Energy storage system loss fitting modeling method, device and equipment and storage medium

Abstract

The invention provides an energy storage system loss fitting modeling method, device and equipment and a storage medium, which are applied to an energy storage system and comprise a grid-connected metering point, an alternating-current transformer, an energy storage converter and a battery, and electric energy charges the battery after passing through the grid-connected metering point, the alternating-current transformer and the energy storage converter. Or the electric energy of the battery is discharged outwards through the energy storage converter, the alternating-current transformer and the grid-connected metering point; comprising the following steps: obtaining corresponding discharging electric quantity and charging electric quantity of a grid-connected metering point monitoring battery, and calculating battery efficiency corresponding to an energy storage system according to the discharging electric quantity and the charging electric quantity of the battery; obtaining rectification efficiency and inversion efficiency corresponding to the energy storage converter, and calculating converter efficiency according to the rectification efficiency and the inversion efficiency; obtaining transformer efficiency corresponding to an AC transformer of the energy storage system; obtaining the power line efficiency corresponding to the energy storage system; and completing loss fitting modeling of the energy storage system according to the battery efficiency, the energy storage converter efficiency, the transformer efficiency and the power line efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of electric energy storage, and particularly relates to a method, device, equipment and storage medium for fitting and modeling the losses of an energy storage system. Background Art

[0002] The loss calculation of each component of the energy storage system is complex. Under the traditional method, the evaluation of the losses of the energy storage system is often based on the individual efficiency indexes of each component, and it is difficult to comprehensively consider the mutual influence between components and the overall loss situation under different working conditions. The efficiency of the energy storage system is jointly determined by multiple parts such as batteries, power conversion systems, power lines and transformers, and each part is affected by various factors. For example, the battery is affected by temperature, charge-discharge rate, etc., and the power conversion system is affected by the access voltage level, etc. This makes it challenging to accurately evaluate the losses of the energy storage system.

[0003] Currently, the research on the losses of the energy storage system focuses on certain specific aspects or theoretical models, which have a certain difference from the operation and application scenarios of the actual energy storage system, and cannot fully meet the requirements of accurately modeling the losses of the energy storage system in engineering practice, and it is difficult to effectively guide the optimization design and operation management of the energy storage system.

[0004] There are many deficiencies in the existing energy storage modeling in practical applications. Most of these models cannot comprehensively consider the loss situations of each link of the energy storage system, and there are obvious imperfections. Since the loss characteristics of components such as batteries, power conversion systems, power lines and transformers under different working conditions are not fully covered, it is difficult for them to be close to the actual operation of the energy storage system and cannot provide accurate and effective guidance for the optimization and management of the energy storage system.

[0005] At the same time, the losses of the energy storage system often appear as an important factor in the overall evaluation of the energy storage system. For occasions such as automatic optimization seeking with the goals of the overall system economy, safety, etc., if the losses of the energy storage system can be modeled and characterized by a continuous function with power as a variable, the convenience of processing can be improved. However, the efficiency of the energy storage converter is characterized in the form of discrete data, resulting in the discretization of the loss data of the energy storage system. How to approximately convert the discretized data into a continuous function for characterization is also an issue that needs to be focused on.

[0006] Therefore, there is an urgent need for a method for fitting and modeling the losses of an energy storage system to solve at least one of the above problems. Summary of the Invention

[0007] The present application provides a method, device, equipment and storage medium for loss fitting modeling of an energy storage system, aiming to solve the many deficiencies existing in the energy storage modeling in the market. Most of these models cannot comprehensively consider the loss conditions of each link of the energy storage system, and there are obvious imperfections. Due to the failure to fully cover the loss characteristics of components such as batteries, power conversion systems, power lines and transformers under different working conditions, it is difficult for them to be close to the actual operation of the energy storage system and cannot provide accurate and effective guidance for the optimization and management of the energy storage system.

[0008] In a first aspect, the present application provides a method for loss fitting modeling of an energy storage system, which is applied to an energy storage system. The energy storage system includes a grid connection metering point, an AC transformer, an energy storage converter and a battery. Electric energy is used to charge the battery after passing through the grid connection metering point, the AC transformer and the energy storage converter, or the electric energy of the battery is discharged externally through the energy storage converter, the AC transformer and the grid connection metering point. The method includes:

[0009] Obtain the discharge power and charge power of the battery corresponding to the grid connection metering point, and calculate the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery.

[0010] Obtain the transformer efficiency corresponding to the AC transformer of the energy storage system.

[0011] Obtain the power line efficiency corresponding to the energy storage system.

[0012] Complete the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency.

[0013] In some embodiments, the calculating the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery includes: calculating the one-way charge power efficiency and one-way discharge power efficiency corresponding to the battery according to the discharge power and charge power; calculating the battery efficiency corresponding to the energy storage system according to the one-way charge power efficiency and one-way discharge power efficiency.

[0014] In some embodiments, the obtaining the rectification efficiency and inversion efficiency corresponding to the energy storage converter, and calculating the converter efficiency according to the rectification efficiency and inversion efficiency includes: obtaining an efficiency monitoring record form corresponding to the rectification efficiency and inversion efficiency; fitting and generating a rectification efficiency formula and an inversion efficiency formula according to the efficiency monitoring record form; inputting the power corresponding to the energy storage system into the rectification efficiency formula and the inversion efficiency formula to obtain the rectification efficiency and the inversion efficiency; calculating the product of the rectification efficiency and the inversion efficiency as the converter efficiency. This power is the power corresponding to the reference discrete power point for energy storage system loss fitting.

[0015] In some embodiments, obtaining the transformer efficiency corresponding to the AC transformer of the energy storage system includes: obtaining the no-load loss and load loss corresponding to the AC transformer; obtaining the load information corresponding to the AC transformer; the load information includes the operating load and the rated load; calculating the winding loss corresponding to the AC transformer according to the no-load loss, load loss, operating load and rated load; and calculating the transformer efficiency according to the winding loss.

[0016] In some embodiments, obtaining the power line efficiency corresponding to the energy storage system includes: obtaining the first loss information corresponding to the battery and the energy storage converter; obtaining the second loss information from the energy storage converter to the AC transformer; obtaining the third loss information from the AC transformer to the grid connection cabinet corresponding to the grid connection measurement point; and generating the power line efficiency according to the first loss information, second loss information and third loss information.

[0017] Exemplarily, obtaining the first loss information corresponding to the battery and the energy storage converter includes: obtaining the nominal voltage of the battery; obtaining the cable information from the battery to the energy storage converter; calculating the cable resistance according to the cable information; obtaining the grid-side voltage corresponding to the energy storage converter; and calculating the first loss information according to the nominal voltage, cable resistance and grid-side voltage.

[0018] In some embodiments, completing the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency includes: obtaining the system efficiency of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency; obtaining the efficiency curve corresponding to the system efficiency; obtaining the approximate fitting polynomial equation corresponding to the system efficiency according to the efficiency curve; and completing the loss fitting modeling of the energy storage system according to the approximate fitting polynomial equation.

[0019] In a second aspect, the present application provides an energy storage system loss fitting modeling device, which is applied to an energy storage system. The energy storage system includes a grid connection measurement point, an AC transformer, an energy storage converter and a battery. Electric energy is used to charge the battery after passing through the grid connection measurement point, AC transformer and energy storage converter, or the electric energy of the battery is discharged externally through the energy storage converter, AC transformer and grid connection measurement point. The device includes:

[0020] A first acquisition unit, configured to acquire the discharge power and charge power corresponding to a plurality of the batteries passing through the grid connection measurement point, and calculate the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery.

[0021] A second acquisition unit, configured to acquire the rectification efficiency and inversion efficiency corresponding to the energy storage converter, and calculate the converter efficiency according to the rectification efficiency and inversion efficiency;

[0022] A third acquisition unit, configured to acquire the transformer efficiency corresponding to the AC transformer of the energy storage system;

[0023] A fourth acquisition unit, configured to acquire the power line efficiency corresponding to the energy storage system;

[0024] A modeling completion unit, configured to complete the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency.

[0025] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor; the memory is used to store a computer program; the processor is configured to execute the computer program and implement the energy storage system loss fitting modeling method provided in any embodiment of the present application when executing the computer program.

[0026] In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to implement the energy storage system loss fitting modeling method provided in any embodiment of the present application.

[0027] Traditional energy storage models often only consider the losses of a single link. However, this method comprehensively covers the loss situations of all links of the energy storage system by acquiring and calculating the efficiencies of the battery, energy storage converter, AC transformer, and power line, thereby improving the accuracy and reliability of the model. By integrating the efficiencies of all links, the model can be closer to the actual operation of the energy storage system, providing more accurate and effective guidance for the optimization and management of the energy storage system. This helps improve the overall energy efficiency of the energy storage system and reduce operating costs. This method can adapt to different working conditions and operating conditions, such as different charge and discharge rates, ambient temperatures, etc., and is thus more flexible and reliable in practical applications. Based on the detailed loss model, the components of the energy storage system can be optimized in design and maintained to reduce unnecessary losses and extend the service life of the system. By building the energy storage system loss model, reliable reference variables can be provided for the execution of the optimization strategy for the operation of the entire system.

[0028] In summary, the energy storage system loss fitting modeling method provided in the present application not only comprehensively considers the loss situations of all links, but also improves the accuracy and practicality of the model, providing strong support for the optimization and management of the energy storage system.

[0029] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0031] Figure 1 is a schematic block diagram of the structure of an energy storage system provided by an embodiment of the present application;

[0032] Figure 2 is a schematic flow chart of the steps of a method for fitting and modeling the losses of an energy storage system provided by an embodiment of the present application;

[0033] Figure 3 is a schematic diagram of an energy storage efficiency curve provided by an embodiment of the present application;

[0034] Figure 4 is a schematic block diagram of the structure of a device for fitting and modeling the losses of an energy storage system provided by an embodiment of the present application;

[0035] Figure 5 is a schematic block diagram of the structure of a computer device provided by an embodiment of the present application.

[0036] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts fall within the scope of protection of the present application.

[0038] The flowcharts shown in the drawings are only illustrative examples, and do not necessarily include all the content and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can also be decomposed, combined, or partially merged, so the actual execution order may change according to the actual situation.

[0039] It should be understood that in order to facilitate the clear description of the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. Those skilled in the art can understand that the terms "first" and "second" do not limit the quantity and execution order, and the terms "first" and "second" do not necessarily mean different.

[0040] It should be understood that the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification of this application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0041] It should also be understood that the term "and / or" used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0042] The following will describe in detail some embodiments of this application with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0043] The loss calculation of each component of the energy storage system is complex. In the traditional method, the evaluation of the energy storage system loss is often based on the individual efficiency indicators of each component, and it is difficult to comprehensively consider the mutual influence between components and the overall loss situation under different working conditions. The efficiency of the energy storage system is jointly determined by multiple parts such as batteries, power conversion systems, power lines, and transformers, and each part is affected by various factors. For example, the battery is affected by temperature, charge and discharge rate, etc., and the power conversion system is affected by the access voltage level, etc. This makes it challenging to accurately evaluate the loss of the energy storage system.

[0044] Current research on the loss of energy storage systems focuses on certain specific aspects or theoretical models, which have a certain difference from the operation and application scenarios of actual energy storage systems, and cannot fully meet the needs of accurately modeling the loss of energy storage systems in engineering practice, and it is difficult to effectively guide the optimal design and operation management of energy storage systems.

[0045] There are many deficiencies in the actual application of energy storage modeling on the market. Most of these models cannot comprehensively consider the loss situation of each link of the energy storage system, and there are obvious imperfections. Due to the failure to fully cover the loss characteristics of components such as batteries, power conversion systems, power lines, and transformers under different working conditions, it is difficult for them to be close to the actual operation of the energy storage system and cannot provide accurate and effective guidance for the optimization and management of the energy storage system.

[0046] Meanwhile, the losses of the energy storage system often appear as an important factor in the overall evaluation of the energy storage system. For occasions such as automated optimization seeking with the goals of the overall system economy, safety, etc., if the losses of the energy storage system can be modeled and characterized by a continuous function with power as a variable, the convenience of processing can be improved. However, the efficiency of the energy storage converter is characterized in the form of discrete data, resulting in the discretization of the energy storage system loss data. How to approximately convert the discretized data into a continuous function for characterization is also an issue that needs to be focused on.

[0047] Therefore, there is an urgent need for a method for fitting and modeling the losses of the energy storage system to solve at least one of the above problems.

[0048] To solve the above problems, this application provides a method for fitting and modeling the losses of the energy storage system. The method is used for the Figure 1 energy storage system shown as follows. The energy storage system includes a grid-connected metering point, an AC transformer (such as Figure 1 the part between the grid-connected metering point and the PCS on the 400V AC side in Figure 1 ), an energy storage converter (such as Figure 1 the PCS on the AC side of the PCS in

[0049] ), and a battery (including battery clusters #1 to #5 such as

[0050] Figure 1 . The number of battery clusters is not limited in the embodiments of this application). Electric energy is used to charge the battery after passing through the grid-connected metering point, the AC transformer, and the energy storage converter, or the electric energy of the battery is discharged externally through the energy storage converter, the AC transformer, and the grid-connected metering point. The method runs on a computer device, and the computer device can be deployed on a single server or a server cluster. It can also be deployed on a handheld terminal, a laptop, a wearable device, or a robot, etc. Figure 1The arrow direction in [it] is the direction of the charging process corresponding to the energy storage system. Electrical energy first enters the system from an external power source, passing through the grid-connected metering point where the input electrical energy is metered and monitored. Then, the energy is transmitted along the AC-side line. The electrical energy on the AC side reaches the power conversion system (PCS). The PCS plays a key role in the charging process, converting the AC electrical energy into DC electrical energy suitable for battery charging. The converted DC electrical energy flows to each battery through the DC-side transmission line respectively, and these batteries receive and store the electrical energy, completing the entire charging process. During the charging process, the in-cabin power distribution and secondary part are responsible for power distribution, control, and monitoring of the entire system to ensure the safe, stable, and efficient progress of the charging process.

[0051] During the energy storage discharging process, the arrow direction is opposite to Figure 1 that. The electrical energy stored in each battery starts to be released. The electrical energy converges to the power conversion system (PCS) through the DC-side transmission line. The PCS converts the DC electrical energy output by the battery into AC electrical energy, and the converted AC electrical energy is transmitted along the AC-side line. Then, the electrical energy passes through the grid-connected metering point where the output electrical energy can be metered and monitored. During the discharging process, the in-cabin power distribution and secondary part are responsible for power distribution, control, and monitoring of the entire system to ensure the safe, stable, and efficient progress of the discharging process.

[0052] As Figure 2 shown, the provided energy storage system loss fitting modeling method includes steps S101 to S105. Details are as follows:

[0053] Step S101. Obtain the discharging power and charging power of the battery corresponding to the grid-connected metering point, and calculate the battery efficiency corresponding to the energy storage system according to the discharging power and charging power of the battery.

[0054] Specifically, this step is mainly to collect the charge and discharge data generated by the battery during actual operation. These data are important bases for evaluating system performance, especially when calculating battery efficiency. Battery efficiency is generally defined as the ratio of the electrical energy released to the electrical energy stored by the battery in a certain charge and discharge cycle. The efficiency is affected by various factors, including working temperature, charge and discharge rate (charge and discharge multiple), battery aging degree, etc.

[0055] Suppose that within one day, the charging power of battery #3 in a certain energy storage system is 100 kWh and the discharging power is 95 kWh. Then the battery efficiency can be calculated as 95 / 100 = 0.95 or 95%.

[0056] By monitoring the data at the grid-connected metering point, the charge and discharge status of the battery can be understood in real time, and then the battery efficiency can be accurately calculated, providing reliable input data for subsequent loss fitting modeling.

[0057] Step S102. Obtain the rectification efficiency and inversion efficiency corresponding to the energy storage converter, and calculate the converter efficiency based on the rectification efficiency and inversion efficiency.

[0058] Specifically, the energy storage converter (PCS, Power Conversion System) is responsible for converting direct current into alternating current or vice versa. In this process, the efficiency of electrical energy conversion is a very crucial performance indicator. The rectification efficiency and inversion efficiency respectively refer to the conversion efficiency in the process of direct current to alternating current (rectification) and alternating current to direct current (inversion). The converter efficiency is usually determined based on the technical parameters provided by the manufacturer or through experimental tests.

[0059] Suppose the rectification efficiency of a certain PCS is 98% and the inversion efficiency is 96%. When calculating the overall efficiency of the PCS, if the main operating mode of the system is charging (inversion), the efficiency can be 96%. If it is the discharging (rectification) mode, the efficiency can be 98%.

[0060] By calculating and considering the rectification and inversion efficiencies of the PCS, it helps to more accurately reflect the energy loss in the energy conversion process of the energy storage system and improve the accuracy of the overall loss assessment of the system.

[0061] Step S103. Obtain the transformer efficiency corresponding to the AC transformer of the energy storage system.

[0062] Specifically, the AC transformer plays a role of boosting or bucking voltage in the energy storage system, affecting the loss of electrical energy during transmission at different voltage levels. The transformer efficiency refers to the ratio of the output power of the transformer to the input power, and is usually affected by various factors such as the load condition and ambient temperature.

[0063] For example, the efficiency of a certain transformer at full load is 97%, while at light load, the efficiency may drop to 95%. This reflects the volatility of the transformer efficiency in actual operation.

[0064] By obtaining the efficiency of the transformer under different working conditions, it can more realistically evaluate the loss in the power transmission process and further improve the loss model of the energy storage system.

[0065] Step S104. Obtain the power line efficiency corresponding to the energy storage system.

[0066] Specifically, the power line efficiency refers to the partial electrical energy loss caused by factors such as the resistance of the wire during the transmission of electrical energy through the wire, and is usually characterized by the resistance loss on the wire. The power line efficiency is affected by physical parameters such as the magnitude of the current, the material of the wire, and the length.

[0067] Suppose the total length of a power line is 100 meters, using copper wire with a wire diameter of 10 mm². When transmitting a current of 100 A, the calculation result of the resistance loss shows that the line efficiency is 98%.

[0068] By considering the transmission efficiency of the power line, the loss of electrical energy during transmission can be effectively identified, which is particularly important during long-distance transmission, and helps to further optimize the network design and operation of the energy storage system.

[0069] Step S105. Complete the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency.

[0070] Specifically, this step is a comprehensive application of all the previous data collection and analysis. By establishing a mathematical model, the efficiency values of the above-mentioned parts are integrated, taking into account their mutual influence under different working conditions, so as to realize the quantification and prediction of the overall loss of the energy storage system. This modeling method should simulate the actual application scenario as much as possible, so as to provide more valuable guidance for the optimal design and operation management of the system.

[0071] After completing the overall loss fitting modeling, not only can the current performance of the energy storage system be accurately evaluated, but more importantly, it can predict the impact of different operating conditions on the system loss, providing a scientific basis for realizing the optimal design of the system, improving the energy efficiency ratio, and reducing energy waste. In addition, through the accurate prediction of the loss, it can also effectively support the economic analysis of the energy storage system and help users make more reasonable cost-benefit decisions.

[0072] In summary, the loss fitting modeling method of the energy storage system provided by this application aims to construct a more accurate loss model that is closer to the actual operating conditions by comprehensively collecting and considering the efficiency data of each component of the energy storage system, so as to provide strong support for the optimal design and operation management of the energy storage system.

[0073] In some embodiments, calculating the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery includes: calculating the unidirectional charge power efficiency and unidirectional discharge power efficiency corresponding to the battery according to the discharge power and charge power; calculating the battery efficiency corresponding to the energy storage system according to the unidirectional charge power efficiency and unidirectional discharge power efficiency.

[0074] In this embodiment, calculating the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery specifically includes the following steps: calculating the unidirectional charge power efficiency: The unidirectional charge power efficiency refers to the efficiency of the battery during the charging process.

[0075] Calculating the unidirectional discharge power efficiency: The unidirectional discharge power efficiency refers to the efficiency of the battery during the discharging process. Among them,

[0076] Calculate the battery efficiency corresponding to the energy storage system: The battery efficiency usually takes the geometric mean of the charging efficiency and the discharging efficiency to reflect the comprehensive efficiency of the battery during the charge-discharge cycle. The calculation formula is as follows:

[0077] .

[0078] By calculating the charging and discharging efficiencies separately and then comprehensively evaluating, the performance of the battery during the actual charge-discharge cycle can be more accurately reflected. Identifying the different efficiencies of the battery during charging and discharging helps to discover bottlenecks in the system and guide the optimization of battery performance. Calculating the battery efficiency in real time can promptly detect abnormal changes in battery performance for fault diagnosis and maintenance.

[0079] In some embodiments, obtain the rectification efficiency and inversion efficiency corresponding to the energy storage converter, and calculate the converter efficiency according to the rectification efficiency and the inversion efficiency, including: obtaining the efficiency monitoring record table corresponding to the rectification efficiency and the inversion efficiency; fitting and generating the rectification efficiency formula and the inversion efficiency formula according to the efficiency monitoring record table; inputting the power corresponding to the energy storage system into the rectification efficiency formula and the inversion efficiency formula to obtain the rectification efficiency and the inversion efficiency; calculating the product of the rectification efficiency and the inversion efficiency as the converter efficiency.

[0080] In this embodiment, obtain the rectification efficiency and inversion efficiency of the power conversion system (PCS) of the energy storage system, and calculate the converter efficiency according to these efficiencies. The specific steps are as follows: Obtain the efficiency monitoring record table of the rectification efficiency and the inversion efficiency: The efficiency monitoring record table includes the rectification and inversion efficiencies of the PCS under different power conditions. Calculate the rectification efficiency and the inversion efficiency according to the input power: Input the actual power of the energy storage system into the rectification efficiency formula and the inversion efficiency formula to calculate the corresponding rectification efficiency and inversion efficiency. Calculate the converter efficiency: The converter efficiency is the product of the rectification efficiency and the inversion efficiency. The calculation formula is: Converter efficiency = Rectification efficiency × Inversion efficiency.

[0081] By fitting the formula, the efficiency of the PCS can be dynamically calculated according to the actual power, improving the adaptability and accuracy of the model. The fitting formula can be used in the design and selection process of the PCS to select a PCS with higher efficiency within the target power range. By calculating the rectification and inversion efficiencies of the PCS, it helps to promptly detect abnormal performance of the PCS for fault diagnosis and maintenance.

[0082] In some embodiments, obtain the transformer efficiency corresponding to the AC transformer of the energy storage system, including: obtaining the no-load loss and load loss corresponding to the AC transformer; obtaining the load information corresponding to the AC transformer; the load information includes the operating load and the rated load; calculating the winding loss corresponding to the AC transformer according to the no-load loss, the load loss, the operating load, and the rated load; calculating the transformer efficiency according to the winding loss.

[0083] In this embodiment, obtaining the transformer efficiency corresponding to the AC transformer of the energy storage system specifically includes the following steps: Obtain the no-load loss and load loss of the AC transformer: The no-load loss refers to the energy loss of the transformer in the no-load state, and the load loss refers to the energy loss of the transformer in the load state. Obtain the load information of the AC transformer: The load information includes the operating load and the rated load.

[0084] By considering the no-load loss and winding loss, the efficiency of the transformer under different load conditions can be more accurately evaluated. The calculation of the winding loss can be used in the design and selection process of the transformer to select a transformer with higher efficiency within the target load range. Real-time monitoring of the transformer loss helps to detect performance anomalies of the transformer in a timely manner for fault diagnosis and maintenance.

[0085] In some embodiments, obtaining the power line efficiency corresponding to the energy storage system includes: obtaining the first loss information corresponding to the battery and the energy storage converter; obtaining the second loss information from the energy storage converter to the AC transformer; obtaining the third loss information of the grid connection cabinet corresponding to the AC transformer to the grid metering point; generating the power line efficiency according to the first loss information, the second loss information, and the third loss information.

[0086] In an embodiment, obtaining the power line efficiency corresponding to the energy storage system specifically includes the following steps: Obtain the first loss information corresponding to the battery and the energy storage converter: Obtain the nominal voltage of the battery: The nominal voltage is the rated voltage of the battery. Obtain the cable information from the battery to the energy storage converter: The cable information includes the cable length, material, and cross-section. Calculate the cable resistance value according to the cable information: Calculate the resistance value of the cable using the cable information. Obtain the grid-side voltage corresponding to the energy storage converter: The grid-side voltage is the voltage when the energy storage converter is connected to the grid.

[0087] Calculate the first loss information according to the nominal voltage, cable resistance value, and grid-side voltage: Calculate the loss between the battery and the PCS, and obtain the second loss information from the energy storage converter to the AC transformer: Similarly, calculate the loss between the PCS and the transformer. Obtain the third loss information of the grid connection cabinet corresponding to the AC transformer to the grid metering point: Calculate the loss between the transformer and the grid metering point. Generate the power line efficiency: Integrate the first loss information, the second loss information, and the third loss information to calculate the overall efficiency of the power line.

[0088] By calculating the loss information of each segment, the overall loss of the power line can be comprehensively evaluated. The calculation of the power line efficiency can be used for the design and optimization of the line to select more suitable cable materials and cross-sections to reduce transmission losses. Real-time monitoring of the power line loss helps to detect anomalies in the line in a timely manner for fault diagnosis and maintenance.

[0089] Exemplarily, obtaining the first loss information corresponding to the battery and the energy storage converter includes: obtaining the nominal voltage of the battery; obtaining the cable information from the battery to the energy storage converter; calculating the cable resistance according to the cable information; obtaining the grid-side voltage corresponding to the energy storage converter; and calculating the first loss information according to the nominal voltage, the cable resistance, and the grid-side voltage.

[0090] In the example, obtaining the first loss information corresponding to the battery and the energy storage converter specifically includes the following steps: Obtaining the nominal voltage of the battery: Assume the nominal voltage is 400V. Obtaining the cable information from the battery to the energy storage converter: Assume the cable length is 50 meters, the material is copper, and the cross-section is 10mm². Calculating the cable resistance according to the cable information: The resistivity of the copper cable is approximately 0.01724Ω*mm² / m, so the cable resistance is: 0.0862 Ω.

[0091] By considering the specific parameters of the cable and the transmitted current, the cable loss can be accurately calculated. The calculation of cable loss helps to select a more suitable cable material and cross-section, reducing the electrical energy loss during transmission. Real-time monitoring of cable loss can promptly detect abnormal conditions of the cable for maintenance and replacement.

[0092] In some embodiments, completing the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency includes: obtaining the system efficiency of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency; obtaining the efficiency curve corresponding to the system efficiency; obtaining the approximate fitting univariate polynomial equation corresponding to the system efficiency according to the efficiency curve, and completing the loss fitting modeling of the energy storage system according to the approximate fitting univariate polynomial equation.

[0093] In the embodiment, completing the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency specifically includes the following steps: Obtaining the system efficiency: The system efficiency refers to the comprehensive efficiency of the entire energy storage system from charging the grid to the battery and then discharging from the battery to the grid. The calculation formula is: System efficiency = Battery efficiency × Converter efficiency × Transformer efficiency × Power line efficiency.

[0094] Obtaining the efficiency curve corresponding to the system efficiency: Generating a curve of the system efficiency varying with different operating conditions through historical data. Generating the approximate fitting univariate polynomial equation: Using the least squares method or other fitting methods to fit the efficiency curve into a univariate polynomial equation. Completing the loss fitting modeling: According to the approximate fitting univariate polynomial equation, predicting the system efficiency under different operating conditions, and thus calculating the loss of the system.

[0095] By integrating the efficiency of each part, the loss situation of the entire energy storage system can be comprehensively evaluated. Approximating and fitting a polynomial equation of one variable can be used for the design and optimization of the system, and components with higher efficiency under target operating conditions can be selected. By predicting the system efficiency and losses under different operating conditions, operation and management personnel can better optimize the operation strategy and reduce energy waste. Accurate loss prediction helps with the economic analysis of the system and enables users to make more reasonable cost-benefit decisions.

[0096] In summary, through detailed data collection and analysis, these embodiments and examples have constructed a more accurate energy storage system loss model that is closer to the actual operating situation, providing strong support for the optimal design and operation management of the energy storage system.

[0097] The specific implementation manner of the method provided by this application is illustrated through a complete embodiment:

[0098] The efficiency of the energy storage system should be calculated according to factors such as battery efficiency, power conversion system efficiency, power line efficiency, and transformer efficiency using the following formula:

[0099] ;

[0100] is the energy storage system efficiency, , , , are the battery efficiency, power conversion system efficiency, power line efficiency, and transformer efficiency respectively.

[0101] The calculation of the battery efficiency corresponding to battery charging and discharging is relatively complex. Regarding the battery system efficiency, curve fitting can be performed using the test data of battery manufacturers or specific analysis and calculation can be carried out through the battery charging and discharging data of the already put into operation system. However, there is little disclosure of the test data of each battery manufacturer. Therefore, according to the battery module power curve performance requirements in "GB / T 36276-2023 Lithium-Ion Batteries for Electric Energy Storage", the energy efficiency of the battery module under different charging and discharging powers is not less than 94%. Then: The one-way efficiency with the same battery charging and discharging power is: ; Battery efficiency: .

[0102] Obtain the rectification efficiency and inversion efficiency monitoring record forms from the transformer manufacturer. Since there are differences in the efficiency of different manufacturers and models, the obtained efficiency data curve is fitted into an approximate polynomial equation of one variable to calculate the power conversion system efficiency of this PCS device. The following is obtained through fitting the manufacturer's data:

[0103] Rectification efficiency is: ; ( is the power, (where [constant] is a constant).

[0104] Inverter efficiency is: ; ( where [power] is the power, [constant] is a constant).

[0105] Power conversion system efficiency is: .

[0106] The overall power line of the energy storage system is divided into three sections: the first section is the DC side transmission from the battery to the PCS; the second section is the AC side transmission from the PCS to the transformer; the third section is the transmission from the transformer to the grid connection cabinet. The power line efficiency is composed of these three sections respectively.

[0107] Then, the power line efficiency is: .

[0108] : Battery-PCS unidirectional efficiency; : PCS-transformer unidirectional efficiency; : Transformer-grid connection cabinet unidirectional efficiency. The resistance value of the cable is based on the resistance value of the conductor at 20°C in the national standard "GB / T_3956 - 2008 Conductors of Cables" and is determined by looking up the table.

[0109] Based on the battery nominal voltage, the cable-related information from the battery to the PCS, and the number and length of the cables used, the line loss and efficiency from the battery to the PCS are calculated. Then, . . U is the battery voltage. ρ: Resistivity, L: Length, y: Number of lines, S: Wire diameter, x: Number of parallel connections. The battery-PCS bidirectional efficiency is: .

[0110] Based on the rated input voltage of the PCS AC side, the cable-related information from the PCS to the transformer, and the number and length of the cables used, the line loss and efficiency from the PCS to the transformer are calculated.

[0111] .

[0112] .

[0113] The PCS-transformer unidirectional efficiency is: . U is the grid side voltage of the PCS.

[0114] The PCS-transformer bidirectional efficiency is: .

[0115] Based on the rated voltage of the high-voltage side of the transformer, the relevant information of the cable from the transformer to the grid connection cabinet, and the quantity and length of the cables used, the line loss and efficiency from the transformer to the grid connection cabinet are calculated.

[0116] Then, ;

[0117] ;

[0118] The single-direction efficiency of the transformer-grid connection cabinet is: P. U is the voltage of the high-voltage side of the transformer. The two-direction efficiency of the transformer-grid connection cabinet is: .

[0119] The no-load loss and load loss of this transformer can be obtained from the product specification provided by the transformer manufacturer. Combining with the actual operating load and rated load data, the efficiency of this transformer is calculated.

[0120] Winding loss: .

[0121] Single-direction efficiency:

[0122] ;

[0123] Transformer efficiency: .

[0124] The present invention has achieved a series of results around obtaining an approximate fitting polynomial equation for energy storage system modeling. Using the detailed data of the actual energy storage system, by substituting the values of different power points within a certain range into the above method for calculation, the efficiency of the energy storage system at each power can be obtained. Eventually, an approximate fitting polynomial equation can be obtained through the efficiency curve:

[0125] .

[0126] The generated approximate fitting polynomial equation can concisely and effectively describe the complex relationship between the losses of the energy storage system and related factors. Through the loss model, the conditions for the highest charge-discharge efficiency can also be analyzed, which can be used to optimize the operation strategy, improve the energy utilization efficiency, and reduce costs.

[0127] The present invention proposes a method for loss fitting modeling of an energy storage system. By using the detailed information of the energy storage configuration, the losses of each equipment link can be calculated, and finally an approximate fitting polynomial equation for the losses of the entire energy storage system can be obtained. This helps to accurately evaluate the performance of the energy storage system and provides a reliable basis for system optimization and improvement.

[0128] First of all, in terms of the model, it comprehensively considers multiple factors such as batteries, PCS systems, power lines, and transformers and their mutual influences, and can better reflect the actual operating state of the energy storage system.

[0129] Secondly, in terms of practicability and guidance, it can better guide the optimization of the energy storage system, clarify the weak links and improvement directions of the system, and help to select the best configuration plan.

[0130] Finally, in terms of economy, it can help enterprises reduce the initial investment cost during the design and selection stages, improve the energy utilization efficiency to reduce the operating cost, and bring better economic benefits.

[0131] A method for loss fitting modeling of an energy storage system according to the present invention is implemented as follows:

[0132] (1) Obtain the specification and relevant test data provided by the equipment manufacturer.

[0133] (2) Organize the detailed configuration information of the entire energy storage system, especially the data that needs to be substituted for calculation.

[0134] (3) Substitute the data into the efficiency calculation formulas of each device and link in the above method to obtain the corresponding efficiency.

[0135] (4) After obtaining the efficiency of each device and link, calculate the efficiency of the entire system.

[0136] (5) Substitute the power regulation within the rated power range of the energy storage system into the formula multiple times to obtain the efficiency at each power point to form a curve, and an approximate fitting polynomial equation can be obtained through the curve for modeling use.

[0137] Example:

[0138] The first step: Obtain the test data provided by the PCS manufacturer and calculate the efficiency of the PCS device. For example, according to the power curve fitting of the energy storage converter test data, it is found that the inverter-conversion efficiency reaches the maximum efficiency at around the 20% - 40% power point after sorting.

[0139] ;

[0140] ;

[0141] ;

[0142] The second step: Obtain the specification of the transformer provided by the transformer manufacturer to obtain the load and no-load data. A certain park uses a 630 kVA three-phase isolation transformer of a certain company. According to the product specification, the no-load loss of this transformer ≤ 910 W, and the load loss ≤ 5660 W. Substitute the actual operating load for calculation to obtain the efficiency.

[0143] When operating under the 400 kVA condition:

[0144] ;

[0145] ) / 400000 = 99.2%;

[0146] Step 3: Organize other configuration information and substitute it into the calculation method of transmission line efficiency.

[0147] Step 4: Substitute the formula in the method through multiple sampling points within the rated range.

[0148] Step 5: Obtain the following curve and approximately fit a polynomial equation through the data. The obtained equation and curve are as Figure 3 shown. Through the curve, we obtain at what power the power point reaches the maximum efficiency. At the same time, we obtain an approximately fitted equation for the power and efficiency of the energy storage system, which can be used for the modeling of the energy storage system.

[0149] Traditional energy storage models often only consider the losses of a single link. However, this method comprehensively covers the loss situations of all links in the energy storage system by obtaining and calculating the efficiencies of batteries, energy storage converters, AC transformers, and power lines, thereby improving the accuracy and reliability of the model. By integrating the efficiencies of all links, the model can be closer to the actual operation of the energy storage system, providing more accurate and effective guidance for the optimization and management of the energy storage system. This helps to improve the overall energy efficiency of the energy storage system and reduce operating costs. This method can adapt to different working conditions and operating conditions, such as different charge and discharge rates, ambient temperatures, etc., and is thus more flexible and reliable in practical applications. Based on the detailed loss model, the components of the energy storage system can be optimized in design and maintained to reduce unnecessary losses and extend the service life of the system. By continuously monitoring and calculating the efficiencies of all links, data-driven decision support can be provided for system operation, helping operators to adjust system parameters in a timely manner to ensure the efficient operation of the system.

[0150] In summary, the energy storage system loss fitting modeling method provided in this application not only comprehensively considers the loss situations of all links, but also improves the accuracy and practicality of the model, providing strong support for the optimization and management of the energy storage system.

[0151] Please refer to Figure 4 , Figure 4 which is a schematic structural diagram of an energy storage system loss fitting modeling device 200 for a power system provided in an embodiment of this application. The energy storage system loss fitting modeling device 200 for a power system is used to execute the steps of the energy storage system loss fitting modeling method shown in any embodiment of this application. The energy storage system loss fitting modeling device 200 for a power system can be a single server or a server cluster, or the energy storage system loss fitting modeling device 200 for a power system can be a terminal, and the terminal can be a handheld terminal, a laptop computer, a wearable device, or a robot, etc.

[0152] As Figure 4 shown, the energy storage system loss fitting modeling device 200 includes:

[0153] A first acquisition unit 201, configured to acquire the discharge power and charge power of the battery corresponding to the grid connection metering point, and calculate the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery;

[0154] A second acquisition unit 202, configured to acquire the rectification efficiency and inversion efficiency of the energy storage converter, and calculate the converter efficiency according to the rectification efficiency and inversion efficiency;

[0155] A third acquisition unit 203, configured to acquire the transformer efficiency of the AC transformer of the energy storage system;

[0156] A fourth acquisition unit 204, configured to acquire the power line efficiency corresponding to the energy storage system;

[0157] A modeling completion unit 205, configured to complete the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency.

[0158] It should be noted that those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described energy storage system loss fitting modeling device 200 and each module can refer to Figure 2 the corresponding process in the energy storage system loss fitting modeling method embodiment described in the corresponding embodiment, which will not be elaborated here.

[0159] Figure 2 The corresponding energy storage system loss fitting modeling method can be implemented in the form of a computer program, and this computer program can run on a device as Figure 4 shown.

[0160] Please refer to Figure 5 , Figure 5 which is a schematic block diagram of the structure of the computer device provided in the embodiment of the present application. The computer device includes a processor, a memory, and a network interface connected through a device bus. Among them, the memory may include a storage medium and an internal memory.

[0161] The storage medium can store an operating device and a computer program. This computer program includes program instructions, and when these program instructions are executed, the processor can be made to execute Figure 2 any one of the corresponding energy storage system loss fitting modeling methods.

[0162] The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

[0163] The internal memory provides an environment for the operation of a computer program in a non-volatile storage medium. When the computer program is executed by a processor, the processor can be caused to execute any one of the energy storage system loss fitting modeling methods.

[0164] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 5 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the terminal to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0165] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0166] Wherein, in one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0167] Obtain the discharge power and charge power of the battery corresponding to the grid-connected metering point, and calculate the battery efficiency of the energy storage system according to the discharge power and charge power of the battery;

[0168] Obtain the rectification efficiency and inversion efficiency of the energy storage converter, and calculate the converter efficiency according to the rectification efficiency and inversion efficiency;

[0169] Obtain the transformer efficiency of the AC transformer of the energy storage system;

[0170] Obtain the power line efficiency of the energy storage system;

[0171] Complete the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency.

[0172] In some embodiments, calculating the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery includes: calculating the unidirectional charge power efficiency and unidirectional discharge power efficiency corresponding to the battery according to the discharge power and charge power; calculating the battery efficiency corresponding to the energy storage system according to the unidirectional charge power efficiency and unidirectional discharge power efficiency.

[0173] In some embodiments, obtaining the rectification efficiency and inversion efficiency corresponding to the energy storage inverter and calculating the inverter efficiency according to the rectification efficiency and inversion efficiency includes: obtaining an efficiency monitoring record table corresponding to the rectification efficiency and inversion efficiency; fitting a rectification efficiency formula and an inversion efficiency formula according to the efficiency monitoring record table; inputting the power corresponding to the energy storage system into the rectification efficiency formula and the inversion efficiency formula to obtain the rectification efficiency and the inversion efficiency; calculating the product of the rectification efficiency and the inversion efficiency as the inverter efficiency.

[0174] In some embodiments, obtaining the transformer efficiency corresponding to the AC transformer of the energy storage system includes: obtaining the no-load loss and load loss corresponding to the AC transformer; obtaining the load information corresponding to the AC transformer; the load information includes the operating load and the rated load; calculating the winding loss corresponding to the AC transformer according to the no-load loss, load loss, operating load and rated load; calculating the transformer efficiency according to the winding loss.

[0175] In some embodiments, obtaining the power line efficiency corresponding to the energy storage system includes: obtaining the first loss information corresponding to the battery and the energy storage inverter; obtaining the second loss information from the energy storage inverter to the AC transformer; obtaining the third loss information from the AC transformer to the grid connection cabinet corresponding to the grid connection metering point; generating the power line efficiency according to the first loss information, second loss information and third loss information.

[0176] Exemplarily, obtaining the first loss information corresponding to the battery and the energy storage inverter includes: obtaining the nominal voltage of the battery; obtaining the cable information from the battery to the energy storage inverter; calculating the cable resistance value according to the cable information; obtaining the grid-side voltage corresponding to the energy storage inverter; calculating the first loss information according to the nominal voltage, cable resistance value and grid-side voltage.

[0177] In some embodiments, the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency includes: obtaining the system efficiency of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency, and power line efficiency; obtaining the efficiency curve corresponding to the system efficiency; obtaining an approximate fitting polynomial equation corresponding to the system efficiency according to the efficiency curve, and completing the loss fitting modeling of the energy storage system according to the approximate fitting polynomial equation.

[0178] This application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to implement the steps of the energy storage system loss fitting modeling method provided in any corresponding embodiment of this application. Figure 2 The steps of the energy storage system loss fitting modeling method provided in any corresponding embodiment of this application.

[0179] Among them, the computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device.

[0180] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims

1. A method for fitting modeling of energy storage system loss, characterized in that: Applied to an energy storage system, the energy storage system includes a grid-connected metering point, an AC transformer, an energy storage converter and a battery, the electric energy is charged to the battery after passing through the grid-connected metering point, the AC transformer and the energy storage converter, or the electric energy of the battery is discharged to the outside through the energy storage converter, the AC transformer and the grid-connected metering point; including: Obtaining the discharge power and charge power corresponding to the battery passing through the grid-connected metering point, and calculating the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery; Obtaining the rectification efficiency and the inversion efficiency corresponding to the energy storage converter, and calculating the converter efficiency according to the rectification efficiency and the inversion efficiency; Obtaining a transformer efficiency corresponding to an AC transformer of the energy storage system; Obtaining power line efficiency corresponding to the energy storage system; The loss fitting modeling of the energy storage system is completed according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency.

2. The method according to claim 1, characterized in that The calculating the battery efficiency corresponding to the energy storage system according to the discharge power and the charge power of the battery includes: Calculating the charging power unidirectional efficiency and the discharging power unidirectional efficiency corresponding to the battery according to the power and charging power of the battery; The battery efficiency corresponding to the energy storage system is calculated according to the charging power unidirectional efficiency and the discharging power unidirectional efficiency.

3. The method according to claim 1, characterized in that The obtaining of the rectification efficiency and the inversion efficiency corresponding to the energy storage converter, and calculating the converter efficiency according to the rectification efficiency and the inversion efficiency, comprises: Obtaining an efficiency monitoring record table corresponding to the rectification efficiency and the inversion efficiency; Generating a rectifier efficiency formula and an inverter efficiency formula by fitting according to the efficiency monitoring record table; Inputting the power corresponding to the energy storage system into the rectification efficiency formula and the inverter efficiency formula to obtain the rectification efficiency and the inverter efficiency; The product of the rectification efficiency and the inversion efficiency is calculated as the converter efficiency.

4. The method according to claim 1, characterized in that: The obtaining of the transformer efficiency corresponding to the AC transformer of the energy storage system includes: Obtaining no-load loss and load loss corresponding to the AC transformer; Obtaining load information corresponding to the AC transformer; the load information includes operating load and rated load; Calculating the winding loss corresponding to the AC transformer according to the no-load loss, load loss, operating load and rated load; The transformer efficiency is calculated based on the winding losses.

5. The method according to claim 1, characterized in that The obtaining of the power line efficiency corresponding to the energy storage system comprises: Acquire first loss information corresponding to the battery and the energy storage converter; Acquire second loss information from the energy storage converter to the AC transformer; Acquire third loss information from the AC transformer to the grid-connected cabinet corresponding to the grid-connected metering point; The power line efficiency is generated according to the first loss information, the second loss information, and the third loss information.

6. The method according to claim 5, characterized in that The obtaining of first loss information corresponding to the battery and the energy storage converter includes: obtaining a nominal voltage of the battery; Obtaining cable information from the battery to the energy storage converter; Calculate the cable resistance according to the cable information; Obtaining a grid-side voltage corresponding to the energy storage converter; The first loss information is calculated according to the nominal voltage, the cable resistance and the grid-side voltage.

7. The method according to claim 1, characterized in that The loss fitting modeling of the energy storage system is completed according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency, including: Obtaining the system efficiency of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency; Obtaining an efficiency curve corresponding to the system efficiency; An approximate fitting univariate multi-order equation corresponding to the system efficiency is obtained according to the efficiency curve, and loss fitting modeling of the energy storage system is completed according to the approximate fitting univariate multi-order equation.

8. A loss fitting modeling device for an energy storage system, characterized in that: Applied to an energy storage system, the energy storage system includes a grid-connected metering point, an AC transformer, an energy storage converter and a battery, the electric energy is charged to the battery after passing through the grid-connected metering point, the AC transformer and the energy storage converter, or the electric energy of the battery is discharged to the outside through the energy storage converter, the AC transformer and the grid-connected metering point; the device includes: A first acquisition unit is used to acquire the discharge power and charge power corresponding to the battery through the grid-connected metering point, and calculate the battery efficiency corresponding to the energy storage system according to the discharge power and charge power of the battery; A second acquisition unit, used to acquire the rectification efficiency and the inversion efficiency corresponding to the energy storage converter, and calculate the converter efficiency according to the rectification efficiency and the inversion efficiency; A third acquisition unit, used to acquire a transformer efficiency corresponding to the AC transformer of the energy storage system; A fourth acquisition unit, used to acquire the power line efficiency corresponding to the energy storage system; The modeling completion unit is used to complete the loss fitting modeling of the energy storage system according to the battery efficiency, converter efficiency, transformer efficiency and power line efficiency.

9. A computer device, characterized in that: The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is configured to execute the computer program and implement the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to implement the method according to any one of claims 1 to 7.

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