Wind and light storage system test method

Abstract

The embodiment of the invention discloses a wind and light storage system test method, which comprises the following steps: acquiring multiple groups of test data of a wind and light storage system under different test parameters, and determining performance indexes of the wind and light storage system corresponding to each group of test data according to output power, maximum power point efficiency and residual capacity in each group of test data, then determining the performance attenuation value of the wind and light storage system corresponding to each group of test data according to the thermal degradation activation energy, the accumulated damage effect and the aging factor in each group of test data, and finally determining the performance attenuation value of the wind and light storage system according to the output power, the maximum power point efficiency and the residual capacity in each group of test data. And determining a test result of the wind and light storage system according to the performance index and the performance attenuation value corresponding to each group of test data. By providing a set of comprehensive and effective test solution, the performance of the wind and light storage system under the actual operation condition can be comprehensively and accurately evaluated, so that the requirements of accurate test and reliable evaluation on the wind and light storage system are met.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power engineering testing, and in particular to a wind-solar-storage system testing method. BACKGROUND

[0002] Under the background of the global energy structure accelerating towards clean and low-carbon transformation, the demand for clean energy is showing an explosive growth trend, and renewable energy technologies have also made great progress. As an innovative energy solution that integrates wind energy, solar energy and energy storage technology, wind-solar-storage power equipment has become increasingly important in the energy supply system due to its significant environmental advantages and sustainability features, and has become an indispensable key link in the construction of distributed energy systems and smart grids. As the core component of the system, wind-solar-storage power equipment realizes the organic integration of wind power generation, solar power generation and energy storage.

[0003] However, wind-solar-storage power equipment faces many severe challenges in actual operation. On the one hand, the natural environment is complex and variable, and meteorological factors such as wind speed and light intensity are uncertain and volatile, which will directly affect the power generation efficiency of wind turbine generators and photovoltaic modules; on the other hand, the operation state of the power grid is not constant, and the fluctuation of parameters such as voltage and frequency of the power grid will put higher requirements on the grid-connected operation and power quality of wind-solar-storage power equipment. In addition, after a long time of operation, the equipment will inevitably show performance degradation, such as capacity attenuation of battery energy storage systems and wear of mechanical parts, which puts extremely strict standards on the comprehensive performance, reliability and durability of wind-solar-storage power equipment.

[0004] In the prior art, there have been some degree of testing method research and application for single wind power equipment, photovoltaic power equipment or energy storage equipment, and these testing methods can evaluate the performance of the equipment to some extent. However, when wind power generation, photovoltaic power generation and energy storage are integrated into a whole wind-solar-storage system, there is a lack of a complete and comprehensive testing solution. Therefore, the existing single equipment testing method cannot comprehensively and accurately evaluate the performance of the wind-solar-storage system under actual operating conditions, and it is difficult to meet the demand for precise testing and reliable evaluation of the wind-solar-storage system. SUMMARY

[0005] Therefore, it is necessary to propose a wind-solar-storage system testing method to provide a comprehensive and effective testing solution to comprehensively and accurately evaluate the performance of the wind-solar-storage system under actual operating conditions, so as to meet the demand for precise testing and reliable evaluation of the wind-solar-storage system.

[0006] To achieve the above-mentioned purpose, the present application provides a wind-solar-storage system testing method in the first aspect, which comprises:

[0007] obtaining a plurality of sets of test data of the wind-solar-storage system under different test parameters, the test data comprising output power of a wind turbine generator, maximum power point efficiency of a photovoltaic generator assembly, and remaining capacity of an energy storage device in the wind-solar-storage system, and thermal degradation activation energy, cumulative damage effect, and aging factor of the wind-solar-storage system;

[0008] determining a performance index of the wind-solar-storage system corresponding to each set of test data according to the output power, the maximum power point efficiency, and the remaining capacity in the set of test data;

[0009] determining a performance degradation value of the wind-solar-storage system corresponding to each set of test data according to the thermal degradation activation energy, the cumulative damage effect, and the aging factor in the set of test data;

[0010] determining a test result of the wind-solar-storage system according to the output power, the maximum power point efficiency, and the remaining capacity in each set of test data, and the performance index and the performance degradation value corresponding to each set of test data.

[0011] Optionally, the determining of the performance index of the wind-solar-storage system corresponding to each set of test data according to the output power, the maximum power point efficiency, and the remaining capacity in the set of test data comprises:

[0012] determining the performance index of the wind-solar-storage system corresponding to each set of test data by using a formula Y n = β0+ β wind × P n + β sun × η n + β save × Q n + c × Afe + ε.

[0013] In the formula, Y n is the performance index corresponding to the nth set of test data, β0is an initial regression coefficient of the wind-solar-storage system, β wind is a first regression coefficient of the wind turbine generator, P n is the output power in the nth set of test data, β sun is a second regression coefficient of the photovoltaic generator assembly, η n is the maximum power point efficiency in the nth set of test data, β save is a third regression coefficient of the energy storage device, Q n is the remaining capacity in the nth set of test data, c is a final regression coefficient of the wind-solar-storage system, Afe is the service life of the wind-solar-storage system, and ε is a random error term.

[0014] Optionally, the method further comprises:

[0015] determining a first number of groups in which the output power meets a preset output power range among the groups of test data, and a second number of groups in which the output power meets the preset output power range and the performance index corresponding to the group meets a preset performance index range among the groups of test data;

[0016] determining a third number of groups in which the maximum power point efficiency meets a preset maximum power point efficiency range among the groups of test data, and a fourth number of groups in which the maximum power point efficiency meets the preset maximum power point efficiency range and the performance index corresponding to the group meets the preset performance index range among the groups of test data;

[0017] determining a fifth number of groups in which the remaining capacity meets a preset remaining capacity range among the groups of test data, and a sixth number of groups in which the remaining capacity meets the preset remaining capacity range and the performance index corresponding to the group meets the preset performance index range among the groups of test data;

[0018] determining a first correlation between the output power and the performance index according to the first number and the second number, a second correlation between the maximum power point efficiency and the performance index according to the third number and the fourth number, and a third correlation between the remaining capacity and the performance index according to the fifth number and the sixth number;

[0019] optimizing the first regression coefficient according to the first correlation, optimizing the second regression coefficient according to the second correlation, and optimizing the third regression coefficient according to the third correlation;

[0020] using the optimized first regression coefficient, the second regression coefficient and the third regression coefficient, re-determining the performance index of the wind-solar-storage system corresponding to each group of test data according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data.

[0021] Optionally, the determining a first correlation between the output power and the performance index according to the first number and the second number, a second correlation between the maximum power point efficiency and the performance index according to the third number and the fourth number, and a third correlation between the remaining capacity and the performance index according to the fifth number and the sixth number comprises:

[0022] using the formula determining the first correlation, the second correlation and the third correlation;

[0023] wherein N is the total number of groups of test data, when i is 1, is the second number, is the first quantity, Confidence (X1→Y) is the first correlation, i is 2, is the fourth quantity, is the third quantity, Confidence (X2→Y) is the second correlation, i is 3, is the sixth quantity, is the fifth quantity, Confidence (X3→Y) is the third correlation.

[0024] Optionally, the determining of the performance degradation value of the wind-solar-storage system corresponding to each group of test data according to the thermal degradation activation energy, the cumulative damage effect and the aging factor in each group of test data comprises:

[0025] determining the performance degradation value of the wind-solar-storage system corresponding to each group of test data by using the formula

[0026] wherein, k n (T) is the performance degradation value of the nth group of test data at the current temperature T, A is the initial performance degradation coefficient of the wind-solar-storage system, e is the natural constant, E a,n is the thermal degradation activation energy in the nth group of test data, k B is the Boltzmann constant, T is the current temperature, f n (N T ) is the cumulative damage effect of the nth group of test data at the current temperature T after N T temperature cycles, l n (t) is the aging factor in the nth group of test data.

[0027] Optionally, the obtaining of the multiple groups of test data of the wind-solar-storage system under different test parameters comprises:

[0028] adjusting the test parameters of the wind-solar-storage system multiple times according to the energy management strategy of the wind-solar-storage system and the preset standard, and before each adjustment, determining the energy management strategy of the wind-solar-storage system according to the state of charge of the energy storage device at the next moment, so as to obtain the multiple groups of test data of the wind-solar-storage system under different test parameters;

[0029] wherein, the state of charge of the energy storage device at the next moment is determined by using the formula

[0030] In the above formula, SOC t+1 is the state of charge of the energy storage device at the next moment, SOC t ​​SoC is the state of charge of the energy storage device at the current time, ω is the self-discharge rate of the energy storage device, Δt is the time interval between the current time and the next time, ΔE is the energy charged or discharged by the energy storage device in the time interval, and C is the total energy of the energy storage device.

[0031] Optionally, the method further comprises:

[0032] determining the output power of the wind turbine generator set under different test parameters by using the formula

[0033] or, determining the output power of the wind turbine generator set under different test parameters by using the formula

[0034] wherein P n is the output power of the wind turbine generator set under the nth test parameter, λ is the correction coefficient between the output power of the wind turbine generator set and the wind speed, P r is the rated power of the wind turbine generator set, V n is the wind speed in the nth test parameter, V r is the rated wind speed corresponding to the rated power of the wind turbine generator set, ρ n is the air density in the nth test parameter, A wind is the swept area of the wind turbine generator set, C p is the power coefficient of the wind turbine generator set, and δ is the aerodynamic efficiency of the wind turbine generator set.

[0035] Optionally, the method further comprises:

[0036] determining the maximum power point efficiency of the photovoltaic power generation assembly under different test parameters by using the formula

[0037] wherein η n is the maximum power point efficiency of the photovoltaic power generation assembly under the nth test parameter, α is the temperature coefficient of the photovoltaic power generation assembly, P max is the output power of the photovoltaic power generation assembly at the maximum power point, G n is the solar radiation intensity per unit area in the nth test parameter, and A sun is the effective area of the photovoltaic power generation assembly.

[0038] Optionally, the method further comprises:

[0039] determining the remaining capacity of the energy storage device under different test parameters by using the formula Q n = Q0 × (1 - DOD n ) b × o​​​

[0040] wherein Q n is the remaining capacity of the energy storage device under the nth test parameter, Q0 is the initial capacity of the energy storage device, DOD n is the depth of discharge in the nth test parameter, b is the Peukert constant, and o is the temperature coefficient of the energy storage device.

[0041] Optionally, the determining the test result of the wind-solar-storage system according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the performance index and the performance attenuation value corresponding to each group of test data comprises:

[0042] obtaining a standard test parameter range table of the wind-solar-storage system;

[0043] determining a first average value and a first standard deviation of the output power in each group of test data, a second average value and a second standard deviation of the maximum power point efficiency in each group of test data, and a third average value and a third standard deviation of the remaining capacity in each group of test data;

[0044] determining the test result of the wind-solar-storage system according to the first average value, the first standard deviation, the second average value, the second standard deviation, the third average value, the third standard deviation, the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the performance index and the performance attenuation value corresponding to each group of test data, and the standard test parameter range table.

[0045] To achieve the above object, the present application provides a wind-solar-storage system testing device in the second aspect, which comprises:

[0046] an obtaining module, configured to obtain a plurality of groups of test data of the wind-solar-storage system under different test parameters, wherein the test data comprises the output power of a wind turbine generator set, the maximum power point efficiency of a photovoltaic power generation assembly and the remaining capacity of an energy storage device in the wind-solar-storage system, and the thermal degradation activation energy, the cumulative damage effect and the aging factor of the wind-solar-storage system;

[0047] a first determining module, configured to determine the performance index of the wind-solar-storage system corresponding to each group of test data according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data;

[0048] a second determining module, configured to determine the performance attenuation value of the wind-solar-storage system corresponding to each group of test data according to the thermal degradation activation energy, the cumulative damage effect and the aging factor in each group of test data;

[0049] The third determining module is configured to determine the test result of the wind-solar-storage system according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the performance index and the performance attenuation value corresponding to each group of test data.

[0050] To achieve the above object, the present application provides, in a third aspect, a computer readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the method according to any one of the first aspect.

[0051] To achieve the above object, the present application provides, in a fourth aspect, a computer device comprising a memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, causes the processor to perform the method according to any one of the first aspect.

[0052] By the method, a plurality of groups of test data of the wind-solar-storage system under different test parameters are obtained, the test data including the output power of the wind turbine generator, the maximum power point efficiency of the photovoltaic power generation assembly and the remaining capacity of the energy storage device, and the thermal degradation activation energy, the cumulative damage effect and the aging factor of the wind-solar-storage system, the performance index of the wind-solar-storage system corresponding to each group of test data is determined according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data, the performance attenuation value of the wind-solar-storage system corresponding to each group of test data is determined according to the thermal degradation activation energy, the cumulative damage effect and the aging factor in each group of test data, and the test result of the wind-solar-storage system is determined according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the performance index and the performance attenuation value corresponding to each group of test data; that is, by comprehensively and systematically obtaining and analyzing the performance parameters of the wind-solar-storage system, the independent performance test of the wind power generation, the photovoltaic power generation and the energy storage is combined with the system integrated linkage test, a comprehensive and effective test solution is provided, the performance of the wind-solar-storage system under actual operation conditions can be comprehensively and accurately evaluated, and the demand for accurate test and reliable evaluation of the wind-solar-storage system is met. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only show some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0054] In the formula, the parameters are as follows:

[0055] Figure 1A schematic diagram of a wind-solar-storage system test method in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of a wind-solar-storage system test method in an embodiment of the present application;

[0057] Figure 3 An internal structure diagram of a computer device in some embodiments. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0059] Under the background of the global energy structure accelerating the transformation towards clean and low-carbon, the demand for clean energy is showing an explosive growth trend, and renewable energy technology has also made great progress. As an innovative energy solution integrating wind power, solar power and energy storage technology, wind-solar-storage power equipment has become increasingly important in the energy supply system due to its significant environmental advantages and sustainability features, and has become an indispensable key link in the construction of distributed energy systems and smart grids. As the core component of the system, wind-solar-storage power equipment realizes the organic integration of wind power, solar power generation and energy storage.

[0060] However, wind-solar-storage power equipment faces many severe challenges in actual operation. On the one hand, the natural environment is complex and changeable, and meteorological factors such as wind speed and light intensity are uncertain and volatile, which will directly affect the power generation efficiency of wind turbine generators and photovoltaic modules; on the other hand, the operation state of the power grid is not constant, and the fluctuation of parameters such as voltage and frequency of the power grid will put higher requirements on the grid-connected operation and power quality of wind-solar-storage power equipment. In addition, after a long time of operation, the equipment will inevitably show performance degradation, such as capacity attenuation of battery energy storage systems and wear of mechanical parts, which puts extremely strict standards on the comprehensive performance, reliability and durability of wind-solar-storage power equipment.

[0061] In the prior art, there are certain degree of test method research and application for single wind power generation equipment, photovoltaic power generation equipment or energy storage equipment, which can evaluate the performance status of the equipment to a certain extent. However, when the wind power generation, photovoltaic power generation and energy storage are integrated into a whole system, there is a lack of a perfect and comprehensive test solution. Therefore, the existing single device test method cannot comprehensively and accurately evaluate the performance of the wind-solar-storage system under actual operating conditions, and it is difficult to meet the demand for precise testing and reliable evaluation of the wind-solar-storage system.

[0062] To solve the above problems, the present application provides a wind-solar-storage system test method, which can comprehensively and accurately evaluate the performance of the wind-solar-storage system under actual operating conditions by providing a comprehensive and effective test solution, so as to meet the demand for precise testing and reliable evaluation of the wind-solar-storage system. The specific implementation principle will be described in detail in the following embodiments.

[0063] In a first aspect, the present application provides a wind-solar-storage system test method.

[0064] Please refer to Figure 1 , a schematic diagram of a wind-solar-storage system test method in an embodiment of the present application, which method comprises:

[0065] Step 110: Obtain multiple sets of test data of the wind-solar-storage system under different test parameters, the test data including the output power of the wind turbine generator set, the maximum power point efficiency of the photovoltaic power generation assembly and the remaining capacity of the energy storage device in the wind-solar-storage system, and the thermal degradation activation energy, cumulative damage effect and aging factor of the wind-solar-storage system.

[0066] Among them, the test parameter indicates the parameter to be changed in the test process of the wind-solar-storage system; the thermal degradation activation energy is used to reflect the influence of temperature on the performance degradation rate of the wind-solar-storage system; the cumulative damage effect is used to reflect the cumulative influence of the damage of the wind-solar-storage system with time; and the aging factor is used to describe the influence of the aging of the wind-solar-storage system with time.

[0067] As for the parameters contained in the test parameters, in some embodiments, the test parameters can include but are not limited to temperature, humidity, air pressure, wind speed, light intensity, starting wind speed, rated speed, safety shutdown threshold, light intensity range, temperature compensation coefficient, upper limit of charging voltage, discharge depth, balancing strategy, air density, solar radiation intensity, etc. Of course, the number of specific parameters contained in the test parameters can be increased or decreased by the operator according to the actual demand, which is not limited here.

[0068] For the acquisition mode of multiple sets of test data, in some embodiments, the test parameters can be adjusted multiple times according to preset standards to obtain multiple sets of test data of the wind-solar-storage system under different test parameters; wherein the preset standards can be obtained by the operator according to a large amount of experience, experiments or statistics and pre-set, of course, the operator can also set according to the actual demand, which will not be repeated here.

[0069] It should be particularly pointed out that before testing the wind-solar-storage system, the wind-solar-storage system also needs to be connected with the test platform through the standardized interface, so as to facilitate the adjustment of the test parameters.

[0070] Step 120: According to the output power, maximum power point efficiency and remaining capacity in each set of test data, the performance index of the wind-solar-storage system corresponding to each set of test data is determined.

[0071] For the determination method of the performance index, in some embodiments, a multiple regression analysis function formula can be used to determine the performance index corresponding to each set of test data according to the output power, maximum power point efficiency and remaining capacity in each set of test data.

[0072] Step 130: According to the thermal degradation activation energy, cumulative damage effect and aging factor in each set of test data, the performance attenuation value corresponding to each set of test data is determined.

[0073] For the determination method of the performance attenuation value, in some embodiments, the Arrhenius equation can be used to determine the performance attenuation value of the wind-solar-storage system corresponding to each set of test data according to the thermal degradation activation energy, cumulative damage effect and aging factor in each set of test data.

[0074] Step 140: According to the output power, maximum power point efficiency and remaining capacity in each set of test data, and the performance index and performance attenuation value corresponding to each set of test data, the test result of the wind-solar-storage system is determined.

[0075] For the determination method of the test result, in some embodiments, the test result can be determined according to the comparison result between the output power, maximum power point efficiency and remaining capacity in each set of test data, and the performance index and performance attenuation value corresponding to each set of test data, and the corresponding each threshold range.

[0076] In other embodiments, a test report can also be generated according to the output power, maximum power point efficiency and remaining capacity in each set of test data, and the performance index and performance attenuation value corresponding to each set of test data, and the corresponding each threshold range.

[0077] In the embodiments of the present application, by comprehensively and systematically acquiring and analyzing various performance parameters of the wind-solar-storage system, the independent performance test of the wind power generation, the photovoltaic power generation and the energy storage device is combined with the system integrated linkage test, a comprehensive and effective test solution is provided, the performance of the wind-solar-storage system under actual operation conditions can be comprehensively and accurately evaluated, and the needs of accurate test and reliable evaluation of the wind-solar-storage system are met.

[0078] In addition to comprehensively and accurately assessing the performance of the wind-solar-storage system under actual operating conditions to meet the needs of precise testing and reliable evaluation, the wind-solar-storage system testing method proposed by the present application also has the following advantages: precise positioning of problem links: by comprehensively obtaining various test data of the wind turbine generator, photovoltaic power generation component and energy storage device, including output power, maximum power point efficiency, remaining capacity and parameters reflecting system performance degradation (thermal degradation activation energy, cumulative damage effect, aging factor) and the like, the specific link of poor system performance can be accurately positioned, such as whether the wind power generation part is greatly affected by the environment, whether the energy storage device ages too quickly, or whether the photovoltaic power generation component efficiency is not up to standard, etc., providing a clear direction for subsequent research and development improvement; accelerate technology iteration: as the system performance can be comprehensively evaluated, researchers can optimize equipment design, improve material selection or adjust control strategies according to the test results, thereby accelerating the iterative upgrade of wind-solar-storage power equipment technology and promoting the technological progress of the entire industry; optimize system configuration: in distributed energy system and smart grid construction projects, accurate performance evaluation can help optimize the configuration of the wind-solar-storage system, such as determining the appropriate capacity ratio of wind turbine generators, photovoltaic power generation components and energy storage devices according to the test results, so that the system meets the energy supply demand while reducing costs and improving economic efficiency; reduce construction risk: through comprehensive testing and evaluation, potential problems and risks of the system can be found in advance, such as performance fluctuations of equipment under certain environmental conditions, performance degradation after long-term operation, etc., so that appropriate preventive measures can be taken before the project is constructed, reducing the construction risk and ensuring the smooth implementation of the project; develop a scientific maintenance plan: based on performance degradation values and other data, a scientific maintenance plan can be developed to understand the performance degradation law of equipment under different operating conditions, so that the maintenance cycle and content can be reasonably arranged, such as replacing or repairing severely aged components in advance to avoid equipment failure and improve the reliability and stability of the system; real-time monitoring and early warning: the data obtained by the testing method can provide a basis for real-time monitoring and early warning of the system, and by establishing a data monitoring platform, the current operating data can be compared with the test data in real time, and an early warning can be issued in a timely manner when an abnormal situation occurs, so that the operating personnel can take measures quickly to ensure the normal operation of the system; provide market decision basis: for energy market participants such as power companies and energy investors, accurate performance evaluation results can provide an important basis for their decision-making, and understanding the actual performance of the wind-solar-storage system can help them plan energy procurement, sales strategies and optimize energy resource allocation to improve market competitiveness; assist in policy making: when formulating energy policies, the government and relevant departments need to accurately understand the technical level and actual operation of wind-solar-storage power equipment, and the testing method proposed by the present application can provide comprehensive and reliable data support to help policy makers formulate policies that are more in line with the needs of industry development, such as subsidy policies and grid connection standards, to promote the healthy development of the clean energy industry.

[0079] In an implementable implementation, step 120 in the above embodiments determines the performance index of the wind-solar-storage system corresponding to each set of test data according to the output power, the maximum power point efficiency and the residual capacity in each set of test data, including:

[0080] The performance index of the wind-solar-storage system corresponding to each set of test data is determined by the formula Y n = β0+ β wind × P n + β sun × η n + β save × Q n + c × Afe+ ε.

[0081] Wherein, Y n is the performance index corresponding to the nth set of test data, β0is the initial regression coefficient of the wind-solar-storage system, β wind is the first regression coefficient of the wind turbine set, P n is the output power in the nth set of test data, β sun is the second regression coefficient of the photovoltaic generator set, η n is the maximum power point efficiency in the nth set of test data, β save is the third regression coefficient of the energy storage device, Q n is the residual capacity in the nth set of test data, c is the end regression coefficient of the wind-solar-storage system, Afe is the service life of the wind-solar-storage system, and ε is a random error term.

[0082] It should be noted that the service life can be used to reflect the wear and tear degree, aging state and other factors of the wind-solar-storage system; the end regression coefficient corresponds to the service life, and the end regression coefficient can be used to reflect the influence degree of the service life on the performance index of the wind-solar-storage system.

[0083] In the embodiments of the present application, the performance index is quantitatively determined by a specific formula, which provides a more accurate and scientific basis for the performance evaluation of the wind-solar-storage system, and helps to comprehensively and deeply understand the system performance.

[0084] It can be understood that the precise quantitative evaluation: the formula takes into account the key parameters such as the output power of the wind turbine unit, the maximum power point efficiency of the photovoltaic power generation component and the remaining capacity of the energy storage device, and through the relationship between the regression coefficient and the variable, the corresponding performance index of the wind-solar-storage system of each test data is accurately quantified, which makes the performance evaluation no longer limited to qualitative description, but has specific and quantifiable numerical basis, improves the accuracy and reliability of the evaluation; consider the influence of service life: the formula introduces the service life of the wind-solar-storage system as a variable, and the corresponding end regression coefficient, which fully considers the performance degradation of the equipment after a long time of running, and can more truly reflect the performance change of the system in the actual running process, by considering the influence of service life, the evaluation result is more in line with the actual situation, and provides more valuable reference for subsequent maintenance, optimization and decision-making; convenient for comparative analysis: since a unified formula is used to calculate the performance index, the performance indexes between different test data groups are comparable, which makes us can conveniently compare and analyze the performance of the wind-solar-storage system under different operating conditions and different equipment configurations, find out the difference between the performance advantages and disadvantages, and provide a clear direction for the optimization and improvement of the system; support system optimization and decision-making: based on the performance index calculated by the formula, the researchers can more accurately understand the performance bottleneck of the system, and can carry out targeted device design optimization, control strategy adjustment, etc., the project constructors and operators can reasonably plan the system configuration and formulate the maintenance plan according to the performance index, and the energy market participants and policy makers can also make more scientific and reasonable decisions according to these indexes, so as to promote the continuous progress of the wind-solar-storage power equipment technology and the healthy development of the clean energy industry.

[0085] In a possible implementation, the method in the above embodiments further includes: determining a first number of groups in which the output power meets the preset output power range among the groups of test data, and a second number of groups in which the output power meets the preset output power range and the performance index corresponding to the group meets the preset performance index range among the groups of test data; determining a third number of groups in which the maximum power point efficiency meets the preset maximum power point efficiency range among the groups of test data, and a fourth number of groups in which the maximum power point efficiency meets the preset maximum power point efficiency range and the performance index corresponding to the group meets the preset performance index range among the groups of test data; determining a fifth number of groups in which the remaining capacity meets the preset remaining capacity range among the groups of test data, and a sixth number of groups in which the remaining capacity meets the preset remaining capacity range and the performance index corresponding to the group meets the preset performance index range among the groups of test data; determining a first correlation between the output power and the performance index according to the first number and the second number, a second correlation between the maximum power point efficiency and the performance index according to the third number and the fourth number, and a third correlation between the remaining capacity and the performance index according to the fifth number and the sixth number; optimizing the first regression coefficient according to the first correlation, optimizing the second regression coefficient according to the second correlation, and optimizing the third regression coefficient according to the third correlation; and determining the performance index of the wind-solar-storage system corresponding to each group of test data according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data by using the optimized first regression coefficient, the optimized second regression coefficient and the optimized third regression coefficient.

[0086] For the optimization mode of the regression coefficient, in some embodiments, the corresponding optimization value can be obtained according to the correlation, and the optimized regression coefficient can be determined according to the optimization value and the regression coefficient.

[0087] In some other embodiments, the regression coefficient can be optimized for multiple times, for example, 10 times.

[0088] In the embodiments of the present application, by optimizing the first regression coefficient, the second regression coefficient and the third regression coefficient according to the correlations between the parameters and the performance index, the accuracy and reliability of the performance index evaluation are improved, and a more accurate basis is provided for the optimization of the wind-solar-storage system.

[0089] It can be understood that the correlation between the parameters and the performance indicators can be accurately quantified by counting the number of groups that meet the preset range of the statistical output power, the maximum power point efficiency and the remaining capacity respectively, and the corresponding performance indicators also meet the preset range. This quantification method avoids subjective judgment, making the correlation evaluation more scientific and objective. The regression coefficients are optimized according to the correlation between the parameters and the performance indicators, which makes the regression coefficients more accurately reflect the influence of the parameters on the system performance, thereby improving the accuracy of the performance indicator evaluation. The evaluation reliability is improved by using the optimized regression coefficients to determine the performance indicators corresponding to each group of test data, making the performance indicator evaluation results more reliable. This reliability improvement helps researchers more accurately understand the system performance, providing strong support for subsequent device design optimization, control strategy adjustment, etc. The system optimization is supported based on the optimized performance indicator evaluation results, which can more accurately locate the system performance bottleneck and provide a clear direction for system optimization.

[0090] In a feasible implementation manner, the first correlation between the output power and the performance indicator is determined according to the first quantity and the second quantity, the second correlation between the maximum power point efficiency and the performance indicator is determined according to the third quantity and the fourth quantity, and the third correlation between the remaining capacity and the performance indicator is determined according to the fifth quantity and the sixth quantity in the above embodiment, including:

[0091] The first correlation, the second correlation and the third correlation are determined by using the formula

[0092] Wherein, N is the total number of test data groups, when i is 1, is the second quantity, is the first quantity, Confidence(X1→Y) is the first correlation, when i is 2, is the fourth quantity, is the third quantity, Confidence(X2→Y) is the second correlation, when i is 3, is the sixth quantity, is the fifth quantity, Confidence(X3→Y) is the third correlation.

[0093] In the embodiments of the present application, the correlation between the parameters and the performance indicators is calculated by a quantification formula, which helps to more accurately evaluate the performance of the wind-solar-storage system and provides strong support for system optimization.

[0094] ​It can be understood that quantitative evaluation correlation: through this formula, the correlation between output power, maximum power point efficiency, remaining capacity and performance indicators can be quantified in the form of specific numerical values, avoiding errors caused by subjective judgment, making the correlation evaluation more scientific and accurate; accurately locating influencing factors: by quantifying the correlation between each parameter and performance indicators, the key parameters that have a greater impact on system performance can be accurately located, providing a clear direction for subsequent system optimization and improvement; improving evaluation accuracy: based on the correlation of quantitative calculations, the degree of influence of each parameter on system performance can be more accurately evaluated, thereby improving the accuracy of the performance evaluation of the entire wind, solar and storage system; supporting system optimization decisions: accurate correlation evaluation results help R&D personnel and operators to formulate more reasonable system optimization strategies, such as adjusting equipment configuration, optimizing control strategies, etc., thereby improving the overall performance and reliability of the system.

[0095] In one feasible implementation, step 130 in the above embodiment, determining the performance degradation value of the wind-solar-storage system corresponding to each set of test data based on the thermal degradation activation energy, cumulative damage effect, and aging factor in each set of test data, includes:

[0096] Using the formula Determine the performance attenuation value of the wind-solar-storage system corresponding to each set of test data;

[0097] Among them, k n (T) is the performance attenuation value corresponding to the nth group of test data at the current temperature T, A is the initial performance degradation coefficient of the wind-solar-storage system, e is a natural constant, E a,n is the thermal decay activation energy in the nth set of test data, k B is the Boltzmann constant, T is the current temperature, f n (N T ) is the number of N test data in the nth group T The cumulative damage effect at the current temperature T after temperature cycles, l n (t) is the aging factor in the nth set of test data.

[0098] It should be noted that the initial performance degradation factor is the performance of the wind, solar and storage system at the reference temperature.

[0099] In the embodiments of the present application, the performance attenuation value is accurately quantified through a formula, providing a scientific basis for the performance evaluation and optimization of the wind, solar and storage system.

[0100] It can be understood that the precise quantitative evaluation: the formula comprehensively considers multiple key parameters such as thermal degradation activation energy, cumulative damage effect and aging factor, and accurately quantitatively calculates the performance degradation value of the wind-solar-storage system corresponding to each group of test data at the current temperature through mathematical operation, so that the performance degradation evaluation has specific and quantifiable numerical basis, and the accuracy and reliability of the evaluation are improved; comprehensively reflect the performance change: the thermal degradation activation energy in the formula reflects the influence of temperature on the performance degradation rate, the cumulative damage effect reflects the cumulative influence of damage over time, and the aging factor describes the influence of aging over time, which comprehensively covers the main factors affecting the performance degradation of the wind-solar-storage system, and can more truly reflect the performance change of the system in the actual operation process; support system optimization and decision-making: based on the performance degradation value calculated by the formula, the researchers can more accurately understand the rules and reasons of system performance degradation, and can carry out targeted device design optimization, material improvement or control strategy adjustment, etc., and the project constructors and operators can reasonably plan the system configuration and develop maintenance plans according to the performance degradation value, so as to promote the continuous progress of wind-solar-storage power equipment technology and the healthy development of clean energy industry.

[0101] In a feasible implementation manner, the step 110 in the above embodiment of acquiring multiple groups of test data of the wind-solar-storage system under different test parameters comprises: adjusting the test parameters of the wind-solar-storage system multiple times according to the energy management strategy of the wind-solar-storage system and a preset standard, and before each adjustment, determining the energy management strategy of the wind-solar-storage system according to the state of charge of the energy storage device at the next moment, so as to acquire multiple groups of test data of the wind-solar-storage system under different test parameters.

[0102] As to the determination manner of the state of charge of the energy storage device at the next moment, in some embodiments, the formula may be used to determine the state of charge of the energy storage device at the next moment; wherein, SOC t+1 is the state of charge of the energy storage device at the next moment, SOC t is the state of charge of the energy storage device at the current moment, ω is the self-discharge rate of the energy storage device, Δt is the time interval between the current moment and the next moment, ΔE is the energy charged or discharged by the energy storage device within the time interval, and C is the total energy of the energy storage device.

[0103] Wherein, the energy management strategy refers to the energy flow of the wind turbine generator, the photovoltaic power generation component and the energy storage device in the wind-solar-storage system, and the power generation of the wind turbine generator and the photovoltaic power generation component, as well as the charging or discharging of the energy storage device; the preset standard can be set by the operator according to a large amount of experience, experiment or statistics in advance, of course, it can also be set by the operator according to the actual demand; the self-discharge rate is used to reflect the rate of natural reduction of the energy of the energy storage device in the static state.

[0104] For the determination manner of the energy management strategy, in some embodiments, the energy management strategy can be determined according to a comparison result between the state of charge of the energy storage device at the next moment and the state of charge threshold value; wherein the state of charge threshold value can be set in advance by the operator according to a large amount of experience, experiment or statistics, of course, can also be set by the operator according to the actual demand, not limited here.

[0105] In the embodiments of the present application, by determining the energy management strategy to adjust the test parameters, various actual working conditions of the wind-solar-storage system can be accurately simulated, and the reliability of the test data is improved.

[0106] It can be understood that accurately simulating the actual working condition: by determining the energy management strategy of the wind-solar-storage system according to the state of charge of the energy storage device at the next moment, and adjusting the test parameters multiple times to obtain multiple sets of test data, the energy trend and power generation, charging and discharging of the wind-solar-storage system in actual operation can be more realistically simulated, and the test data is closer to the actual working condition; improve the reliability of the test data: since the state of charge change of the energy storage device and the influence of the energy management strategy are considered, the test data obtained is more representative and reliable, and can more accurately reflect the performance of the wind-solar-storage system under different conditions, providing a solid data foundation for subsequent performance evaluation and system optimization.

[0107] In a feasible implementation manner, the method in the above embodiments further includes:

[0108] determining the output power of the wind turbine generator set under different test parameters by using the formula

[0109] or, determining the output power of the wind turbine generator set under different test parameters by using the formula

[0110] wherein, P n is the output power of the wind turbine generator set under the nth test parameter, λ is the correction coefficient between the output power of the wind turbine generator set and the wind speed, P r is the rated power of the wind turbine generator set, V n is the wind speed in the nth test parameter, V r is the rated wind speed corresponding to the rated power of the wind turbine generator set, ρ n is the air density in the nth test parameter, A wind is the swept area of the wind turbine generator set, C p is the power coefficient of the wind turbine generator set, and δ is the aerodynamic efficiency of the wind turbine generator set.

[0111] In the embodiments of the present application, the output power is accurately calculated by the formula, which provides accurate data support for performance evaluation of the wind-solar-storage system. ​​

[0112] It can be understood that the precise quantitative calculation: the output power of the wind turbine generator set under different test parameters is accurately calculated by the formula, which avoids the error caused by subjective estimation, and makes the calculation result of the output power more accurate and reliable; considering multiple factors: the formula comprehensively considers multiple key factors such as wind speed, air density, wind wheel swept area, power coefficient and aerodynamic efficiency, fully reflects the influence of these factors on the output power of the wind turbine generator set, and can more truly simulate the actual operation situation; support performance evaluation: accurate output power data is an important basis for evaluating the performance of the wind-solar-storage system, based on which the performance of the system under different working conditions can be more accurately analyzed, which provides a strong basis for the optimization and improvement of the system; guide system design: in the design and planning stage of the wind-solar-storage system, accurate output power calculation results are helpful to reasonably determine the selection and configuration of the wind turbine generator set, and improve the overall performance and economic benefit of the system.

[0113] In a feasible implementation manner, the method in the above embodiment further includes:

[0114] The maximum power point efficiency of the photovoltaic power generation assembly under different test parameters is determined by using the formula

[0115] η n = α · P m · G n · A n n η n is the maximum power point efficiency of the photovoltaic power generation assembly under the nth test parameter, α is the temperature coefficient of the photovoltaic power generation assembly, P m is the output power of the photovoltaic power generation assembly at the maximum power point, G n is the solar radiation intensity per unit area in the nth test parameter, and A n is the effective area of the photovoltaic power generation assembly. max n sun

[0116] It should be noted that the temperature coefficient of the photovoltaic power generation assembly is used to weaken the influence of temperature on the power generation efficiency of the photovoltaic power generation assembly.

[0117] In the embodiment of the present application, the maximum power point efficiency of the photovoltaic power generation assembly is accurately quantitatively evaluated by the formula, which provides key data for performance evaluation of the wind-solar-storage system.

[0118] ​​​​It can be understood that: accurate quantitative evaluation: through the formula, the maximum power point efficiency of the photovoltaic power generation component under different test parameters can be accurately calculated, and the evaluation results are presented in the form of specific numerical values, avoiding subjective judgment and fuzzy estimation, and improving the accuracy and reliability of the evaluation; considering temperature influence: the temperature coefficient of the photovoltaic power generation component is introduced in the formula, which is used to weaken the influence of temperature on the power generation efficiency, so that the calculation result can more truly reflect the performance of the photovoltaic power generation component in the actual operation environment; support performance evaluation: the maximum power point efficiency is one of the key indicators for evaluating the performance of the photovoltaic power generation component, and the accurate calculation result provides an important basis for the performance evaluation of the wind-solar-storage system, which helps to comprehensively understand the performance of the system under different working conditions; guide system optimization: based on the accurate maximum power point efficiency data, the performance change of the photovoltaic power generation component under different conditions can be analyzed, which provides a direction for system optimization, such as adjusting the installation angle of the photovoltaic power generation component, selecting a more suitable component type, etc., so as to improve the overall performance of the wind-solar-storage system.

[0119] In a feasible implementation manner, the method in the above embodiment further includes:

[0120] The formula Q n = Q0 x (1-DOD n ) b o determines the remaining capacity of the energy storage device under different test parameters.

[0121] Wherein, Q n is the remaining capacity of the energy storage device under the nth test parameter, Q0 is the initial capacity of the energy storage device, DOD n is the discharge depth in the nth test parameter, b is the Peukert constant, and o is the temperature coefficient of the energy storage device.

[0122] It should be noted that the temperature coefficient of the energy storage device can reflect the influence of temperature on the remaining capacity of the battery.

[0123] In the embodiments of the present application, the formula is used to accurately quantify the remaining capacity of the energy storage device, and provides key data for the performance evaluation of the wind-solar-storage system.

[0124] It can be understood that: accurate quantitative evaluation: through the formula, the remaining capacity of the energy storage device under different test parameters can be accurately calculated, and the evaluation results are presented in the form of specific numerical values, avoiding subjective judgment and fuzzy estimation, and improving the accuracy and reliability of the evaluation; considering multiple factors: the formula comprehensively considers multiple key factors such as discharge depth, Peukert constant and temperature coefficient, fully reflects the influence of these factors on the remaining capacity of the energy storage device, and can more truly simulate the performance of the energy storage device in the actual operating environment; support performance evaluation: the remaining capacity of the energy storage device is one of the key indicators for evaluating the performance of the wind-solar-storage system, and accurate calculation results provide an important basis for performance evaluation of the wind-solar-storage system, which helps to fully understand the performance of the system under different working conditions; guide system optimization: based on accurate remaining capacity data of the energy storage device, the performance change of the energy storage device under different conditions can be analyzed, which provides direction for system optimization, such as adjusting the charge and discharge strategy of the energy storage device, selecting a more suitable energy storage type, etc., thereby improving the overall performance of the wind-solar-storage system.

[0125] In a feasible implementation manner, the step 140 in the above embodiment, according to the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the performance index and the performance attenuation value corresponding to each group of test data, determines the test result of the wind-solar-storage system, including: obtaining a standard test parameter range table of the wind-solar-storage system; determining a first average value and a first standard deviation of the output power in each group of test data, a second average value and a second standard deviation of the maximum power point efficiency in each group of test data, and a third average value and a third standard deviation of the remaining capacity in each group of test data; according to the first average value, the first standard deviation, the second average value, the second standard deviation, the third average value, the third standard deviation, the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the performance index and the performance attenuation value corresponding to each group of test data, and the standard test parameter range table, determining the test result of the wind-solar-storage system.

[0126] Among them, the standard code test parameter range table includes each parameter range corresponding to the first average value, the first standard deviation, the second average value, the second standard deviation, the third average value, the third standard deviation, the output power, the maximum power point efficiency, the remaining capacity, the performance index and the performance attenuation value.

[0127] For the determination method of the test result, in some embodiments, the test result can be determined according to the comparison results between the first average value, the first standard deviation, the second average value, the second standard deviation, the third average value, the third standard deviation, the output power, the maximum power point efficiency and the remaining capacity in each group of test data, and the corresponding each parameter range.

[0128] In the embodiments of the present application, the performance of the wind-solar-storage system is comprehensively and accurately evaluated by obtaining the standard test parameter range table of the wind-solar-storage system, and reliable test results are provided.

[0129] It can be understood that: comprehensive consideration: by obtaining the standard test parameter range table of the wind-solar-storage system, and determining the average value and standard deviation of the output power, maximum power point efficiency and remaining capacity, combined with each group of test data and the corresponding performance indicators and performance degradation values, comprehensive consideration can comprehensively reflect the performance of the wind-solar-storage system under different conditions; accurate determination of test results: according to the calculated average value, standard deviation and each group of test data, compared with each parameter range in the standard test parameter range table, the test results of the wind-solar-storage system can be accurately determined, avoiding the one-sidedness of single index evaluation, and improving the accuracy and reliability of the test results; support performance optimization: comprehensive test results help to accurately locate the advantages and disadvantages of the performance of the wind-solar-storage system, and provide clear direction for system performance optimization, and researchers can improve equipment design, adjust control strategy, etc. according to the test results, so as to improve the overall performance of the system; reduce the risk of operation: accurate test results can reveal the problems and potential risks that may exist in the actual operation of the wind-solar-storage system, such as unstable performance and rapid aging of components, which helps to take maintenance or replacement measures in time, reduces the risk of system operation, and ensures the stable and reliable operation of the system; provide decision basis: comprehensive test results provide scientific and reliable decision basis for energy market participants and policy makers, which helps to reasonably plan energy procurement, sales strategy, and develop policies more in line with the needs of industry development, and promote the healthy development of clean energy industry.

[0130] The present application provides a wind-solar-storage system test device in the second aspect.

[0131] Please refer to Figure 2 , a schematic diagram of a wind-solar-storage system test device in the embodiments of the present application, the device 210 includes:

[0132] The acquisition module 211 is configured to acquire a plurality of sets of test data of the wind-solar-storage system under different test parameters, the test data including the output power of the wind turbine generator set, the maximum power point efficiency of the photovoltaic power generation assembly, and the remaining capacity of the energy storage device in the wind-solar-storage system, and the thermal degradation activation energy, cumulative damage effect and aging factor of the wind-solar-storage system.

[0133] The first determination module 212 is configured to determine the performance indicators of the wind-solar-storage system corresponding to each set of test data according to the output power, maximum power point efficiency and remaining capacity in each set of test data.

[0134] The second determining module 213 is configured to determine a performance attenuation value of the wind-solar-storage system corresponding to each set of test data according to the thermal degradation activation energy, the cumulative damage effect and the aging factor in each set of test data.

[0135] The third determining module 214 is configured to determine the test result of the wind-solar-storage system according to the output power, the maximum power point efficiency and the remaining capacity in each set of test data, and the performance index and the performance attenuation value corresponding to each set of test data.

[0136] In the embodiments of the present application, the related content of the above-mentioned acquisition module 211, the first determining module 212, the second determining module 213 and the third determining module 214 can be referred to the content in the embodiments shown in the above-mentioned embodiments, and details are not described herein. Figure 1

[0137] It should be noted that the device 210 of the present application further includes some other modules, and it can be understood that the method of the present application has a one-to-one corresponding relationship with the device 210, and therefore some other modules of the device 210 of the present application are the corresponding content of the method of the present application in the above-mentioned embodiments.

[0138] In the embodiments of the present application, by comprehensively and systematically acquiring and analyzing various performance parameters of the wind-solar-storage system, the independent performance test of the wind power generation, the photovoltaic power generation and the energy storage is combined with the system integrated linkage test, a comprehensive and effective test solution is provided, the performance of the wind-solar-storage system under actual operation conditions can be comprehensively and accurately evaluated, and the demand for accurate test and reliable evaluation of the wind-solar-storage system is met.

[0139] ​In addition to comprehensively and accurately assessing the performance of the wind-solar-storage system under actual operating conditions to meet the needs of precise testing and reliable evaluation, the wind-solar-storage system testing device proposed by the present application also has the following advantages: precise positioning of problem links: by comprehensively obtaining various test data of the wind turbine generator, photovoltaic power generation component and energy storage device, including output power, maximum power point efficiency, remaining capacity and parameters reflecting system performance degradation (thermal degradation activation energy, cumulative damage effect, aging factor) and the like, the specific link of poor system performance can be accurately positioned, such as whether the wind power generation part is greatly affected by the environment, whether the energy storage device ages too quickly, or whether the photovoltaic power generation component efficiency is not up to standard, etc., providing a clear direction for subsequent research and development improvement; accelerate technology iteration: as the system performance can be comprehensively evaluated, researchers can optimize equipment design, improve material selection or adjust control strategies according to the test results, thereby accelerating the iterative upgrade of wind-solar-storage power equipment technology and promoting the technological progress of the entire industry; optimize system configuration: in distributed energy system and smart grid construction projects, accurate performance evaluation can help optimize the configuration of the wind-solar-storage system, such as determining the appropriate capacity ratio of wind turbine generators, photovoltaic power generation components and energy storage devices according to the test results, so that the system meets the energy supply demand while reducing costs and improving economic efficiency; reduce construction risk: through comprehensive testing and evaluation, potential problems and risks of the system can be found in advance, such as performance fluctuations of equipment under certain environmental conditions, performance degradation after long-term operation, etc., so that appropriate preventive measures can be taken before the project is constructed, reducing the construction risk and ensuring the smooth implementation of the project; develop a scientific maintenance plan: based on performance degradation values and other data, a scientific maintenance plan can be developed to understand the performance degradation law of equipment under different operating conditions, so that the maintenance cycle and content can be reasonably arranged, such as replacing or repairing severely aged components in advance to avoid equipment failure and improve the reliability and stability of the system; real-time monitoring and early warning: the data obtained by the testing device can provide a basis for real-time monitoring and early warning of the system, and by establishing a data monitoring platform, the current operating data can be compared with the test data in real time, and an early warning can be issued in a timely manner when an abnormal situation occurs, so that the operating personnel can take measures quickly to ensure the normal operation of the system; provide market decision basis: for energy market participants such as power companies and energy investors, accurate performance evaluation results can provide an important basis for their decision-making, and understanding the actual performance of the wind-solar-storage system can help them plan energy procurement, sales strategies and optimize energy resource allocation to improve market competitiveness; assist in policy making: when formulating energy policies, the government and relevant departments need to accurately understand the technical level and actual operation of wind-solar-storage power equipment, and the testing device of the present application can provide comprehensive and reliable data support to help policy makers formulate policies such as subsidies and grid connection standards that are more in line with the needs of industry development, thereby promoting the healthy development of the clean energy industry.

[0140] The application also provides a computer readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the wind-solar-storage system testing method in any of the above method embodiments.

[0141] The application also provides a computer device including a memory and a processor, the memory storing a computer program, which, when executed by the processor, causes the processor to perform the wind-solar-storage system testing method in any of the above method embodiments.

[0142] Figure 3 An internal structure diagram of the computer device in some embodiments is shown. The computer device can be a terminal, a server, or a gateway. As shown in the figure, the computer device includes a processor, a memory, and a network interface connected through a system bus. Figure 3

[0143] The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and can also store a computer program, which, when executed by the processor, can cause the processor to implement each step in the above method embodiments. The internal memory can also store a computer program, which, when executed by the processor, can cause the processor to perform each step in the above method embodiments. Those skilled in the art can understand that the computer device shown in the figure is only a block diagram of part of the structure related to the scheme of the application, and does not constitute a limitation on the computer device to which the scheme of the application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement. Figure 3

[0144] Those of ordinary skill in the art can understand that all or part of the processes in the above embodiments can be completed by a computer program instructing related hardware. The program can be stored in a non-volatile computer readable storage medium and, when executed, can include the processes of the above embodiments.

[0145] ​​Any reference to storage, memory, database or other medium herein includes non-volatile and / or volatile storage. Non-volatile storage can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), and / or flash memory. Volatile storage can include random access memory (RAM), which acts as external cache. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct Rambus dynamic RAM (DRDRAM), and / or Rambus dynamic RAM (RDRAM). The RAM can be 16 megabytes, 32 megabytes, 64 megabytes, or even larger in various types of supercomputers or servers. This disclosure contemplates any other such storage media.

[0146] Any combination of one or more computer-related aspects described herein can be implemented. For the sake of brevity, the numerous individual aspects of the various embodiments will not be described in detail. However, it should be understood that all combinations of the various aspects described herein can be implemented.

[0147] The above-described embodiments are merely illustrative for the present application and are not in limitation of the present application. It should be pointed out that, for those of ordinary skill in the art, some modifications and improvements can be made without departing from the concept of the present application, and these modifications and improvements should be considered within the scope of the present application. Therefore, the patent protection scope of the present application should be subject to the appended claims.

Claims

1. A wind-solar-storage system testing method, characterized in that: The method comprises: Acquire multiple sets of test data of the wind-solar-storage system under different test parameters, the test data including the output power of the wind turbine generator set in the wind-solar-storage system, the maximum power point efficiency of the photovoltaic power generation assembly, and the remaining capacity of the energy storage device, as well as the thermal decay activation energy, cumulative damage effect, and aging factor of the wind-solar-storage system; Determine the performance indicators of the wind-solar-storage system corresponding to each set of test data based on the output power, maximum power point efficiency and remaining capacity in each set of test data; Determine the performance attenuation value of the wind-solar-storage system corresponding to each set of test data based on the thermal decay activation energy, cumulative damage effect, and aging factor in each set of test data; The test results of the wind-solar-storage system are determined based on the output power, maximum power point efficiency and remaining capacity in each set of test data, and the performance indicators and performance attenuation values ​​corresponding to each set of test data.

2. The method according to claim 1, characterized in that Determining the performance indicators of the wind-solar-storage system corresponding to each set of test data according to the output power, maximum power point efficiency, and remaining capacity in each set of test data includes: Using the formula Y n =β0+β wind ×P n +β sun ×η n +β save ×Q n +c×Afe+ε to determine the performance index of the wind-solar-storage system corresponding to each set of test data; Among them, Y n is the performance index corresponding to the nth group of test data, β0 is the initial regression coefficient of the wind-solar-storage system, β wind is the first regression coefficient of the wind turbine generator set, P n is the output power in the nth group of test data, β sun is the second regression coefficient of the photovoltaic power generation group, η n is the maximum power point efficiency in the nth group of test data, β save is the third regression coefficient of the energy storage device, Q n is the remaining capacity in the nth group of test data, c is the end regression coefficient of the wind-solar-storage system, Afe is the service life of the wind-solar-storage system, and ε is the random error term.

3. The method according to claim 2, characterized in that The method further comprises: Determining, in each set of test data, a first number of groups whose output power satisfies a preset output power range, and a second number of groups whose output power satisfies the preset output power range and whose performance indicators of the corresponding groups of output power meet the preset performance indicator range; Determining, in each set of test data, a third number of groups whose maximum power point efficiency satisfies a preset maximum power point efficiency range, and a fourth number of groups whose maximum power point efficiency satisfies the preset maximum power point efficiency range and whose performance index of the group corresponding to the maximum power point efficiency satisfies the preset performance index range; Determining, in each set of test data, a fifth number of groups whose remaining capacity satisfies a preset remaining capacity range, and a sixth number of groups whose remaining capacity satisfies the preset remaining capacity range and whose performance indicators of the groups corresponding to the remaining capacity satisfy the preset performance indicator range; determining a first correlation between output power and a performance indicator based on the first number and the second number, determining a second correlation between maximum power point efficiency and a performance indicator based on the third number and the fourth number, and determining a third correlation between remaining capacity and a performance indicator based on the fifth number and the sixth number; optimizing the first regression coefficient according to the first correlation, optimizing the second regression coefficient according to the second correlation, and optimizing the third regression coefficient according to the third correlation; Using the optimized first regression coefficient, second regression coefficient and third regression coefficient, the performance indicators of the wind-solar-storage system corresponding to each set of test data are re-determined based on the output power, maximum power point efficiency and remaining capacity in each set of test data.

4. The method according to claim 3, characterized in that Determining a first correlation between output power and a performance indicator based on the first number and the second number, determining a second correlation between maximum power point efficiency and a performance indicator based on the third number and the fourth number, and determining a third correlation between remaining capacity and a performance indicator based on the fifth number and the sixth number includes: Using the formula determining the first association, the second association, and the third association; Among them, N is the total number of test data groups, when i is 1, is the second number, is the first quantity, Confidence(X1→Y) is the first correlation, when i is 2, is the fourth quantity, is the third quantity, Confidence(X2→Y) is the second correlation, when i is 3, is the sixth quantity, is the fifth quantity, and Confidence(X3→Y) is the third association.

5. The method according to claim 1, wherein Determining the performance attenuation value of the wind-solar-storage system corresponding to each set of test data according to the thermal decay activation energy, cumulative damage effect, and aging factor in each set of test data includes: Using the formula Determine the performance attenuation value of the wind-solar-storage system corresponding to each set of test data; Among them, k n (T) is the performance attenuation value corresponding to the nth group of test data at the current temperature T, A is the initial performance degradation coefficient of the wind-solar-storage system, e is a natural constant, E a,n is the thermal decay activation energy in the nth set of test data, k B is the Boltzmann constant, T is the current temperature, f n (N T ) is the number of N test data in the nth group T The cumulative damage effect at the current temperature T after temperature cycles, l n (t) is the aging factor in the nth set of test data.

6. The method according to claim 1, characterized in that The obtaining of multiple sets of test data of the wind-solar-storage system under different test parameters includes: According to the energy management strategy and preset standards of the wind-solar-storage system, the test parameters of the wind-solar-storage system are adjusted multiple times, and before each adjustment, the energy management strategy of the wind-solar-storage system is determined according to the state of charge of the energy storage device at the next moment, so as to obtain multiple sets of test data of the wind-solar-storage system under different test parameters; Among them, using the formula determining a state of charge of the energy storage device at a next moment; In the above formula, SOC t+1 is the state of charge of the energy storage device at the next moment, SOC t is the state of charge of the energy storage device at the current moment, ω is the self-discharge rate of the energy storage device, Δt is the time interval between the current moment and the next moment, ΔE is the energy charged or discharged by the energy storage device during the time interval, and C is the total energy of the energy storage device.

7. The method according to claim 1, characterized in that The method further comprises: Using the formula Determining the output power of the wind turbine generator set under different test parameters; Or, using the formula Determining the output power of the wind turbine generator set under different test parameters; Among them, P n is the output power of the wind turbine generator set under the nth test parameter, λ is the correction coefficient between the output power of the wind turbine generator set and the wind speed, P r is the rated power of the wind turbine generator set, V n is the wind speed in the nth test parameter, V r is the rated wind speed corresponding to the rated power of the wind turbine generator set, ρ n is the air density in the nth test parameter, A wind is the rotor swept area of ​​the wind turbine generator set, C p is the power coefficient of the wind turbine generator set, and δ is the aerodynamic efficiency of the wind turbine generator set.

8. The method according to claim 1, characterized in that The method further comprises: Using the formula Determining the maximum power point efficiency of the photovoltaic power generation assembly under different test parameters; Among them, η n is the maximum power point efficiency of the photovoltaic power generation component under the nth test parameter, α is the temperature coefficient of the photovoltaic power generation component, P max is the output power of the photovoltaic power generation component at the maximum power point, G n is the solar radiation intensity per unit area in the nth test parameter, A sun is the effective area of ​​the photovoltaic power generation component.

9. The method according to claim 1, characterized in that The method further comprises: Using the formula Q n =Q0×(1-DOD n ) b ×o determine the remaining capacity of the energy storage device under different test parameters; Among them, Q n is the remaining capacity of the energy storage device under the nth test parameter, Q0 is the initial capacity of the energy storage device, DOD n is the discharge depth in the nth test parameter, b is the Peukert constant, and o is the temperature coefficient of the energy storage device.

10. The method according to claim 1, characterized in that Determining the test results of the wind-solar-storage system according to the output power, maximum power point efficiency, and remaining capacity in each set of test data, and the performance indicators and performance attenuation values ​​corresponding to each set of test data, includes: Obtain a table of standard test parameter ranges for the wind-solar-storage system; Determining a first average value and a first standard deviation of the output power in each set of test data, a second average value and a second standard deviation of the maximum power point efficiency in each set of test data, and a third average value and a third standard deviation of the remaining capacity in each set of test data; The test results of the wind-solar-storage system are determined based on the first average value, the first standard deviation, the second average value, the second standard deviation, the third average value, the third standard deviation, the output power, maximum power point efficiency and remaining capacity in each group of test data, the performance indicators and performance attenuation values ​​corresponding to each group of test data, and the standard test parameter range table.

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