New energy storage method and device based on high-efficiency conversion technology and medium thereof

Abstract

The invention relates to the technical field of new energy, in particular to a new energy storage method and device based on the high-efficiency conversion technology and a medium thereof.The method comprises the following steps that 1, feature data generated by new energy storage are collected through a sensor and a monitoring tool, and the feature data are stored into a database; the method comprises the following steps: step 1, acquiring various monitoring parameters of new energy storage performance to obtain various monitoring parameters for analyzing the new energy storage performance, step 2, analyzing the various monitoring parameters of the new energy storage acquired in the step 1 to obtain various indexes of the new energy storage performance, and step 3, evaluating the various indexes of the new energy storage performance analyzed in the step 2, the method comprises the following steps: step 1, obtaining a qualified coefficient of each index of new energy storage, step 2, carrying out comprehensive analysis on the qualified coefficient calculated in the step 3 to obtain a comprehensive index of the energy storage performance of the new energy, and step 5, carrying out man-machine interaction on the comprehensive index of the energy storage performance of the new energy obtained by the comprehensive analysis in the step 4. Through the high-efficiency conversion technology, new energy is converted into electric energy, and the utilization efficiency of the energy is improved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a new energy storage method, equipment and medium based on high-efficiency energy conversion technology. Background Art

[0002] New energy refers to various forms of energy other than traditional energy (such as coal, oil, natural gas, etc.), including solar energy, wind energy, biomass energy, etc., while high-efficiency conversion technology refers to the technology of efficiently and reliably converting one form of energy into another. In the field of new energy storage, high-efficiency conversion technology mainly focuses on converting renewable energy (such as solar energy and wind energy) into electrical energy, and storing the electrical energy through energy storage equipment so that it can be released and used when needed.

[0003] As the global demand for clean energy continues to grow, the development and utilization of new energy sources such as solar energy and wind energy are increasingly valued. However, these new energy sources are intermittent and unstable, which limits their widespread application. Traditional new energy storage methods include electrochemical energy storage conversion technology, thermal energy storage conversion technology, etc. Chemical energy storage technology mainly refers to the use of hydrogen or synthetic natural gas as a secondary energy carrier, hydrogen is produced by electrolysis of water, and then hydrogen is stored and released as an energy carrier; thermal energy storage technology includes molten salt energy storage, water energy storage, etc., which use the thermal capacity of matter to store energy.

[0004] However, there are still some shortcomings in its actual use. For example, thermal energy storage has problems of heat loss and low energy conversion efficiency; chemical energy storage may face challenges such as material scarcity, high cost and insufficient technological maturity. Therefore, the existing new energy storage technology has problems such as low energy storage efficiency, high cost and poor stability in the process of energy storage and release. In addition, the energy density of most energy storage devices is relatively low, and the energy storage capacity is also subject to certain limitations, which cannot meet large-scale and long-term energy storage needs. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a new energy storage method based on high-efficiency energy conversion technology to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a new energy storage method based on high-efficiency energy conversion technology, comprising the following steps:

[0007] Step 1: Collect characteristic data generated by new energy storage through sensors and monitoring tools to obtain various monitoring parameters for analyzing the performance of new energy storage;

[0008] Step 2: Analyze the various monitoring parameters of the new energy storage collected in step 1 to obtain various indicators of the new energy storage performance;

[0009] Step 3: Evaluate the various indicators of the new energy storage performance analyzed in step 2 to obtain the qualified coefficients of the various indicators of the new energy storage;

[0010] Step 4: Comprehensively analyze the qualified coefficients calculated in step 3 to obtain comprehensive indicators of new energy storage performance;

[0011] Step 5: Conduct human-computer interaction on the comprehensive indicators of new energy storage performance obtained through comprehensive analysis in step 4.

[0012] Preferably, the monitoring parameters include management personnel identity authentication information, new energy conversion evaluation parameters, new energy storage evaluation parameters and new energy storage management parameters, wherein the new energy conversion evaluation parameters specifically include the actual stored energy, the total energy of new energy input, the input power and the output power; the new energy storage evaluation parameters specifically include the actual stored energy, the energy that the energy storage device can store, the capacity of the energy storage device at the beginning of the measurement, the capacity of the energy storage device after the storage time t, the discharge energy of the energy storage device, the charging energy of the energy storage device, the temperature of each point of the energy storage device, the power consumption of the cooling system, the power consumption of the energy storage system and the ambient temperature of the energy storage system; the new energy storage management parameters specifically include the predicted demand energy, the actual demand energy, the power consumption after intelligent scheduling, the power consumption before intelligent scheduling and the intelligent scheduling response time.

[0013] Preferably, the model of the new energy conversion efficiency index among the various indicators of the new energy storage performance is: Where Neei represents the new energy conversion efficiency index, η() represents the energy conversion efficiency function, E(st) represents the actual stored energy, E(in) represents the total energy input from new energy sources, η(st) represents the static energy conversion efficiency, η(dyn) represents the dynamic energy conversion efficiency, p(in) represents the input power, and p(out) represents the output power.

[0014] Preferably, the model of the new energy storage efficiency index among the various indexes of the new energy storage performance is: Where Nesi represents the new energy storage efficiency index, E(st) represents the actual stored energy, E(jz) represents the energy that the energy storage device can store, C(chu) represents the capacity of the energy storage device at the beginning of the measurement, C(mo) represents the capacity of the energy storage device after the storage time t, E(fd) represents the discharge energy of the energy storage device, E(cd) represents the charging energy of the energy storage device, and ξ represents the new energy storage impact coefficient.

[0015] Preferably, the model of the new energy storage influence coefficient in the new energy storage efficiency index among the various indicators of the new energy storage performance is: Where T(b) represents the standard deviation of the temperature at each point of the energy storage device, T(p) represents the average temperature at each point of the energy storage device, Pc represents the power consumption of the cooling system, Sc represents the power consumption of the energy storage system, and Rh max Indicates the maximum ambient humidity of the energy storage system, Rh min Indicates the minimum ambient humidity of the energy storage system, T max Indicates the maximum ambient temperature of the energy storage system, T min It represents the minimum ambient temperature of the energy storage system. a1 and a2 represent the weights of the thermal management efficiency influencing factor and the environmental adaptability influencing factor, respectively.

[0016] Preferably, the model of the new energy storage management efficiency index among the various indicators of the new energy storage performance is: Where Nemi represents the new energy storage management efficiency index, E(p) represents the predicted demand energy, E(a) represents the actual demand energy, Sc(aft) represents the power consumption after intelligent scheduling, Sc(bef) represents the power consumption before intelligent scheduling, and t_r represents the intelligent scheduling response time.

[0017] Preferably, the qualification coefficients of various indicators of the new energy storage system include the following steps:

[0018] Step 3.1: Substitute the new energy conversion efficiency index Neei obtained from the new energy conversion evaluation index analysis unit into the formula: ρ(Neei)=exp[(Neei / Neei0)-1], where ρ(Neei) represents the qualified coefficient of the new energy conversion efficiency, and Neei0 represents the set value;

[0019] Step 3.2: Substitute the new energy storage efficiency index Nesi obtained from the new energy storage evaluation index analysis unit into the formula: ρ(Nesi)=exp[(Nesi / Nesi0)-1], where ρ(Nesi) represents the qualified coefficient of new energy storage efficiency, and Nesi0 represents the set value;

[0020] Step 3.3: Substitute the new energy storage management efficiency index Nemi obtained from the new energy storage management index analysis unit into the formula: ρ(Nemi)=exp[(Nemi / Nemi0)-1], where ρ(Nemi) represents the qualified coefficient of the new energy storage management efficiency, and Nemi0 represents the set value;

[0021] Preferably, the comprehensive analysis model of the comprehensive index of new energy storage performance is: Neci=b1×ρ(Neei)+b2×ρ(Nesi)+b3×ρ(Nemi), wherein Neci represents the comprehensive index of new energy storage performance, and b1, b2, and b3 respectively represent the weights of the qualified coefficient ρ(Neei) of new energy conversion efficiency, the qualified coefficient ρ(Nesi) of new energy storage efficiency, and the qualified coefficient ρ(Nemi) of new energy storage management efficiency.

[0022] Preferably, an electronic device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program in the storage device to implement a new energy storage method based on high-efficiency energy conversion technology.

[0023] Preferably, a computer-readable storage medium stores a computer program, which is executed by a processor to implement a new energy storage method based on high-efficiency energy conversion technology.

[0024] Technical effects and advantages of the present invention:

[0025] 1. The present invention adopts high-efficiency energy conversion technology in the energy conversion link, which can convert unstable new energy into stable electric energy with minimal energy loss, thereby improving the energy utilization efficiency. In the energy storage process, a new energy storage material with high energy density and long cycle life is adopted, so that more energy can be stored and it can remain stable for a long time;

[0026] 2. The present invention adopts a new type of energy storage material with high energy density and long cycle life, and uses energy storage equipment to store the converted electric energy, so that more energy can be stored and can remain stable for a long time, thereby maximizing the capacity of the energy storage equipment and improving energy utilization efficiency;

[0027] 3. The present invention monitors and regulates the operating status of the entire energy storage system in real time through intelligent management, which helps to flexibly adjust the energy storage and release strategies according to the energy input and output requirements, solve the intermittent and instability problems of new energy, ensure that the system is always in the best working state, and improve the system stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the overall process of the present invention.

[0029] Figure 2 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 As shown, the present invention provides a new energy storage method based on high-efficiency energy conversion technology, including: a new energy storage data acquisition module, a new energy storage data analysis module, a new energy storage control module, a new energy storage control comprehensive analysis module, and a new energy storage human-computer interaction module.

[0032] What needs to be specifically explained in this embodiment is that the present invention first collects characteristic data generated by new energy storage through sensors and monitoring tools, and then converts the collected renewable energy into electrical energy through high-efficiency conversion technology. Secondly, by adopting new energy storage materials with high energy density and long cycle life, the converted electrical energy is stored using energy storage equipment (such as batteries, supercapacitors, hydrogen energy storage tanks, etc.). Finally, through the intelligent scheduling algorithm, the energy storage process is finely managed according to the energy demand predicted by the energy prediction model and the actual energy demand.

[0033] The new energy storage data acquisition module is connected to the new energy storage data analysis module, the new energy storage control module is respectively connected to the new energy storage control comprehensive analysis module and the new energy storage data analysis module, and the new energy storage human-computer interaction module is respectively connected to the new energy storage control comprehensive analysis module and the new energy storage control module.

[0034] The new energy storage data acquisition module is used to collect characteristic data generated by the new energy storage, obtain various monitoring parameters for analyzing the performance of the new energy storage, and transmit the various monitoring parameters to the new energy storage data analysis module;

[0035] What needs to be specifically explained in this embodiment is that the collected new energy storage data is subjected to pre-processing operations such as filtering and denoising using existing technologies to improve the accuracy and reliability of the data.

[0036] The new energy storage data analysis module is used to analyze various monitoring parameters in the new energy storage data acquisition module, obtain various indicators for analyzing the new energy storage performance, and transmit the various indicators to the new energy storage control module;

[0037] The new energy storage control module is used to compare the various indicators of new energy storage obtained by the data analysis module with the set values, and transmit the comparison evaluation results to the new energy storage control comprehensive analysis module;

[0038] The new energy storage regulation and control comprehensive analysis module is used to comprehensively analyze the comparison results of the new energy storage regulation and control comprehensive analysis module to obtain a comprehensive index of new energy storage performance, and output the comprehensive index to the new energy storage human-computer interaction module;

[0039] The new energy storage human-computer interaction module is used to output the comprehensive indicators transmitted by the comprehensive analysis module to the management personnel information terminal.

[0040] See also Figure 2 As shown, a new energy storage method based on high-efficiency energy conversion technology includes the following steps: step 1: collecting characteristic data generated by new energy storage through sensors and monitoring tools to obtain various monitoring parameters for analyzing new energy storage performance, step 2: analyzing the various monitoring parameters of new energy storage collected in step 1 to obtain various indicators of new energy storage performance, step 3: evaluating the various indicators of new energy storage performance analyzed in step 2 to obtain the qualified coefficients of various indicators of new energy storage, step 4: comprehensively analyzing the qualified coefficients calculated in step 3 to obtain comprehensive indicators of new energy storage performance, and step 5: performing human-computer interaction on the comprehensive indicators of new energy storage performance obtained by comprehensive analysis in step 4.

[0041] Step 1: Collect characteristic data generated by new energy storage through sensors and monitoring tools to obtain various monitoring parameters for analyzing the performance of new energy storage, including management personnel identity authentication information, new energy conversion evaluation parameters, new energy storage evaluation parameters and new energy storage management parameters, where the new energy conversion evaluation parameters are specifically the actual stored energy, the total energy input of new energy, the input power and the output power; the new energy storage evaluation parameters are specifically the actual stored energy, the energy that the energy storage device can store, the capacity of the energy storage device at the beginning of the measurement, the capacity of the energy storage device after the storage time t, the energy storage device discharge energy, the energy storage device charging energy, the temperature of each point of the energy storage device, the power consumption of the cooling system, the power consumption of the energy storage system and the ambient temperature of the energy storage system; the new energy storage management parameters are specifically the predicted demand energy, the actual demand energy, the power consumption after intelligent scheduling, the power consumption before intelligent scheduling and the intelligent scheduling response time;

[0042] Step 2: Analyze the various monitoring parameters of the new energy storage collected in step 1 to obtain various indicators of the new energy storage performance, including a new energy conversion evaluation index analysis unit, a new energy storage evaluation index analysis unit and a new energy storage management index analysis unit, wherein the new energy conversion evaluation index analysis unit is used to calculate the new energy conversion evaluation parameters, the new energy storage evaluation index analysis unit is used to calculate the new energy storage evaluation parameters and the new energy storage management index analysis unit is used to calculate the new energy storage management parameters, and the analysis includes the following steps;

[0043] Step 2.1: The collected renewable energy is converted into electrical energy through high-efficiency conversion technologies (such as photovoltaic conversion, wind power conversion, etc.). The analysis of the new energy conversion evaluation parameters can measure the overall performance of new energy storage, so that more input energy can be effectively converted into stored electrical energy, thereby improving the energy utilization efficiency of the overall system. Therefore, the model for obtaining the new energy conversion efficiency index in the new energy conversion evaluation index analysis unit is: Where Neei represents the new energy conversion efficiency index, η() represents the energy conversion efficiency function, E(st) represents the actual stored energy, E(in) represents the total energy input from new energy, η(st) represents the static energy conversion efficiency, that is, the conversion efficiency of the energy storage system from input energy to stored energy under stable working conditions, η(dyn) represents the dynamic energy conversion efficiency, that is, the conversion efficiency of the energy storage system from input energy to stored energy during rapid charging and discharging, p(in) represents the input power, and p(out) represents the output power;

[0044] Step 2.2: By adopting new energy storage materials with high energy density and long cycle life, using energy storage devices (such as batteries, supercapacitors, hydrogen energy storage tanks, etc.) to store the converted electrical energy, more energy can be stored and can remain stable for a long time. By analyzing the new energy storage evaluation parameters, the ability of energy storage equipment to store electrical energy can be measured. Therefore, the model for obtaining the new energy storage efficiency index in the new energy storage evaluation index analysis unit is: Where Nesi represents the new energy storage efficiency index, E(st) represents the actual stored energy, E(jz) represents the energy that the energy storage device can store, C(chu) represents the capacity of the energy storage device at the beginning of the measurement, C(mo) represents the capacity of the energy storage device after the storage time t, and the storage time can be selected according to the actual situation, such as days, months or years, E(fd) represents the discharge energy of the energy storage device, E(cd) represents the charging energy of the energy storage device, and ξ represents the new energy storage impact coefficient;

[0045] It should be specifically explained in this embodiment that in the energy storage unit of the new energy storage device, the new energy storage is affected by the temperature of the energy storage device and the operating environment factors. The thermal management efficiency influencing factor is directly related to the temperature control and heat exchange efficiency of the energy storage device during operation, while the environmental adaptability influencing factor focuses on the working ability of the energy storage system under different environmental conditions to ensure that the system can operate stably in various complex environments. Therefore, the model of the new energy storage influencing coefficient is: Where T(b) represents the standard deviation of the temperature at each point of the energy storage device, T(p) represents the average temperature at each point of the energy storage device, Pc represents the power consumption of the cooling system, Sc represents the power consumption of the energy storage system, the power consumption of the cooling system is obtained by measuring the power consumption of each component of the cooling system (such as water pumps, fans, etc.), and the power consumption of the energy storage system is obtained by measuring the power consumption of the entire system, Rh max Indicates the maximum ambient humidity of the energy storage system, Rh min Indicates the minimum ambient humidity of the energy storage system, T max Indicates the maximum ambient temperature of the energy storage system, T min It represents the minimum ambient temperature of the energy storage system. a1 and a2 represent the weights of the thermal management efficiency influencing factor and the environmental adaptability influencing factor respectively. For example, a1=0.6 and a2=0.4.

[0046] Step 2.3: In the energy storage process, the key to ensuring the safe and efficient operation of the energy storage system is to manage the energy storage process in a refined manner through the intelligent scheduling algorithm according to the energy demand predicted by the energy prediction model and the actual energy demand. The analysis of the new energy storage management parameters can further measure the efficiency and reliability of the energy storage system. Therefore, the model for obtaining the new energy storage management efficiency index in the new energy storage management index analysis unit is: Where Nemi represents the new energy storage management efficiency index, E(p) represents the predicted demand energy, E(a) represents the actual demand energy, Sc(aft) represents the power consumption after intelligent scheduling, Sc(bef) represents the power consumption before intelligent scheduling, and t_r represents the intelligent scheduling response time, such as the time interval from receiving the charge and discharge instruction to actually starting the charge and discharge.

[0047] Step 3: Evaluate the various indicators of new energy storage analyzed in step 2, including the following steps:

[0048] Step 3.1: Substitute the new energy conversion efficiency index Neei obtained from the new energy conversion evaluation index analysis unit into the formula: ρ(Neei)=exp[(Neei / Neei0)-1], where ρ(Neei) represents the qualified coefficient of the new energy conversion efficiency, and Neei0 represents the set value;

[0049] What needs to be specifically explained in this embodiment is that if ρ(Neei)≥1, it means that the new energy conversion efficiency is qualified, otherwise it is regarded as abnormal, and the energy storage strategy is dynamically adjusted to adopt more efficient conversion materials and technologies, such as efficient solar panels, advanced battery technology, etc.; reduce energy transmission losses in the system, such as optimizing circuit layout, using low impedance materials, etc.; implement intelligent charging and discharging control strategies to reduce unnecessary dynamic losses, and transmit abnormal signals to the new energy storage human-computer interaction module.

[0050] Step 3.2: Substitute the new energy storage efficiency index Nesi obtained from the new energy storage evaluation index analysis unit into the formula: ρ(Nesi)=exp[(Nesi / Nesi0)-1], where ρ(Nesi) represents the qualified coefficient of new energy storage efficiency, and Nesi0 represents the set value;

[0051] What needs to be specifically explained in this embodiment is that if ρ(Nesi)≥1, it means that the new energy storage efficiency is qualified, otherwise it is regarded as abnormal, and the energy storage strategy is dynamically adjusted, and effective thermal management measures are taken to reduce the temperature difference at each point in the system, improve the heat exchange efficiency, reduce the energy consumption ratio of the cooling system, and transmit the abnormal signal to the new energy storage human-computer interaction module.

[0052] Step 3.3: Substitute the new energy storage management efficiency index Nemi obtained from the new energy storage management index analysis unit into the formula: ρ(Nemi)=exp[(Nemi / Nemi0)-1], where ρ(Nemi) represents the qualified coefficient of the new energy storage management efficiency, and Nemi0 represents the set value;

[0053] What needs to be specifically explained in this embodiment is that if ρ(Nemi)≥1, it means that the new energy storage management efficiency is qualified, otherwise it is regarded as abnormal, and the energy storage strategy is dynamically adjusted. According to the grid load forecast and user needs, the charging and discharging plan of the energy storage system is intelligently adjusted to balance the supply and demand of the grid, reduce the peak-to-valley difference, improve the stability of the grid, realize the coordinated scheduling of multiple systems (such as wind power and photovoltaics), improve the overall energy utilization efficiency, and transmit the abnormal signal to the new energy storage human-computer interaction module.

[0054] Step 4: Comprehensively analyze the qualified coefficients calculated in step 3 to obtain a comprehensive index of new energy storage performance. The comprehensive analysis model is: Neci = b1×ρ(Neei)+b2×ρ(Nesi)+b3×ρ(Nemi), where Neci represents the comprehensive index of new energy storage performance, b1, b2, and b3 represent the weights of the qualified coefficient ρ(Neei) of new energy conversion efficiency, the qualified coefficient ρ(Nesi) of new energy storage efficiency, and the qualified coefficient ρ(Nemi) of new energy storage management efficiency, for example, b1 = 0.4, b2 = 0.3, and b3 = 0.3;

[0055] Step 5: Perform human-computer interaction on the comprehensive index of new energy storage performance obtained by comprehensive analysis in step 4. When the comprehensive index of new energy storage performance is within the set allowable range, it means that the new energy storage performance is good. Otherwise, the management personnel are prompted to take timely measures. For example, when the energy storage equipment fails or the performance degrades, the system can automatically alarm and notify the maintenance personnel to handle it; when the power grid fluctuates or the supply and demand are unbalanced, the system can automatically adjust the charging and discharging strategy of the energy storage equipment to ensure the stable operation of the power grid.

[0056] It should be specifically explained in this embodiment that the present invention also provides an electronic device. In an electronic device embodiment according to the present invention, the electronic device includes a processor and a storage device. The storage device can be configured to store a computer program for executing the new energy storage method of the above method embodiment, and the processor can be configured to execute the program in the storage device, which includes but is not limited to the program for executing the new energy storage method of the above method embodiment. The electronic device can be a control device device formed by various electronic devices.

[0057] It should be specifically explained in this embodiment that the present invention also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present invention, the computer-readable storage medium can be configured to store a program for executing the new energy storage method of the above method embodiment, and the program can be loaded and run by the processor to implement the above new energy storage method. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present invention is a non-temporary computer-readable storage medium.

[0058] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0059] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A new energy storage method based on high-efficiency energy conversion technology, characterized in that: The following steps are involved: Step 1: Collect characteristic data generated by new energy storage through sensors and monitoring tools to obtain various monitoring parameters for analyzing the performance of new energy storage; Step 2: Analyze the various monitoring parameters of the new energy storage collected in step 1 to obtain various indicators of the new energy storage performance; Step 3: Evaluate the various indicators of the new energy storage performance analyzed in step 2 to obtain the qualified coefficients of the various indicators of the new energy storage; Step 4: Comprehensively analyze the qualified coefficients calculated in step 3 to obtain comprehensive indicators of new energy storage performance; Step 5: Conduct human-computer interaction on the comprehensive indicators of new energy storage performance obtained through comprehensive analysis in step 4.

2. A new energy storage method based on high-efficiency energy conversion technology according to claim 1, characterized in that: The monitoring parameters include management personnel identity authentication information, new energy conversion evaluation parameters, new energy storage evaluation parameters and new energy storage management parameters, among which the new energy conversion evaluation parameters specifically include the actual stored energy, the total energy of new energy input, the input power and the output power; the new energy storage evaluation parameters specifically include the actual stored energy, the energy that the energy storage device can store, the capacity of the energy storage device at the beginning of the measurement, the capacity of the energy storage device after the storage time t, the discharge energy of the energy storage device, the charging energy of the energy storage device, the temperature of each point of the energy storage device, the power consumption of the cooling system, the power consumption of the energy storage system and the ambient temperature of the energy storage system; the new energy storage management parameters specifically include the predicted demand energy, the actual demand energy, the power consumption after intelligent scheduling, the power consumption before intelligent scheduling and the intelligent scheduling response time.

3. The new energy storage method based on high-efficiency energy conversion technology according to claim 1 is characterized in that: The model of the new energy conversion efficiency index among the various indicators of the new energy storage performance is: Where Neei represents the new energy conversion efficiency index, η() represents the energy conversion efficiency function, E(st) represents the actual stored energy, E(in) represents the total energy input from new energy sources, η(st) represents the static energy conversion efficiency, η(dyn) represents the dynamic energy conversion efficiency, p(in) represents the input power, and p(out) represents the output power.

4. The new energy storage method based on high-efficiency energy conversion technology according to claim 1 is characterized in that: The model of the new energy storage efficiency index among the various indicators of the new energy storage performance is: Where Nesi represents the new energy storage efficiency index, E(st) represents the actual stored energy, E(jz) represents the energy that the energy storage device can store, C(chu) represents the capacity of the energy storage device at the beginning of the measurement, C(mo) represents the capacity of the energy storage device after the storage time t, E(fd) represents the discharge energy of the energy storage device, E(cd) represents the charging energy of the energy storage device, and ξ represents the new energy storage impact coefficient.

5. The new energy storage method based on high-efficiency energy conversion technology according to claim 1 is characterized in that: The model of the new energy storage influence coefficient in the new energy storage efficiency index among the various indicators of the new energy storage performance is: Where T(b) represents the standard deviation of the temperature at each point of the energy storage device, T(p) represents the average temperature at each point of the energy storage device, Pc represents the power consumption of the cooling system, Sc represents the power consumption of the energy storage system, and Rh max Indicates the maximum ambient humidity of the energy storage system, Rh min Indicates the minimum ambient humidity of the energy storage system, T max Indicates the maximum ambient temperature of the energy storage system, T min It represents the minimum ambient temperature of the energy storage system. a1 and a2 represent the weights of the thermal management efficiency influencing factor and the environmental adaptability influencing factor, respectively.

6. The new energy storage method based on high-efficiency energy conversion technology according to claim 1 is characterized in that: The model of the new energy storage management efficiency index among the various indicators of the new energy storage performance is: Where Nemi represents the new energy storage management efficiency index, E(p) represents the predicted demand energy, E(a) represents the actual demand energy, Sc(aft) represents the power consumption after intelligent scheduling, Sc(bef) represents the power consumption before intelligent scheduling, and t_r represents the intelligent scheduling response time.

7. The new energy storage method based on high-efficiency energy conversion technology according to claim 1 is characterized in that: The qualification coefficients of various indicators of the new energy storage system include the following steps: Step 3.1: Substitute the new energy conversion efficiency index Neei obtained from the new energy conversion evaluation index analysis unit into the formula: ρ(Neei)=exp[(Neei / Neei0)-1], where ρ(Neei) represents the qualified coefficient of the new energy conversion efficiency, and Neei0 represents the set value; Step 3.2: Substitute the new energy storage efficiency index Nesi obtained from the new energy storage evaluation index analysis unit into the formula: ρ(Nesi)=exp[(Nesi / Nesi0)-1], where ρ(Nesi) represents the qualified coefficient of new energy storage efficiency, and Nesi0 represents the set value; Step 3.3: Substitute the new energy storage management efficiency index Nemi obtained from the new energy storage management index analysis unit into the formula: ρ(Nemi)=exp[(Nemi / Nemi0)-1], where ρ(Nemi) represents the qualified coefficient of the new energy storage management efficiency, and Nemi0 represents the set value.

8. The new energy storage method based on high-efficiency energy conversion technology according to claim 1 is characterized in that: The comprehensive analysis model of the comprehensive index of new energy storage performance is: Neci=b1×ρ(Neei)+b2×ρ(Nesi)+b3×ρ(Nemi), wherein Neci represents the comprehensive index of new energy storage performance, and b1, b2, and b3 represent the weights of the qualified coefficient ρ(Neei) of new energy conversion efficiency, the qualified coefficient ρ(Nesi) of new energy storage efficiency, and the qualified coefficient ρ(Nemi) of new energy storage management efficiency, respectively.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program in the storage device to implement a new energy storage method based on high-efficiency energy conversion technology as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement a new energy storage method based on high-efficiency energy conversion technology as described in any one of claims 1-8.

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