Parameter identification method and system for photovoltaic cell, storage medium and equipment

Abstract

The embodiment of the invention discloses a parameter identification method for a photovoltaic cell. The method comprises the following steps: constructing an equivalent circuit model and an objective function of a double-diode photovoltaic cell; identifying the parameters of the photovoltaic cell according to an NOA algorithm, and determining a current optimal parameter combination; based on the objective function, determining an output voltage and an output current corresponding to the current optimal parameter combination, fitting the output voltage and the output current with corresponding actual measurement values, and determining a fitting degree value; and when the fitting degree value meets a threshold range and the NOA algorithm converges, determining an optimal photovoltaic cell parameter according to a corresponding current optimal parameter combination when the NOA algorithm converges. According to the method, the accurate photovoltaic cell model is constructed, the efficient NOA algorithm is adopted for parameter identification, the target function is combined for error evaluation and optimization, and rapid and accurate identification of the photovoltaic cell parameters is effectively achieved.

Description

Technical Field

[0001] The present invention relates to the field of battery management technology, and in particular to a parameter identification method, system, storage medium and device for photovoltaic cells. Background Art

[0002] With the continuous development of society, solar energy has been vigorously promoted and developed worldwide due to its advantages such as renewability, cleanliness, pollution-free and wide distribution. As the core component of the solar power generation system, the performance of photovoltaic cells directly affects the power generation efficiency and stability of the entire photovoltaic power station.

[0003] During operation, photovoltaic cells are affected by multiple factors such as irradiance, temperature, and their own aging, which may cause changes in their power generation capacity. Therefore, accurate monitoring of the operating status of photovoltaic cells and real-time analysis of them are of great significance to ensure the stable operation of photovoltaic power stations. In the monitoring of photovoltaic cells, accurate fitting of the photovoltaic array characteristic curve is a common and effective method for evaluating the status of photovoltaic cells. However, due to the complexity and changeability of the actual working environment, the characteristic curve calculated based on standard parameters often has errors with the characteristic curve of the actual test, which limits our accurate judgment of the status of photovoltaic cells.

[0004] In order to solve this problem, most of the current research on mathematical models of photovoltaic cells adopts simplified engineering models. This type of model has been widely promoted in practical applications because of its relatively mature research, clear concepts and high accuracy. However, the measurable parameters of photovoltaic cells are mainly limited to voltage and current, while some important photovoltaic module characteristic parameters, such as the reverse saturation current, series resistance, and parallel resistance of the diode, still lack effective testing methods. Accurate identification of these parameters is crucial to constructing an accurate mathematical model of photovoltaic modules and thus improving the accuracy of characteristic curve fitting. Summary of the invention

[0005] Based on this, it is necessary to propose a parameter identification method for photovoltaic cells to address the above problems.

[0006] A method for identifying parameters of a photovoltaic cell, the method comprising the following steps:

[0007] Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell;

[0008] Identify the parameters of photovoltaic cells according to the NOA algorithm and determine the current optimal parameter combination;

[0009] Based on the objective function, determining the output voltage and output current corresponding to the current optimal parameter combination, fitting the output voltage and output current with corresponding actual measured values, and determining a fitting value;

[0010] When the fitness value satisfies a threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

[0011] In the above scheme, the construction of the equivalent circuit model and objective function of the dual-diode photovoltaic cell specifically includes: the expression of the equivalent circuit model of the dual-diode photovoltaic cell is:

[0012]

[0013] In the formula, I L and V L Respectively represent the output current and output voltage of the photovoltaic cell; I ph Represents photocurrent; I sh and I0 represent the reverse saturation current of the two diodes respectively; R s and R sh Respectively represent the series resistance and parallel resistance; a1 and a2 represent the diode ideal factor; V T represents thermal voltage;

[0014] The thermal voltage V T Defined as:

[0015]

[0016] Where T represents the battery temperature; K represents the Boltzmann constant; and q represents the electron charge.

[0017] In the above scheme, the equivalent circuit model and objective function of the dual-diode photovoltaic cell are constructed, specifically including: the expression of the objective function of the dual-diode photovoltaic cell is:

[0018]

[0019] In the formula, x represents the solution vector of the parameters to be identified, including the photocurrent I ph , the reverse saturation current of the diode I 01 ,I 02 , series resistance R s , parallel resistance R sh , diode ideal factors a1, a2; N represents the number of experimental data;

[0020] f(V L , I L , x) is expressed as:

[0021]

[0022] In the formula, I ph Represents photocurrent; I01 ,I 02 Respectively represent the reverse saturation current of the two diodes; R s Represents the series resistance; R sh represents the parallel resistance; a1 and a2 represent the ideal factors of the two diodes respectively.

[0023] In the above scheme, the identification of the parameters of the photovoltaic cell according to the NOA algorithm and the determination of the current optimal parameter combination specifically include:

[0024] Initialize the parameters of the NOA algorithm, including the starfinch population, the number of iterations t, the upper bound of the search space, and the lower bound of the search space;

[0025] The output voltage and output current of the dual-diode photovoltaic cell are input into the NOA algorithm, and the fitness values ​​of all star finches are determined through the objective function of the dual-diode photovoltaic cell;

[0026] Determine the current optimal solution according to the fitness value, and use the search mechanism of the NOA algorithm to perform iterative search;

[0027] During the search, each starfinch explored the area around the cache using two reference points;

[0028] Updating the position of the starfinch, and determining the optimal solution according to the fitness value;

[0029] It is determined whether the NOA algorithm converges, and if so, the optimal dual-diode photovoltaic cell parameters are output.

[0030] In the above scheme, after determining whether the NOA algorithm has converged, the method further includes:

[0031] If the NOA algorithm does not converge, reinitialize the parameters of the NOA algorithm, including the starfinch population, the number of iterations t, the upper bound of the search space, and the lower bound of the search space;

[0032] The output voltage and output current of the dual-diode photovoltaic cell are used as inputs of the NOA algorithm, and the fitness values ​​of all star finches are determined through the objective function of the dual-diode photovoltaic cell;

[0033] Determine the current optimal solution according to the fitness value, and use the search mechanism of the NOA algorithm to perform iterative search;

[0034] During the search, each starfinch explored the area around the cache using two reference points;

[0035] Update the position of the starfinch and determine the optimal solution based on the fitness value;

[0036] It is determined whether the NOA algorithm converges, and if so, the optimal dual-diode photovoltaic cell parameters are output.

[0037] In the above scheme, during the search process, each starfinch uses two reference points to explore the area around the cache, specifically including:

[0038] In the NOA algorithm, two reference points for each starfinch are determined according to the matrix:

[0039]

[0040] In the formula, and represents the cache location of the i-th starfinch in the current generation t;

[0041] Generate the first reference point by updating the current position within the adjacent region:

[0042]

[0043] When searching for hidden caches in different areas, identify a second reference point:

[0044]

[0045]

[0046] Where k represents the P index; represents the cache location of the i-th starfinch in the current generation t; represents the cache of the i-th starfinch in the current iteration t; and They represent the upper and lower bounds of a d-dimensional problem respectively; α indicates a linear decrease from 1 to 0; represents a vector containing randomly generated values ​​between 0 and 1; represents the cache position of the Ath starfinch in the current iteration t; τ1 represents a random number of the second reference point in the range [0,1]; θ represents a random number in [0,π]; P rp represents a probability that determines the percentage of other regions to explore globally in the search space.

[0047] In the above scheme, the updating of the position of the star bird and determining the optimal solution according to the fitness value specifically include:

[0048] Update the position of the starfinch:

[0049]

[0050] In the formula, It indicates the new position of the Star Finch; represents the current position of the i-th starfinch in the current iteration t; Represents the first reference point of the current position of the i-th starfinch at iteration t.

[0051] The present application also proposes a parameter identification system for photovoltaic cells, the system comprising: a model function construction unit, an identification unit, a fit value acquisition unit and a photovoltaic cell parameter judgment unit;

[0052] The model function construction unit is used to construct an equivalent circuit model and an objective function of a dual-diode photovoltaic cell;

[0053] The identification unit is used to identify the parameters of the photovoltaic cell according to the NOA algorithm and determine the current optimal parameter combination;

[0054] The fitting value acquisition unit is used to determine the output voltage and output current corresponding to the current optimal parameter combination based on the objective function, and fit the output voltage and output current with the corresponding actual measurement values ​​to determine the fitting value;

[0055] The photovoltaic cell parameter judgment unit is used to determine the optimal photovoltaic cell parameters according to the current optimal parameter combination corresponding to the NOA algorithm when the fitting value meets the threshold range and the NOA algorithm converges.

[0056] The present application also proposes a readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the following steps:

[0057] Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell;

[0058] Identify the parameters of photovoltaic cells according to the NOA algorithm and determine the current optimal parameter combination;

[0059] Based on the objective function, determining the output voltage and output current corresponding to the current optimal parameter combination, fitting the output voltage and output current with corresponding actual measured values, and determining a fitting value;

[0060] When the fitness value satisfies a threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

[0061] The present application also proposes a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the following steps of the computer program:

[0062] Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell;

[0063] Identify the parameters of photovoltaic cells according to the NOA algorithm and determine the current optimal parameter combination;

[0064] Based on the objective function, determining the output voltage and output current corresponding to the current optimal parameter combination, fitting the output voltage and output current with corresponding actual measured values, and determining a fitting value;

[0065] When the fitness value satisfies a threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

[0066] The embodiment of the present invention has the following beneficial effects: firstly, an equivalent circuit model and an objective function of a dual-diode photovoltaic cell are constructed; the parameters of the photovoltaic cell are identified according to the NOA algorithm to determine the current optimal parameter combination; based on the objective function, the output voltage and the output current corresponding to the current optimal parameter combination are determined, and the output voltage and the output current are fitted with the corresponding actual measured values ​​to determine the fitting value; when the fitting value satisfies the threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm when the NOA algorithm converges. This method simulates the behavior of star finches in search of food to achieve more directional optimization with a smaller number of iterations, thereby significantly improving the recognition speed while improving the recognition accuracy of photovoltaic cell parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] in:

[0069] Figure 1 is a schematic flow chart of a parameter identification method for a photovoltaic cell in one embodiment;

[0070] Figure 2 is a fitting diagram of a photovoltaic cell voltage-current (IV) characteristic curve identified using the NOA algorithm in one embodiment;

[0071] Figure 3 FIG. 1 is a schematic diagram of a voltage-power (PV) characteristic curve fitting diagram identified using the NOA algorithm in one embodiment. DETAILED DESCRIPTION

[0072] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0073] In the following description, a large number of specific details are given in order to provide a more thorough understanding of the present invention; however, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details; in other examples, in order to avoid confusion with the present invention, some technical features known in the art are not described, and it should be understood that the present invention can be implemented in different forms and should not be interpreted as limited to the embodiments presented here; on the contrary, providing these embodiments will make the disclosure thorough and complete and fully convey the scope of the present invention to those skilled in the art.

[0074] The purpose of the terms used herein is only to describe specific embodiments and is not intended to be limiting of the present invention. When used herein, the singular forms "a", "an" and "said / the" are also intended to include the plural forms, unless the context clearly indicates otherwise, and it should also be understood that the terms "consisting of" and / or "comprising", when used in this specification, determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0075] To facilitate understanding, the relevant terms involved in this application are first introduced below.

[0076] (1) Root mean square error (RMSE). Root mean square error (RMSE) is used as the objective function to evaluate the accuracy of PV cell model parameter identification. RMSE is a commonly used method to measure the difference between the model prediction value and the actual observation value.

[0077] (2) The Noctua Optimization Algorithm (NOA) is an optimization algorithm used to find the optimal solution in a complex search space. The algorithm simulates the behavior of noctua in searching for food caches and improves the search efficiency and effect by dynamically balancing local search and global search.

[0078] In order to thoroughly understand the present invention, a detailed structure will be presented in the following description to illustrate the technical solution proposed by the present invention; optional embodiments of the present invention are described in detail as follows, but in addition to these detailed descriptions, the present invention may also have other implementation methods.

[0079] like Figure 1 As shown, in one embodiment, a parameter identification method for a photovoltaic cell is provided, and the parameter identification method for a photovoltaic cell includes steps S101 to S104, which are described in detail as follows:

[0080] S101. Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell;

[0081] By constructing an equivalent circuit model of a dual-diode photovoltaic cell, the electrical characteristics of the photovoltaic cell can be simulated more accurately. At the same time, defining an objective function (such as the root mean square error (RMSE)) is used to evaluate the error between the simulation data and the experimental data, providing an evaluation criterion for subsequent parameter identification, which can improve the accuracy and credibility of parameter identification.

[0082] In some embodiments, constructing an equivalent circuit model and an objective function of a dual-diode photovoltaic cell specifically includes: the expression of the equivalent circuit model of the dual-diode photovoltaic cell is:

[0083]

[0084] In the formula, I L and V L Respectively represent the output current and output voltage of the photovoltaic cell; I ph Represents photocurrent; I sh and I0 represent the reverse saturation current of the two diodes respectively; R s and R sh Represent the series resistance and parallel resistance respectively; a1 and a2 represent the diode ideal factor, which is the parameter that needs to be identified; V T represents thermal voltage;

[0085] Thermal voltage V T Defined as:

[0086]

[0087] Wherein, T represents the battery temperature; K represents the Boltzmann constant, K = 1.38 × 10-23 J; q represents the electron charge, q = 1.6 × 10-19 C.

[0088] The above a1 and a2 represent the ideal factors of the diode, which are parameters that need to be identified. The main purpose of parameter identification is to find a set of appropriate parameters that can effectively reduce the errors between experimental data and simulation data. These errors can be quantitatively evaluated by the objective function. Therefore, this application selects the root mean square error (RMSE) as the objective function.

[0089] In some embodiments, an equivalent circuit model and an objective function of a dual-diode photovoltaic cell are constructed, specifically including: the expression of the objective function of the dual-diode photovoltaic cell is:

[0090]

[0091] In the formula, x represents the solution vector of the parameters to be identified, including the photocurrent I ph , the reverse saturation current of the diode I 01 ,I 02 , series resistance R s , parallel resistance R sh , diode ideal factors a1, a2; N represents the number of experimental data;

[0092] f(V L , I L , x) is expressed as:

[0093]

[0094] In the formula, I ph Represents photocurrent; I 01 ,I 02 Respectively represent the reverse saturation current of the two diodes; R s Represents the series resistance; R sh represents the parallel resistance; a1 and a2 represent the ideal factors of the two diodes respectively.

[0095] Specifically, x={I ph ,I 01 ,I 02 ,R s ,R sh , a1,a2}.

[0096] S102, identifying the parameters of the photovoltaic cell according to the NOA algorithm, and determining the current optimal parameter combination;

[0097] The core of this method is to use the Starling Optimization Algorithm (NOA) for parameter identification. The NOA algorithm has the characteristics of strong global search capability, fast optimization speed and high precision. It can effectively avoid falling into the local optimal solution, thereby quickly finding a set of optimal parameter combinations, which greatly improves the efficiency and accuracy of parameter identification.

[0098] S103, based on the objective function, determining the output voltage and output current corresponding to the current optimal parameter combination, fitting the output voltage and output current with the corresponding actual measured values, and determining a fitting value;

[0099] The simulated output voltage and current corresponding to the current optimal parameter combination are calculated through the objective function. This is a key step in verifying the effectiveness of the parameter combination and can ensure that the identified parameters can accurately reflect the actual working state of the photovoltaic cell. The simulation data is fitted with the experimental data and the fitting value (such as RMSE) is calculated to intuitively evaluate the accuracy of parameter identification.

[0100] S104 . When the fitting value meets the threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

[0101] Setting the fitting threshold and the convergence condition of the NOA algorithm can ensure that the optimal photovoltaic cell parameters are output only after achieving sufficient accuracy and stability, thereby ensuring the reliability and stability of the identification results and providing strong support for practical applications.

[0102] In some embodiments, the parameters of the photovoltaic cell are identified according to the NOA algorithm to determine the current optimal parameter combination, specifically including:

[0103] Initialize the parameters of the NOA algorithm, including the starfinch population, the number of iterations t, the upper bound of the search space, and the lower bound of the search space;

[0104] The output voltage and output current of the dual-diode photovoltaic cell are input into the NOA algorithm, and the fitness values ​​of all star finches are determined through the objective function of the dual-diode photovoltaic cell;

[0105] Determine the current optimal solution based on the fitness value, and use the search mechanism of the NOA algorithm to perform iterative search;

[0106] During the search, each starfinch explored the area around the cache using two reference points;

[0107] Update the position of the star bird and determine the optimal solution based on the fitness value;

[0108] Determine whether the NOA algorithm converges. If converged, output the optimal dual-diode photovoltaic cell parameters.

[0109] Specifically, the above iteration number t=0, by taking the historical data of output voltage and current determined by different dual-diode photovoltaic cells as the input of the NOA algorithm, converting it into the objective function through the objective function expression, and obtaining the fitness values ​​of all individuals, if t≥tmax (tmax can be determined according to artificial experience or industry standard value), NOA converges and outputs the optimal solution, that is, the parameter identification result.

[0110] In some embodiments, after determining whether the NOA algorithm has converged, the method further includes:

[0111] If the NOA algorithm does not converge, reinitialize the parameters of the NOA algorithm, including the starfinch population, the number of iterations t, the upper bound of the search space, and the lower bound of the search space;

[0112] The output voltage and output current of the dual-diode photovoltaic cell are used as the input of the NOA algorithm, and the fitness values ​​of all star finches are determined through the objective function of the dual-diode photovoltaic cell.

[0113] Determine the current optimal solution based on the fitness value, and use the search mechanism of the NOA algorithm to perform iterative search;

[0114] During the search, each starfinch explored the area around the cache using two reference points;

[0115] Update the position of the starfinch and determine the optimal solution based on the fitness value;

[0116] Determine whether the NOA algorithm converges. If converged, output the optimal dual-diode photovoltaic cell parameters.

[0117] In some embodiments, during the search process, each starfinch explores the area around the cache using two reference points, specifically including:

[0118] In the NOA algorithm, two reference points for each starfinch are determined according to the matrix:

[0119]

[0120] In the formula, and Represents the cache location of the i-th starfinch in the current generation t.

[0121] Preferably, the starfinch can recover the hidden cache with high accuracy. If the starfinch cannot find the food stored at the first reference point, it will identify it through the second reference point. If the starfinch cannot retrieve its cache a second time, it will use the third reference. The first reference point is generated by updating the current position in the adjacent area to find the hidden cache around the walnut block.

[0122] Generate the first reference point by updating the current position within the adjacent region:

[0123]

[0124] When searching for hidden caches in different areas, identify a second reference point:

[0125]

[0126]

[0127] Where k represents the P index; represents the cache location of the i-th starfinch in the current generation t; represents the cache of the ith starfinch in the current iteration t; and They represent the upper and lower bounds of a d-dimensional problem respectively; α indicates a linear decrease from 1 to 0; represents a vector containing randomly generated values ​​between 0 and 1; represents the cache position of the Ath starfinch in the current iteration t; τ1 represents a random number of the second reference point in the range [0,1]; θ represents a random number in [0,π]; P rp represents a probability that determines the percentage of other regions to explore globally in the search space.

[0128] In some embodiments, updating the position of the star bird and determining the optimal solution according to the fitness value specifically includes:

[0129] Update the position of the starfinch:

[0130]

[0131] In the formula, It indicates the new position of the Star Finch; represents the current position of the i-th starfinch in the current iteration t; Represents the first reference point of the current position of the i-th starfinch at iteration t.

[0132] like Figure 2 , 3 The following are the voltage-current (IV) characteristic curve fitting diagram and voltage-power (PV) characteristic curve fitting diagram of the photovoltaic cell identified by the NOA algorithm. It can be seen that the model curve obtained by the NOA algorithm is highly matched with the actual data. Therefore, the NOA algorithm can more accurately identify the model parameters of the photovoltaic cell.

[0133] In summary, this application first establishes a photovoltaic cell model; sets the objective function; then inputs the output voltage and current of the photovoltaic cell into NOA to calculate the fitness of the current parameters; then performs parameter identification through NOA, and continuously repeats this process until the convergence conditions are met, and finally the optimal parameter identification result can be output.

[0134] The present application also proposes a parameter identification system for photovoltaic cells, the system comprising: a model function construction unit, an identification unit, a fit value acquisition unit and a photovoltaic cell parameter judgment unit;

[0135] A model function building unit, used to build an equivalent circuit model and an objective function of a dual-diode photovoltaic cell;

[0136] An identification unit, used to identify the parameters of the photovoltaic cell according to the NOA algorithm and determine the current optimal parameter combination;

[0137] A fitting value acquisition unit is used to determine the output voltage and output current corresponding to the current optimal parameter combination based on the objective function, fit the output voltage and output current with the corresponding actual measured values, and determine the fitting value;

[0138] The photovoltaic cell parameter judgment unit is used to determine the optimal photovoltaic cell parameters according to the current optimal parameter combination corresponding to the NOA algorithm when the fitting value meets the threshold range and the NOA algorithm converges.

[0139] The present application also proposes a readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the following steps:

[0140] Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell;

[0141] Identify the parameters of photovoltaic cells according to the NOA algorithm and determine the current optimal parameter combination;

[0142] Based on the objective function, the output voltage and output current corresponding to the current optimal parameter combination are determined, and the output voltage and output current are fitted with the corresponding actual measured values ​​to determine the fitting value;

[0143] When the fitting value meets the threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

[0144] The present application also proposes a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to perform the following steps:

[0145] Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell;

[0146] Identify the parameters of photovoltaic cells according to the NOA algorithm and determine the current optimal parameter combination;

[0147] Based on the objective function, the output voltage and output current corresponding to the current optimal parameter combination are determined, and the output voltage and output current are fitted with the corresponding actual measured values ​​to determine the fitting value;

[0148] When the fitting value meets the threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

[0149] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0150] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0151] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present application. It should be pointed out that, for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. The above disclosure is only a preferred embodiment of the present invention, and of course it cannot be used to limit the scope of the rights of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope covered by the present invention.

Claims

1. A method for identifying parameters of a photovoltaic cell, characterized in that: The method comprises: Construct the equivalent circuit model and objective function of the dual-diode photovoltaic cell; Identify the parameters of photovoltaic cells according to the NOA algorithm and determine the current optimal parameter combination; Based on the objective function, determining the output voltage and output current corresponding to the current optimal parameter combination, fitting the output voltage and output current with corresponding actual measured values, and determining a fitting value; When the fitness value satisfies a threshold range and the NOA algorithm converges, the optimal photovoltaic cell parameters are determined according to the current optimal parameter combination corresponding to the NOA algorithm convergence.

2. The method for identifying parameters of photovoltaic cells according to claim 1, characterized in that: The construction of the equivalent circuit model and objective function of the dual-diode photovoltaic cell specifically includes: the expression of the equivalent circuit model of the dual-diode photovoltaic cell is: In the formula, I L and V L Respectively represent the output current and output voltage of the photovoltaic cell; I ph Represents photocurrent; I sh and I0 represent the reverse saturation current of the two diodes respectively; R s and R sh Respectively represent the series resistance and parallel resistance; a1 and a2 represent the diode ideal factor; V T represents thermal voltage; The thermal voltage V T Defined as: Where T represents the battery temperature; K represents the Boltzmann constant; and q represents the electron charge.

3. The parameter identification method for photovoltaic cells according to claim 2, characterized in that: The construction of the equivalent circuit model and objective function of the dual-diode photovoltaic cell specifically includes: the objective function of the dual-diode photovoltaic cell is expressed as: In the formula, x represents the solution vector of the parameters to be identified, including the photocurrent I ph , the reverse saturation current of the diode I 01 ,I 02 , series resistance R s , parallel resistance R sh , diode ideal factors a1, a2; N represents the number of experimental data; f(V L , I L , x) is expressed as: In the formula, I ph Represents photocurrent; I 01 ,I 02 Respectively represent the reverse saturation current of the two diodes; R s Represents the series resistance; R sh represents the parallel resistance; a1 and a2 represent the ideal factors of the two diodes respectively.

4. The method for identifying parameters of photovoltaic cells according to claim 3, characterized in that: The method of identifying the parameters of the photovoltaic cell according to the NOA algorithm and determining the current optimal parameter combination specifically includes: Initialize the parameters of the NOA algorithm, including the starfinch population, the number of iterations t, the upper bound of the search space, and the lower bound of the search space; The output voltage and output current of the dual-diode photovoltaic cell are input into the NOA algorithm, and the fitness values ​​of all star finches are determined through the objective function of the dual-diode photovoltaic cell; Determine the current optimal solution according to the fitness value, and use the search mechanism of the NOA algorithm to perform iterative search; During the search, each starfinch explored the area around the cache using two reference points; Updating the position of the starfinch, and determining the optimal solution according to the fitness value; It is determined whether the NOA algorithm converges, and if so, the optimal dual-diode photovoltaic cell parameters are output.

5. The parameter identification method for photovoltaic cells according to claim 4, characterized in that: After determining whether the NOA algorithm has converged, the method further comprises: If the NOA algorithm does not converge, reinitialize the parameters of the NOA algorithm, including the starfinch population, the number of iterations t, the upper bound of the search space, and the lower bound of the search space; The output voltage and output current of the dual-diode photovoltaic cell are used as inputs of the NOA algorithm, and the fitness values ​​of all star finches are determined through the objective function of the dual-diode photovoltaic cell; Determine the current optimal solution according to the fitness value, and use the search mechanism of the NOA algorithm to perform iterative search; During the search, each starfinch explored the area around the cache using two reference points; Update the position of the starfinch and determine the optimal solution based on the fitness value; It is determined whether the NOA algorithm converges, and if so, the optimal dual-diode photovoltaic cell parameters are output.

6. The method for identifying parameters of photovoltaic cells according to claim 5, characterized in that: During the search process, each starfinch uses two reference points to explore the area around the cache, specifically including: In the NOA algorithm, two reference points for each starfinch are determined according to the matrix: In the formula, and represents the cache location of the i-th starfinch in the current generation t; Generate the first reference point by updating the current position within the adjacent region: When searching for hidden caches in different areas, identify a second reference point: Where k represents the P index; represents the cache location of the i-th starfinch in the current generation t; represents the cache of the ith starfinch in the current iteration t; and They represent the upper and lower bounds of a d-dimensional problem respectively; α indicates a linear decrease from 1 to 0; represents a vector containing randomly generated values ​​between 0 and 1; represents the cache position of the Ath starfinch in the current iteration t; τ1 represents a random number of the second reference point in the range [0,1]; θ represents a random number in [0,π]; P rp represents a probability that determines the percentage of other regions to explore globally in the search space.

7. The method for identifying parameters of photovoltaic cells according to claim 6, characterized in that: The updating of the position of the star bird and determining the optimal solution according to the fitness value specifically include: Update the position of the starfinch: In the formula, It indicates the new position of the Star Finch; represents the current position of the i-th starfinch in the current iteration t; Represents the first reference point of the current position of the i-th starfinch at iteration t.

8. A parameter identification system for photovoltaic cells, characterized in that: The system comprises: a model function construction unit, an identification unit, a fitting value acquisition unit and a photovoltaic cell parameter judgment unit; The model function construction unit is used to construct an equivalent circuit model and an objective function of a dual-diode photovoltaic cell; The identification unit is used to identify the parameters of the photovoltaic cell according to the NOA algorithm and determine the current optimal parameter combination; The fitting value acquisition unit is used to determine the output voltage and output current corresponding to the current optimal parameter combination based on the objective function, and fit the output voltage and output current with the corresponding actual measurement values ​​to determine the fitting value; The photovoltaic cell parameter judgment unit is used to determine the optimal photovoltaic cell parameters according to the current optimal parameter combination corresponding to the NOA algorithm when the fitting value meets the threshold range and the NOA algorithm converges.

9. A readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to execute the steps of the method according to any one of claims 1 to 7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 7.

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