at any given time (the maximum net power is the net power with the largest absolute value among the net powers corresponding to each time point in the energy storage supply and demand situation) to ensure that the inverter will not overload under various operating scenarios such as high irradiance, high load, or energy storage charging and discharging. Therefore, in this embodiment of the invention, the inverter's rated power can be determined according to the energy storage supply and demand situation. For example, considering that during periods of high sunlight, a larger photovoltaic output will increase the positive power exchange between the photovoltaic energy storage system and the grid, the absolute value of the maximum net power may further increase when there is low load or the battery is charging simultaneously. The absolute value of the maximum net power reflects the scale of bidirectional power exchange that the inverter needs to withstand at the corresponding time. The increase in the absolute value of the maximum net power means that the inverter needs to withstand a larger instantaneous power at the most unfavorable time. Therefore, the inverter's rated power must be increased synchronously to avoid overload. Thus, the inverter's rated power can be determined to ensure that the inverter's rated power... Greater than or equal to the absolute value of the maximum net power, that is .

[0080] For example, if a target object is configured with a target photovoltaic system of 15 kW, then the photovoltaic capacity is 15 kW. Under typical sunny day peak irradiance conditions, it can be approximated as... ≈1, ≈15kW, meaning the target photovoltaic system may reach full output at certain times. In this scenario, the net power output could be the difference between the target photovoltaic system's full power output and the partial load power, or even higher (if the battery is simultaneously fast charging). To ensure the inverter can handle the maximum energy flow from the target photovoltaic system in this situation, its rated power should at least meet the following requirements. ≥15kW.

[0081] In this embodiment of the invention, considering that some regional grid connection regulations also have requirements for the ratio of photovoltaic capacity to inverter capacity, such as allowing the inverter capacity to be configured between 0.8 and 1.0 of the photovoltaic capacity, or limiting the maximum capacity of a single-phase inverter according to local low-voltage grid connection rules, the rated power of the inverter needs to meet the following requirements: It is also necessary to comprehensively determine the results based on the region's grid connection system, inverter conversion efficiency, protection configuration, and application scenarios.

[0082] In this embodiment of the invention, the grid connection mode can be determined based on the inverter's rated power. For example, if the inverter's rated power is less than a preset power (e.g., 10kW), the grid connection mode can be determined to be single-phase; if the inverter's rated power is greater than or equal to the preset power, the grid connection mode can be determined to be three-phase.

[0083] In this embodiment of the invention, the recommended off-grid topology for the target energy storage can also be determined based on the inverter's rated power.

[0084] The solution of this invention can determine the rated power of the inverter based on the energy storage supply and demand situation, and then determine the grid connection mode based on the rated power of the inverter. This can ensure that the inverter configured for the target energy storage based on the target configuration recommendation obtained on the basis of the grid connection mode can handle the situation where the target photovoltaic output is large and power is supplied to the load or target energy storage during the entire operation cycle, as well as the most unfavorable power scenarios such as load dominance, low target photovoltaic output and the need for supplemental power for target energy storage, thereby ensuring the stability and security of the energy flow of target energy storage.

[0085] Figure 3This is a flowchart of another energy storage configuration suggestion generation method provided in this embodiment of the invention. This embodiment is based on and optimized from the above-mentioned technical solutions. In this embodiment, optionally, determining the target energy storage type from at least one candidate energy storage type according to the expected discharge duration includes: obtaining the electricity consumption of the target object to which the target photovoltaic belongs, and determining the required energy of the target object based on the electricity consumption and the expected discharge duration; determining the target energy storage type from at least one candidate energy storage type based on the required energy. The explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0086] See Figure 3 The method in this embodiment may specifically include the following steps:

[0087] S310. Given the configuration requirement description, obtain the trained suggestion generation model. The configuration requirement description is obtained by describing the configuration requirements of the target energy storage to be configured. The target energy storage is powered by the target photovoltaic. The suggestion generation model includes a description parsing module, a type determination module, and a suggestion generation module.

[0088] S320. Input the configuration requirement description into the suggestion generation model so that the suggestion generation model can generate energy storage configuration suggestions through steps S3201-S3204.

[0089] S3201. The configuration requirement description is parsed through the description parsing module to obtain the expected discharge duration of the target energy storage.

[0090] S3202. Through the type determination module, obtain the power consumption information of the target object to which the target photovoltaic belongs, and determine the required energy for the target object's power consumption based on the power consumption information and the expected discharge duration.

[0091] The target object can be understood as the object to which the target photovoltaic belongs, or as the object to which the target energy storage needs to be configured.

[0092] Electricity usage can be understood as the electricity usage of the target object; for example, electricity usage can be the usage of electrical appliances by the target object; electricity usage can include the average load power (in kW) of the target object's nighttime electricity consumption.

[0093] In this embodiment of the invention, electricity consumption information can be obtained. For example, historical nighttime electricity consumption information of a target object can be obtained (the historical information may include, for example, the historical load power of the target object's historical nighttime electricity consumption). Based on the historical information, the electricity consumption information can be determined (for example, the average nighttime load power can be determined as the electricity consumption information based on the historical load power) for acquisition purposes.

[0094] Energy demand can be understood as the energy required for the electricity consumption of a target object, or as the energy required for the electrical load of a target object; the unit of energy demand can be kWh.

[0095] In this embodiment of the invention, the required energy can be determined based on electricity consumption and the expected discharge duration. For example, it can be determined based on the average nighttime load power in the electricity consumption data. and expected discharge duration Through formula Determine the required energy .

[0096] S3203. Through the type determination module, determine the target energy storage type from at least one alternative energy storage type based on the required energy.

[0097] In this embodiment of the invention, a type determination module can determine a target energy storage type from at least one candidate energy storage type based on the required energy. For example, the type determination module can determine a target energy storage type from at least one candidate energy storage type whose power supply can meet the required energy.

[0098] S3204. Through the suggestion generation module, generate initial configuration suggestions for the target energy storage based on the target energy storage type, and output the initial configuration suggestions as the model output results.

[0099] S330. Based on the model output results generated by the recommendations, generate target configuration recommendations for the target energy storage.

[0100] The technical solution of this invention involves obtaining the electricity consumption information of the target photovoltaic object, and determining the required energy for the target object's electricity consumption based on the electricity consumption information and the expected discharge duration. Based on the required energy, a target energy storage type is determined from at least one alternative energy storage type. This technical solution generates energy storage configuration suggestions based on the determined required energy, ensuring that the target energy storage configured according to the suggested configuration meets the user's electricity consumption needs, thereby improving the user experience.

[0101] An optional technical solution involves parsing the configuration requirement description to obtain the expected discharge duration of the target energy storage, including: parsing the configuration requirement description to obtain the energy storage budget and the expected discharge duration of the target energy storage; determining the target energy storage type from at least one alternative energy storage type based on the required energy, including: determining at least one candidate energy storage type from at least one alternative energy storage type based on the required energy; scoring the at least one candidate energy storage type based on the energy storage budget and the performance of the energy storage type corresponding to the at least one candidate energy storage type, obtaining the scoring results corresponding to the at least one candidate energy storage type; and determining the target energy storage type from the at least one candidate energy storage type based on the scoring results corresponding to the at least one candidate energy storage type.

[0102] The energy storage budget can be understood as the budget for deploying the target energy storage; the energy storage budget may include budgets for purchasing the target energy storage, configuring the target energy storage, and using the target energy storage, etc.

[0103] In this embodiment of the invention, the configuration requirement description can be parsed to obtain the energy storage budget and the expected discharge duration.

[0104] The candidate energy storage type can be understood as the energy storage type that is to be used as the target energy storage type; at least one alternative energy storage type includes at least one candidate energy storage type.

[0105] In this embodiment of the invention, at least one candidate energy storage type can be determined from at least one alternative energy storage type based on the required energy. For example, at least one candidate energy storage type that can supply power to meet the required energy can be determined from at least one alternative energy storage type.

[0106] Energy storage type performance can be understood as the performance of the energy storage corresponding to the selected energy storage type. Energy storage type performance may include, for example, the number of battery cycles supported, the allowable operating temperature range of the battery, and the estimated cost of the energy storage type.

[0107] The scoring results can be understood as the results obtained by scoring the corresponding candidate energy storage types.

[0108] In this embodiment of the invention, at least one candidate energy storage type can be scored based on the energy storage budget and the performance of each candidate energy storage type, resulting in a score for each candidate energy storage type. For example, for each candidate energy storage type, the battery cycle life can be determined based on the energy storage budget cost and the battery cycle life of each candidate energy storage type's performance. Battery operating temperature range and estimated costs Through formula The candidate energy storage types are scored separately to obtain the corresponding score results for each candidate energy storage type. ,in, , and The weights for these factors are the number of battery cycles supported, the battery's allowable operating temperature range, and cost. , and For example, they could be 0.4, 0.3, and 0.3 respectively. The maximum number of battery cycles supported, for each of the at least one candidate energy storage type. This refers to the maximum allowable battery operating temperature range among the allowable battery operating temperature ranges corresponding to at least one candidate energy storage type.

[0109] In this embodiment of the invention, a target energy storage type can be determined from at least one candidate energy storage type based on the scoring results corresponding to each of the at least one candidate energy storage type. For example, the candidate energy storage type corresponding to the highest scoring result among the scoring results corresponding to each of the at least one candidate energy storage type can be used as the target energy storage type.

[0110] The technical solution of this invention analyzes the configuration requirement description to obtain the energy storage budget and expected discharge duration. Then, based on the required energy, at least one candidate energy storage type is determined from at least one alternative energy storage type. The at least one candidate energy storage type is scored according to the energy storage budget and the performance of the energy storage type corresponding to each candidate energy storage type, resulting in a score for each candidate energy storage type. Finally, based on the score results of each candidate energy storage type, a target energy storage type is determined from the at least one candidate energy storage type. This allows for a two-level screening process using the required energy, energy storage budget, and the performance of the energy storage type corresponding to each candidate energy storage type to select the target energy storage type. This results in a more accurate target energy storage type that better meets user needs.

[0111] Another alternative technical solution involves determining a target energy storage type from at least one alternative energy storage type based on the required energy, including: determining a recommended battery capacity for the battery used in the recommended target energy storage based on the required energy; and determining the target energy storage type from at least one alternative energy storage type based on the recommended battery capacity.

[0112] The recommended battery capacity can be understood as the battery capacity recommended for the target energy storage, and its unit can be kWh.

[0113] In this embodiment of the invention, considering that the energy utilization rate of the target energy storage battery may not be 100%, a recommended battery capacity can be determined based on the required energy. This determination of the recommended battery capacity is essentially a correction of the battery capacity corresponding to the required energy. For example, the recommended battery capacity can be determined based on the required energy, battery round-trip efficiency, and allowable depth of discharge. Specifically, for example, it can be determined based on the required energy... Battery round-trip efficiency And the depth of discharge (DOD), through the formula Determine the recommended battery capacity It should be noted that the battery round-trip efficiency and allowable depth of discharge mentioned above can be preset, for example, they can be preset. =0.92 and DOD=0.8; it can also be obtained by parsing the configuration requirement description.

[0114] In this embodiment of the invention, a target energy storage type can be determined from at least one alternative energy storage type based on the recommended battery capacity. For example, a target energy storage type that can be configured with the recommended battery capacity or has a configurable battery capacity larger than the recommended battery capacity can be determined from at least one alternative energy storage type.

[0115] The technical solution of this invention determines a recommended battery capacity based on the required energy, and then determines a target energy storage type from at least one alternative energy storage type based on the recommended battery capacity. This ensures that the determined target energy storage type can meet the requirements of the recommended battery capacity, thereby avoiding situations where the battery capacity of the target energy storage, configured according to the target configuration recommendation based on the recommended battery capacity, does not meet the user's usage needs.

[0116] Another optional technical solution suggests that the generated model also includes a confidence level determination module. The generated model further suggests that the confidence level of the model output result be determined and output in the following way: the confidence level determination module determines and outputs the confidence level based on the required energy; based on the model output result of the generated model, a target configuration suggestion for the target energy storage is generated, including: when the confidence level is greater than or equal to a preset confidence level threshold, a target configuration suggestion for the target energy storage is generated based on the model output result of the generated model.

[0117] The confidence level determination module can be understood as a module used to determine the confidence level.

[0118] Confidence level can be understood as the degree of confidence in the model's output.

[0119] In this embodiment of the invention, a confidence level determination module can determine and output the confidence level based on the required energy. For example, the confidence level determination module can determine the confidence level based on the required energy. Through formula Determine and output the confidence level Conf in the range of 0–1, where, The baseline difference between the energy storage configuration recommendations generated by the model and those generated by professional software is used to determine the energy storage configuration recommendations. This is used to suggest the average token confidence score of the output of the generative model.

[0120] The confidence threshold can be understood as the minimum confidence level of the preset target configuration suggestion; for example, the confidence threshold could be 0.85.

[0121] In this embodiment of the invention, when the confidence level is greater than or equal to the confidence threshold, a target configuration suggestion can be generated based on the model output. For example, if the confidence level is 0.89, which is greater than the confidence threshold of 0.85, then a target configuration suggestion can be generated based on the model output. When the confidence level is less than the confidence threshold, a prompt can be made to review the energy storage configuration suggestion.

[0122] The technical solution of this invention suggests that the generated model also determines and outputs the confidence level of the model output results in the following way: the confidence level determination module determines and outputs the confidence level based on the required energy; when the confidence level is greater than or equal to the confidence level threshold, a target configuration suggestion is generated based on the model output results, thus realizing confidence gating. That is, by generating the target configuration suggestion only when the confidence level is greater than the confidence level threshold, the determination of the illusion target configuration suggestion can be avoided, thereby improving the accuracy of the determined target configuration suggestion.

[0123] To better understand the technical solutions of the above embodiments of the present invention, an optional example is provided here. For example, when a configuration requirement description in natural language is obtained, a suggestion generation model is obtained; the configuration requirement description is input into the suggestion generation model, and the description parsing module parses the configuration requirement description to obtain the photovoltaic capacity, energy storage budget, and expected discharge duration; the capacity determination submodule in the type determination module obtains the electricity consumption situation and determines the required energy based on the electricity consumption situation and expected discharge duration; the capacity determination submodule in the type determination module determines the recommended battery capacity based on the required energy; the type selector in the type determination module determines at least one candidate energy storage type from at least one alternative energy storage type based on the recommended battery capacity; the type selector in the type determination module scores the at least one candidate energy storage type based on the energy storage budget and the performance of the energy storage type corresponding to each of the at least one candidate energy storage type, thereby obtaining at least one candidate energy storage type. The system generates the following modules: 1) Scoring results corresponding to each type; 2) Using the type selector in the type determination module, a target energy storage type is determined from at least one candidate energy storage type based on the scoring results corresponding to each candidate energy storage type; 3) Using the power and grid connection determination submodule in the suggestion generation module, daily load and irradiance curves are obtained, and the energy storage supply and demand situation is determined based on the photovoltaic capacity, daily load curve, irradiance curve, and target energy storage type; 4) Using the power and grid connection determination submodule in the suggestion generation module, the rated power of the inverter is determined based on the energy storage supply and demand situation; 5) Using the power and grid connection determination submodule in the suggestion generation module, the grid connection mode is determined based on the rated power of the inverter, and the suggestion generator in the suggestion generation module generates initial configuration suggestions based on the target energy storage type and grid connection mode, which are then output as model outputs; 6) Target configuration suggestions are generated based on the model outputs.

[0124] A comparative experiment was conducted to generate energy storage configuration recommendations for 50 cases using the above technical solution and the manual solution. The experimental results are shown in Table 1 below.

[0125] Table 1 Experimental Results

[0126]

[0127] The above technical solution can automate the entire process from natural language description of configuration requirements to generation of target configuration suggestions, thereby lowering the entry barrier for target configuration suggestion generation; it allows users to obtain complete target configuration suggestions within 30 seconds by simply providing a natural language description of configuration requirements; and it can ensure that the difference between the obtained target configuration suggestions and those calculated by professional software is less than or equal to 5%.

[0128] Figure 4This is a structural block diagram of an energy storage configuration suggestion generation device provided in an embodiment of the present invention. This device is used to execute the energy storage configuration suggestion generation method provided in any of the above embodiments. This device and the energy storage configuration suggestion generation method of the above embodiments belong to the same inventive concept. Details not described in detail in the embodiments of the energy storage configuration suggestion generation device can be found in the embodiments of the energy storage configuration suggestion generation method described above. See also... Figure 4 The device may specifically include: a suggestion generation model acquisition module 410 and a target configuration suggestion generation module 420.

[0129] Among them, the suggestion generation model acquisition module 410 is used to acquire the trained suggestion generation model when the configuration requirement description is obtained. The configuration requirement description is obtained by describing the configuration requirements of the target energy storage to be configured.

[0130] The target configuration suggestion generation module 420 is used to input the configuration requirement description into the suggestion generation model, and generate target configuration suggestions for the target energy storage based on the model output results of the suggestion generation model.

[0131] Optionally, the target energy storage is powered by the target photovoltaic system, and the proposed generation model includes a description parsing module, a type determination module, and a proposal generation module;

[0132] It is recommended that the energy storage configuration suggestions be generated through the following sub-modules:

[0133] The expected discharge duration submodule is used to parse the configuration requirement description through the description parsing module to obtain the expected discharge duration of the target energy storage.

[0134] The target energy storage type determination submodule is used to determine the target energy storage type from at least one alternative energy storage type based on the expected discharge duration, through the type determination module.

[0135] The model output result output submodule is used to generate initial configuration suggestions for the target energy storage based on the target energy storage type through the suggestion generation module, and output the initial configuration suggestions as the model output result.

[0136] Optionally, based on the above-described device, the target energy storage type determination submodule may include:

[0137] The energy demand determination unit is used to obtain the electricity consumption of the target object to which the target photovoltaic belongs, and to determine the energy demand required for the target object's electricity consumption based on the electricity consumption and the expected discharge duration.

[0138] The target energy storage type determination unit is used to determine the target energy storage type from at least one alternative energy storage type based on the energy demand.

[0139] Optionally, based on the above device, a sub-module for determining the desired discharge duration may include:

[0140] The expected discharge duration is obtained by parsing the configuration requirement description to obtain the energy storage budget and the expected discharge duration of the target energy storage.

[0141] The target energy storage type determination unit may include:

[0142] The candidate energy storage type determination sub-unit is used to determine at least one candidate energy storage type from at least one alternative energy storage type based on the required energy.

[0143] The scoring results are used to obtain sub-units, which are used to score at least one candidate energy storage type based on the energy storage budget and the performance of the energy storage type corresponding to at least one candidate energy storage type, and obtain the scoring results corresponding to at least one candidate energy storage type.

[0144] The target energy storage type determination sub-unit is used to determine the target energy storage type from at least one candidate energy storage type based on the scoring results corresponding to at least one candidate energy storage type.

[0145] Optionally, based on the above-described device, the target energy storage type determination unit may include:

[0146] The recommended battery capacity determination subunit is used to determine the recommended battery capacity for the target energy storage based on the required energy.

[0147] The target energy storage type determination sub-unit is used to determine the target energy storage type from at least one alternative energy storage type based on the recommended battery capacity.

[0148] Optionally, based on the above-mentioned apparatus, it is suggested that the generated model may also include a confidence determination module;

[0149] It is recommended that the generative model also determine and output the confidence level of the model output through the following sub-modules:

[0150] The confidence output submodule is used to determine and output the confidence level based on the required energy by the confidence level determination module.

[0151] Target configuration suggestion generation module 420 may include:

[0152] The target configuration suggestion generation submodule is used to generate target configuration suggestions for the target energy storage based on the model output results of the suggestion generation model when the confidence level is greater than or equal to the preset confidence level threshold.

[0153] Optionally, based on the above device, a sub-module for determining the desired discharge duration may include:

[0154] The expected discharge duration unit is used to parse the configuration requirement description through the description parsing module to obtain the photovoltaic capacity of the target photovoltaic and the expected discharge duration of the target energy storage.

[0155] The model output result output submodule may include:

[0156] The energy storage supply and demand determination unit is used to obtain the daily load curve and irradiance curve of the target photovoltaic, and determine the energy storage supply and demand of the target energy storage using the target energy storage type based on the photovoltaic capacity, daily load curve, irradiance curve and target energy storage type.

[0157] The initial configuration suggestion generation unit is used to determine the grid connection mode of the target energy storage based on the energy storage supply and demand situation, and to generate an initial configuration suggestion for the target energy storage based on the target energy storage type and grid connection mode.

[0158] Optionally, based on the above-described apparatus, the initial configuration suggestion generation unit may include:

[0159] The inverter rated power determination subunit is used to determine the rated power of the inverter for the target energy storage type based on the energy storage supply and demand situation.

[0160] The grid connection mode determination sub-unit is used to determine the recommended grid connection mode for the target energy storage based on the inverter's rated power.

[0161] The energy storage configuration suggestion generation device provided in this embodiment of the invention, through a suggestion generation model acquisition module, obtains a configuration requirement description derived from the configuration requirements of the target energy storage to be configured, and then acquires a trained suggestion generation model. This facilitates the automatic and accurate generation of target configuration suggestions through the suggestion generation model. The target configuration suggestion generation module inputs the configuration requirement description into the suggestion generation model and automatically generates target configuration suggestions for the target energy storage based on the model output. This device, by automatically generating target configuration suggestions through a suggestion generation model, avoids the impact of the difficulty and low accuracy of manual analysis on the speed and accuracy of energy storage configuration suggestion generation, thereby achieving accurate and efficient generation of energy storage configuration suggestions.

[0162] The energy storage configuration suggestion generation device provided in the embodiments of the present invention can execute the energy storage configuration suggestion generation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0163] It is worth noting that in the embodiments of the above-mentioned energy storage configuration suggestion generation device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0164] Figure 5 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0165] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0166] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0167] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the energy storage configuration recommendation generation method.

[0168] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0169] In some embodiments, the energy storage configuration recommendation generation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the energy storage configuration recommendation generation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the energy storage configuration recommendation generation method by any other suitable means (e.g., by means of firmware).

[0170] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0171] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0172] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0173] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0174] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0175] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0176] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0177] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for generating energy storage configuration suggestions, characterized in that, include: Given the configuration requirement description, a trained suggestion generation model is obtained, wherein the configuration requirement description is obtained by describing the configuration requirements of the target energy storage to be configured. The configuration requirements are described and input into the suggestion generation model. Based on the model output of the suggestion generation model, a target configuration suggestion for configuring the target energy storage is generated.

2. The method according to claim 1, characterized in that, The target energy storage is powered by the target photovoltaic power, and the proposed generation model includes a description parsing module, a type determination module, and a proposed generation module; The suggestion generation model generates energy storage configuration suggestions in the following manner: The configuration requirement description is parsed by the description parsing module to obtain the expected discharge duration of the target energy storage. The type determination module determines the target energy storage type from at least one candidate energy storage type based on the expected discharge duration. The suggestion generation module generates initial configuration suggestions for the target energy storage based on the target energy storage type, and outputs the initial configuration suggestions as the model output.

3. The method according to claim 2, characterized in that, The step of determining the target energy storage type from at least one candidate energy storage type based on the expected discharge duration includes: Obtain the electricity consumption status of the target object to which the target photovoltaic belongs, and determine the required energy for the target object's electricity consumption based on the electricity consumption status and the expected discharge duration; Based on the required energy, a target energy storage type is determined from at least one alternative energy storage type.

4. The method according to claim 3, characterized in that, The step of parsing the configuration requirement description to obtain the expected discharge duration of the target energy storage includes: The configuration requirement description is parsed to obtain the energy storage budget and the expected discharge duration of the target energy storage. The step of determining the target energy storage type from at least one alternative energy storage type based on the energy demand includes: Based on the energy demand, at least one candidate energy storage type is determined from at least one alternative energy storage type. Based on the energy storage budget and the performance of the energy storage type corresponding to at least one of the candidate energy storage types, the at least one candidate energy storage type is scored to obtain the scoring results corresponding to at least one candidate energy storage type. Based on the scoring results corresponding to at least one of the candidate energy storage types, a target energy storage type is determined from at least one candidate energy storage type.

5. The method according to claim 3, characterized in that, The step of determining the target energy storage type from at least one alternative energy storage type based on the energy demand includes: Based on the energy demand, determine the recommended battery capacity for the target energy storage battery; Based on the recommended battery capacity, a target energy storage type is determined from at least one alternative energy storage type.

6. The method according to claim 3, characterized in that, The suggestion generation model also includes a confidence determination module; The proposed model also determines and outputs the confidence level of the model's output in the following manner: The confidence level determination module determines and outputs the confidence level based on the required energy. The step of generating a target configuration recommendation for the target energy storage based on the model output result generated according to the recommendation includes: If the confidence level is greater than or equal to a preset confidence level threshold, the model output result of the proposed model output is used to generate a target configuration proposal for the target energy storage.

7. The method according to claim 2, characterized in that, The step of parsing the configuration requirement description through the description parsing module to obtain the expected discharge duration of the target energy storage includes: The configuration requirement description is parsed by the description parsing module to obtain the photovoltaic capacity of the target photovoltaic and the expected discharge duration of the target energy storage. The step of generating initial configuration suggestions for configuring the target energy storage based on the target energy storage type includes: Obtain the daily load curve and irradiance curve of the target photovoltaic, and determine the energy supply and demand situation of the target energy storage using the target energy storage type based on the photovoltaic capacity, the daily load curve, the irradiance curve and the target energy storage type. Based on the energy storage supply and demand situation, determine the recommended grid connection mode for the target energy storage, and generate an initial configuration recommendation for the target energy storage based on the target energy storage type and the grid connection mode.

8. The method according to claim 7, characterized in that, The step of determining the recommended grid connection method for the target energy storage based on the energy storage supply and demand situation includes: Based on the energy storage supply and demand situation, determine the rated power of the inverter for the target energy storage using the target energy storage type; Based on the rated power of the inverter, determine the recommended grid connection method for the target energy storage.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to cause the at least one processor to perform the energy storage configuration recommendation generation method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the energy storage configuration recommendation generation method as described in any one of claims 1-8.

Images