A simulation generation system and method for IV curve simulation modeling

Abstract

The application discloses a simulation generation system and method for IV curve simulation simulation, and belongs to the field of solar photovoltaic detection. The system comprises an IV curve simulation simulation platform and an IV curve simulation generation system deployed thereon. The simulation generation system inversely deduces the benchmark value of the core physical parameter based on the working condition characteristic data of the photovoltaic module in the standard defect-free state through a parameter self-calibration engine. A defect simulation module adopts a specific parameter perturbation strategy to perturb the benchmark value according to a preset defect type, and solves the equivalent circuit equation of the photovoltaic cell after perturbation by a curve generation engine, so as to generate the IV curve corresponding to the defect type. The application can simulate 10 types of standard defects including large steps, small steps, low voltage, low current, round knees, abnormal slope, local shading and semiconductor level defects, realizes more detailed, higher precision and more category IV curve simulation, and effectively solves the problem that fault defect samples are difficult to obtain.

Description

Technical Field

[0001] This invention belongs to the field of solar photovoltaic detection, specifically relating to a simulation generation system and method for IV curve simulation. Background Technology

[0002] During operation, photovoltaic (PV) arrays are susceptible to a series of typical faults due to external environmental factors, such as rounded knees, stepped edges, low current, PID degradation, open circuits, and short circuits. Failure to detect and eliminate these faults promptly will affect the PV array's conversion efficiency and even compromise the safe and stable operation of the entire PV power generation system.

[0003] Currently, the monitoring and analysis of photovoltaic modules mainly relies on IV curve analysis technology. However, current IV curve diagnostic technology is highly dependent on the inverter's scanning of string voltage and current, and is usually provided by the inverter manufacturer. In practical applications, fault and defect samples are often difficult to obtain, which severely limits the development and application of IV curve diagnostic technology.

[0004] Therefore, given the difficulty in obtaining IV curve fault sample data, there is an urgent need to use simulation technology to generate IV curve sample data for any defect type. However, current technology has not yet achieved more detailed, higher-precision, and more diverse IV curve simulations. Summary of the Invention

[0005] This invention overcomes the shortcomings of the prior art and provides a simulation generation system and method for IV curve simulation, which can achieve more detailed, higher precision and more types of IV curve simulation and generation.

[0006] The technical solution adopted in this invention is: A simulation generation system for IV curve simulation includes: IV curve simulation platform, used to provide a computing environment; The IV curve simulation generation system is deployed on the IV curve simulation platform and is used to simulate and generate IV curves for various defect types. The IV curve simulation generation system includes: The parameter self-calibration engine is used to receive the key operating condition feature data point set of photovoltaic modules under standard defect-free conditions, and reverse deduce the benchmark values ​​of core physical parameters under standard operating conditions based on the equivalent circuit model of photovoltaic cells. The defect simulation module is used to perturb the baseline value of the core physical parameters according to the preset defect type, so as to obtain the perturbed physical parameters. The curve generation engine is used to solve the equivalent circuit equation of the photovoltaic cell based on the perturbated physical parameters and generate IV curves corresponding to the defect types.

[0007] The IV curve simulation generation system constructs a dual-modal simulation framework. This framework can not only generate ideal IV characteristic curves as a health state benchmark based on standard operating condition parameters, but also accurately reconstruct non-ideal IV characteristic curves representing various known defect modes within the same computational framework by systematically and directionally perturbing specific physical parameters in the model.

[0008] The simulation principle and implementation path of the IV curve simulation generation system are as follows: Its core technology is based on a parameterized equivalent circuit model that has been verified by engineering. This model abstracts the complex photoelectric conversion and charge transport processes inside the photovoltaic module into a set of mathematical relationships driven by core physical parameters (including photocurrent, diode characteristics, series resistance, and parallel resistance). The simulation engine achieves this through the following process: First, it accurately calibrates the baseline values ​​of these parameters under a standard defect-free state; then, based on failure physics analysis, it performs quantitative or correlational offset operations on specific parameters or combinations of parameters to simulate specific failure causes such as material degradation, process defects, or external stress; finally, by solving the circuit equations after parameter perturbation, it directly maps out the macroscopic IV characteristic distortion with a clear physical correspondence.

[0009] The mathematical expression for the equivalent circuit model of a photovoltaic cell is as follows:

[0010] In the above formula, Photocurrent; I d It is the reverse saturation current; n Ideal factor; R s It is a series resistor; R sh These are parallel resistors; V th I is the thermal voltage; V is the photovoltaic cell operating current; and V is the photovoltaic cell operating voltage.

[0011] The IV curve simulation generation system incorporates a self-calibration engine for equivalent circuit model parameters based on multi-constraint point data fusion. Before performing characteristic simulation, this engine executes the following automated parameter extraction process: First, the system receives a set of key operating condition characteristic data points provided by external devices (such as inverters or IV testers), including at least short-circuit points, open-circuit points, and maximum power points. Then, a closed nonlinear equation system with equivalent circuit model parameters as unknowns is constructed. This equation system is automatically generated by substituting the aforementioned characteristic point constraints into the circuit equations and adding a zero-power differential constraint at the maximum power point. Subsequently, the system employs a hybrid solution algorithm combining analytical derivation and numerical iteration to stably and efficiently solve the underdetermined equation system, thereby automatically inversely deriving the baseline values ​​of the core physical parameters under standard operating conditions.

[0012] The IV curve simulation generation system can systematically generate IV curves for a total of 10 standard defects based on a unified and scalable physical electrical model framework, including: large step, small step, low voltage, low current, round knee, increasing slope, decreasing slope, local occlusion, ideal factor anomaly and reverse saturation current anomaly.

[0013] Secondly, the present invention also provides a simulation generation method for IV curve simulation, specifically including: S1: Receive the set of key operating condition feature data points of photovoltaic modules under standard defect-free conditions; S2: Based on the equivalent circuit model of photovoltaic cells, the baseline values ​​of core physical parameters under standard operating conditions are derived in reverse. S3: Obtain the preset defect type and its corresponding parameter perturbation strategy; S4: According to the parameter perturbation strategy, the baseline value of the core physical parameter is perturbed to obtain the perturbed physical parameter; S5: Based on the physical parameters after the disturbance, solve the equivalent circuit equation of the photovoltaic cell and generate the IV curve corresponding to the defect type.

[0014] The parameter perturbation strategy includes: When simulating the "low current" defect, a global photoelectric conversion efficiency scaling transformation method is used to linearly scale the entire IV curve family in the current axis direction; When simulating the "low voltage" defect, a system topology reduction method is used to reduce the maximum output voltage of the system by reducing the number of effective series components; When simulating the "partial shading" defect, a subconducting threshold current mismatch network is established, and the voltage solution range is extended to cover the reverse bias operating region of the component.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1) The main influencing parameters and physical mechanisms of various defect types were identified, and a suitable mathematical algorithm model was established for each defect type, which greatly improved the accuracy and reliability of the simulation. 2) It can simulate 10 types of IV defect curves, and each defect type can be simulated to obtain IV curves of three degrees of defect: mild, moderate and severe, truly realizing more categories and more detailed IV curve simulation.

[0016] 3) Equivalent circuit equations are used to replace complex original equations to simplify the simulation process. At the same time, efficient data solving and iterative calculation methods are used to continuously approximate the response voltage with the minimum error at each current point, thus achieving both high accuracy and high efficiency in the simulation. Attached Figure Description

[0017] The present invention will be described by way of example and with reference to the accompanying drawings, wherein: Figure 1 This is an architectural block diagram of the simulation generation system provided in the embodiments of this application; Figure 2 A flowchart of the simulation generation method provided in the embodiments of this application; Figure 3 This is a diagram of the equivalent circuit model of a photovoltaic cell provided in an embodiment of this application; Figure 4-13 IV curves for 10 types of defects provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0019] Example 1: This embodiment provides a simulation generation system for IV curve simulation, see below. Figure 1 ,include: The IV curve simulation platform is used to provide a high-speed simulation computing environment based on the equivalent circuit equation of photovoltaic cells. An IV curve simulation generation system is deployed on the platform to simulate and generate IV curves for 10 types of defects, each containing different degrees of defects.

[0020] The IV curve simulation generation system constructs a dual-modal simulation framework. This framework can not only generate ideal IV characteristic curves as a health state benchmark based on standard operating condition parameters, but also accurately reconstruct non-ideal IV characteristic curves representing various known defect modes within the same computational framework by systematically and directionally perturbing specific physical parameters in the model. This achieves full-coverage simulation capability from ideal reference to fault diagnosis samples.

[0021] The simulation principle and implementation path of the IV curve simulation generation system are as follows: Its core technology is based on a parameterized equivalent circuit model that has been verified by engineering. This model abstracts the complex photoelectric conversion and charge transport processes inside the photovoltaic module into a set of mathematical relationships driven by core physical parameters (including photocurrent, diode characteristics, series resistance, and parallel resistance). The simulation engine achieves this through the following process: First, it accurately calibrates the baseline values ​​of these parameters under standard defect-free conditions; then, based on failure physics analysis, it performs quantitative or correlational offset operations on specific parameters or parameter combinations to simulate specific failure causes such as material degradation, process defects, or external stress; finally, by solving the circuit equations after parameter perturbation, it directly maps macroscopic IV characteristic distortions with clear physical correspondences, such as low voltage, low current, and abnormal slope, thereby systematically generating various defect curves.

[0022] The mathematical expression for the equivalent circuit model of a photovoltaic cell is as follows:

[0023] In the above formula, Photocurrent; I d It is the reverse saturation current; n Ideal factor; R s It is a series resistor; R sh These are parallel resistors; V th I is the thermal voltage; V is the photovoltaic cell operating current; and V is the photovoltaic cell operating voltage.

[0024] The core of the IV curve simulation generation system lies in implementing a highly efficient physical reduction modeling strategy for engineering applications. (See also...) Figure 3This strategy replaces the original microscopic models involving complex semiconductor physics processes with well-validated single-diode or dual-diode equivalent circuit models. This method accurately abstracts and preserves the core physical mechanisms determining macroscopic IV characteristics, such as photocurrent sources, diode PN junction characteristics, and series-parallel parasitic losses, while reasonably removing microscopic details irrelevant to system-level simulation. The resulting model simplification, while ensuring the fidelity of key electrical characteristic simulations, reduces computational complexity by several orders of magnitude, enabling large-scale array simulations and rapid iterative analysis, significantly improving computational efficiency and practicality.

[0025] The IV curve simulation generation system incorporates an equivalent circuit model parameter self-calibration engine based on multi-constraint point data fusion, a curve generation engine, and a defective simulation module.

[0026] The parameter self-calibration engine is used to receive the key operating condition feature data point set of photovoltaic modules under standard defect-free conditions, and reverse deduce the benchmark values ​​of core physical parameters under standard operating conditions based on the equivalent circuit model of photovoltaic cells. The defect simulation module is used to perturb the baseline value of the core physical parameters according to the preset defect type, so as to obtain the perturbed physical parameters. The curve generation engine is used to solve the equivalent circuit equation of the photovoltaic cell based on the perturbated physical parameters and generate IV curves corresponding to the defect types.

[0027] In a specific implementation, before performing characteristic simulation, the parameter self-calibration engine executes the following automated parameter extraction process: First, the system receives a set of key operating condition characteristic data points provided by external devices (such as inverters or IV testers), including at least short-circuit points, open-circuit points, and maximum power points. Then, a closed nonlinear equation set with the equivalent circuit model parameters as unknowns is constructed. This equation set is automatically generated by substituting the aforementioned characteristic point constraints into the circuit equations and adding a zero-power differential constraint at the maximum power point. Subsequently, the curve generation engine uses a hybrid solution algorithm combining analytical derivation and numerical iteration (e.g., introducing initial empirical values ​​of ideal factors to reduce solution uncertainty) to stably and efficiently solve the underdetermined equation set. This automatically derives the baseline values ​​of core physical parameters such as photocurrent, diode saturation current, series resistance, and parallel resistance under standard operating conditions, laying an accurate model foundation for all subsequent defect simulations.

[0028] See Figure 4-13 The defect simulation module can simulate and generate IV curves for at least 10 types of defects, including: large step, small step, low voltage, low current, rounded knee, increased slope, decreased slope, local occlusion, ideal factor anomaly and reverse saturation current anomaly.

[0029] Furthermore, by introducing a continuously adjustable defect severity control factor, the system achieves continuous and gradient simulation of each type of defect from mild to severe states, thereby constructing a standardized IV curve spectrum library that can be used for quantitative defect diagnosis and pattern recognition algorithm training.

[0030] The defect simulation module employs one or more of the following parameter perturbation strategies for different types of defects: To address the "large step" defect, a graded current mismatch and diode cluster conduction model is employed for simulation. This method constructs a discretized strong mismatch current distribution vector, applying a stepped, significantly different setting to the photocurrent generated by photovoltaic modules at different locations within the string. Furthermore, based on the cluster diode collaborative conduction criterion, it simulates the state where multiple bypass diodes are simultaneously activated under strong current mismatch. By establishing piecewise linearized system node equations, a nonlinear equation solver suitable for non-smooth systems is used in a global scan from open-circuit current to maximum short-circuit current to iteratively search for the equilibrium operating point satisfying all piecewise circuit constraints in the voltage domain. This allows for a high-fidelity reconstruction of the "large step" characteristic IV curve with a significant current plateau.

[0031] To address the "small-step" defect, a high-density micro-mismatch perturbation simulation algorithm is implemented. This method generates a continuously and gradually varying irradiance distribution profile and applies high-density, small-amplitude short-circuit current perturbations to a large number of photovoltaic cells in the string. The number of mismatched cells and the gradient continuity far exceed those of the large-step type. A distributed diode state-parallel computation model is used to analyze the complex local conduction network caused by micro-mismatch. During the solution process, an adaptive step-size prediction-correction method is employed to perform high-precision numerical tracking of the quasi-continuous IV trajectory composed of dense micro-steps in the IV plane, thereby accurately simulating the "small-step" IV curve characterizing slight uneven aging or shading.

[0032] To address the "partial shading" defect, a method for extending the reverse bias operating region is proposed. This method first establishes a sub-conduction threshold current mismatch network to simulate the internal current imbalance caused by partial shading, which fails to meet the bypass diode conduction condition. The core of this method lies in defining an extended voltage solution interval, whose negative boundary is analytically determined by the number of components in series and the reverse blocking characteristics of the diodes, ensuring complete coverage of the reverse bias operating region that the components may withstand. A dual-iteration framework based on the trust region algorithm is employed to ensure convergence robustness in the strongly nonlinear reverse bias region. Through a global residual minimization strategy, the system IV characteristics are accurately solved, reproducing the "partial shading" defect curve.

[0033] To address the "low current" deficiency, a global photoelectric conversion efficiency scaling method is employed for simulation. This method downgrades the universality of the component short-circuit current, characterizing it as a uniform irradiance attenuation coefficient acting on the system model. Through the calibration and mapping of the system-level performance attenuation factor, linear scaling of the entire IV curve family along the current axis is achieved. During the solution process, a parametric continuity method is used to stably and continuously evolve from the initial solution under standard operating conditions to the low-current curve solution under the target parameters, avoiding the sensitivity problem of iterative initial values ​​and efficiently generating "low current" IV curves that characterize global irradiance insufficiency.

[0034] To address the "low voltage" defect, a system topology reduction and electrical parameter remapping method is employed. This method dynamically updates the electrical topology connections of the strings, reducing the number of effective series components and thus lowering the system's maximum output voltage potential. Subsequently, port characteristics are renormalized for the equivalent circuit composed of the remaining components. Based on a recursive equivalent circuit synthesis algorithm, the external characteristic equations of the system under the new topology are quickly solved, accurately simulating the "low voltage" IV curve caused by component failure, open circuit, or connection faults.

[0035] To address the "rounded knee" defect, a collaborative degradation model for key operating point parameters is proposed. This method modifies the two core parameters, maximum power point current and voltage, by linking them together, and introduces a fill factor degradation factor to quantitatively control their nonlinear influence on the rounded shape of the curve's "knee". A constrained optimization algorithm is employed to search the model parameter space for parameter combinations that accurately match the target fill factor and maximum power point, thereby simulating the "rounded knee" IV curve caused by the degradation of the cell's intrinsic performance (such as PID and LeTID).

[0036] To address the "increased slope" defect, a parallel leakage conductance enhancement model is employed. This method explicitly reduces the parallel resistance in the equivalent circuit of the photovoltaic module, systematically increasing its parallel leakage conductance in the circuit model to simulate the aggravation of the internal leakage current path. Mathematically, this is equivalent to introducing an additional shunt term proportional to the terminal voltage into the module's output characteristics. Using a modified nodal admittance matrix method, the new linearized network equations are solved directly and efficiently, reproducing the defect morphology of a significantly increased slope of the curve near the open-circuit voltage caused by moisture intrusion, insulation aging, etc.

[0037] To address the "reduced slope" defect, a series loss impedance embedding model is employed. This method increases the series resistance of the photovoltaic module, embedding additional ohmic loss components in the current transmission path. The process uses a hierarchical equivalent impedance network algorithm to calculate the cumulative voltage division effect of the additional impedance on each voltage level. An improved Newton-Raphson method considering series losses is used for the solution, effectively simulating the IV characteristic of an overall "reduced slope" (i.e., reduced fill factor) caused by solder ribbon aging, interconnect corrosion, or loose contacts.

[0038] To address the "ideal factor anomaly" defect, a carrier recombination correction method based on the reconstruction of non-ideal diode characteristics is proposed. This method increases the diode's ideal factor, essentially correcting the weight of the recombination current term in the double-exponential diode model to reflect the enhancement of non-ideal mechanisms such as space charge recombination. This is achieved by reconstructing the diode's current-voltage characteristic function. A device-circuit joint simulation iterative strategy is employed to accurately simulate the abnormal IV characteristics, where the curve collapses near the maximum power point due to increased lattice defects and recombination centers.

[0039] To address the "abnormal reverse saturation current" defect, a diode junction characteristic degradation model is employed. This method simulates the deviation in ideal characteristics caused by the degradation of the PN junction quality by increasing the reverse saturation current of the bypass diode. This is manifested in the model as an increase in the calibrated value of the diode's reverse saturation current parameter. By establishing a hybrid system equation that includes the degraded diode model and employing sparse matrix techniques and a nonlinear solver for efficient numerical solution, the IV curve characteristics of increased leakage current under reverse bias due to diode defects or degradation are accurately reproduced.

[0040] The system also includes a multiphysics coupling module for: A mapping relationship is established between the internal temperature distribution field of the component and the series resistance and diode ideality factor in the equivalent circuit model. Based on the thermal simulation results under the non-uniform temperature rise scenario, the circuit parameters are dynamically corrected. The temperature-dependent correction values ​​of the obtained series resistance and diode ideality factor are used to drive the simulation engine to generate or enhance the simulation of "small steps" and "slope anomalies" type IV defect curves caused by non-uniform temperature.

[0041] By using humidity diffusion simulation and dielectric aging equations, the lower limit of the internal insulation resistance of the component is predicted and mapped to the parallel resistance degradation parameter in the equivalent circuit. The obtained humidity-dependent degradation parameter of the parallel resistance is used to drive the simulation engine to simulate the "increased slope" type IV defect curve caused by moisture intrusion, characterized by a decrease in parallel resistance.

[0042] The defect simulation module is also used to generate IV curves for composite defects. It establishes a fault-symptom mapping matrix and employs a partitioned-coupled iterative solver to collaboratively handle parameter perturbations corresponding to multiple defects in a single simulation, generating IV curves that simultaneously possess characteristics of multiple defects. Specifically, this includes: To address the hybrid simulation of large step defects and local shading defects, a composite defect generation method based on graph theory and circuit partitioning iteration is proposed. This method first abstracts the photovoltaic string as an electrical network graph composed of nodes and edges. It identifies and isolates sub-graph units subject to local shading and implants controlled current sources at their adjacent boundaries to simulate mismatch. Simultaneously, a discretized large step current perturbation vector is introduced at the string level. The system employs a partitioned-coupled iterative solver, first independently solving the local IV relationship of each defect sub-region, and then coordinating convergence through node voltage continuity conditions and global power balance constraints. This allows for the high-fidelity generation of composite defect IV curves exhibiting both "large step" and "local shading (diode not conducting)" characteristics in a single simulation.

[0043] To address the defects associated with the three types of shadow occlusion—large steps, small steps, and local occlusion—a unified simulation framework based on spatial occlusion spectrum analysis and multi-scale current mismatch synthesis is proposed. This framework first decomposes any two-dimensional occlusion pattern into different spatial frequency components using discrete cosine transform, mapping them to string-level large steps (low-frequency components) and unit-level small steps / local occlusion (high-frequency components) current mismatch modes, respectively. The system employs a frequency division-synthesis-iteration algorithm to inject multi-scale mismatch current sources in parallel within a unified equivalent circuit model. Finally, it generates a composite IV curve simultaneously incorporating the characteristics of all three types of occlusion through global circuit solving, achieving efficient and high-fidelity simulation of complex non-uniform occlusion scenes.

[0044] To address the dynamic coupling simulation of the aforementioned defects involving rounded knees and decreasing slope, a time-series parameter linkage evolution model based on degradation path simulation is proposed. This method defines a continuous performance degradation path from early "decreasing slope" (increasing series resistance) to late "rounded knee" (degradation of fill factor). By introducing a degradation driving factor associated with the equivalent runtime, the series resistance, diode ideality factor, and photocurrent parameters are dynamically and correlatedly adjusted. The simulation engine employs a parametric extension method to continuously solve the circuit equations along this degradation path, generating a series of IV curve sequences reflecting the defect coupling evolution process, thereby reproducing the dynamic changes in IV morphology caused by the intertwining of multiple defect mechanisms during actual aging.

[0045] To address the combined simulation of low voltage and low current defects, the system proposes a hybrid modeling method combining multiple fault root cause tracing and symptom separation. This method can distinguish and simulate three different combinations of physical root causes leading to the symptoms of "low voltage" and "low current": 1) pure low voltage caused by component failure (topology change); 2) pure low current caused by a decrease in global irradiance; and 3) mixed symptoms caused by partial component failure and performance degradation of the remaining components. The system establishes a fault-symptom mapping matrix and employs a two-layer optimization framework to automatically adjust topology connectivity and performance degradation factors, generating a family of IV curves with the same macroscopic symptoms (low voltage, low current) but different physical mechanisms and internal states. This family supports refined fault diagnosis algorithm training.

[0046] To address semiconductor-level defects such as ideality factor anomalies and reverse saturation current anomalies, a cross-scale simulation method based on microscopic physical parameter inversion and macroscopic circuit parameter mapping is proposed. This method first establishes an analytical mapping relationship from semiconductor process parameters (such as minority carrier lifetime and doping concentration) to diode macroscopic SPICE parameters (ideality factor n, reverse saturation current I0). Users can specify or randomly generate microscopic defect parameters, and the system automatically calculates the corresponding macroscopic circuit parameter changes and substitutes them into the equivalent circuit model for simulation. This method enables simulations not only to generate macroscopic IV curves but also to trace and correlate them to specific material or process degradation root causes, achieving end-to-end simulation from process defects to electrical characteristics.

[0047] To address the continuously adjustable simulation of the aforementioned slope increase and decrease defects, the system proposes a dynamic ohmic-leakage composite model based on dual-parameter collaborative modulation. This method simulates the collaborative evolution of ohmic loss and leakage current paths during actual aging by simultaneously adjusting the series and parallel resistances and introducing an empirical correlation function between them. The system employs a gradient-guided parameter scanning algorithm, automatically searching along a preset trajectory in the two-dimensional parameter space to generate a family of IV curves that smoothly transition from "slope decrease" to "slope increase," achieving continuous and controllable simulation of slope changes near the fill factor and open-circuit voltage.

[0048] To address the coupling between low current and rounded knee defects, the system proposes a coupled simulation model of photo-induced attenuation and potential-induced degradation. This method simultaneously introduces the light intensity attenuation coefficient and the system voltage stress factor to modulate the photogenerated current and diode ideality factor, respectively, simulating the IV characteristics under the combined effects of insufficient illumination and potential-induced attenuation in actual operation. By establishing a response surface model with dual driving factors, the system allows users to set environmental and electrical stress ratios and automatically generates a series of "low current-rounded knee" hybrid IV curves characterizing the combined attenuation mechanism.

[0049] To simulate the combined defects of small steps and low current, a hybrid generation method combining random field superposition and a global attenuation factor is proposed. This method first generates a high-density, small-amplitude spatial irradiance perturbation distribution based on a Gaussian random field to simulate the complex non-uniform shading required for the "small step" defect. Simultaneously, a global attenuation coefficient is introduced to uniformly reduce the photocurrent of all battery cells, simulating the overall insufficient irradiance represented by the "low current" defect. The system employs a spectral random method combined with a deterministic attenuation solution strategy, decomposing the random perturbation field into a series of characteristic modes and injecting them into the corresponding nodes of the circuit model. Then, global current scaling is applied, and by solving a global nonlinear equation system, an IV curve is generated that simultaneously exhibits dense small steps and a decrease in overall current amplitude, reproducing the complex illumination scene of intertwined local clouds and global overcast skies.

[0050] To address the combined simulation of three high-impact defects—large step, low voltage, and reduced slope—a hierarchical fault injection and system-level characteristic co-solution method is proposed. This method simulates a photovoltaic string simultaneously exhibiting: 1) severely mismatched sub-strings ("large step"); 2) completely failed open-circuit modules ("low voltage"); and 3) contact aging in the remaining healthy modules ("reduced slope"). The system employs a hierarchical modeling strategy: the top layer updates the electrical topology to reflect the reduction in series number caused by the failed modules; the middle layer applies a discrete current source perturbation model to the mismatched sub-strings; and the bottom layer applies an increased series resistance model to the remaining healthy modules. A co-solver synchronously processes topology changes, strong current mismatch, and ohmic losses, generating a complex composite defect IV curve that comprehensively exhibits: overall voltage range compression (low voltage), a significant current plateau (large step) on the curve, and a generally reduced slope in the plateau region and subsequent curves (reduced slope), used to simulate extreme fault scenarios.

[0051] The defect simulation module introduces a "defect gene" encoding mechanism, defining a set of core defect gene parameters for each type of defect. By editing a chromosome sequence composed of multiple sets of defect gene parameters, the type, degree, and combination of various defects can be specified, and a gene-phenotype parser decodes it into a specific circuit model parameter perturbation scheme. Specifically, for all 10 types of defects, the system proposes an IV curve generation method based on "defect gene" encoding and controllable expression. This method defines a set of core "defect gene" parameters (such as current mismatch rate, resistance multiplication factor, factor offset, etc.) for each type of defect. Users or upper-level algorithms can precisely specify the type, degree, spatial location, and combination of various defects by editing a chromosome sequence composed of multiple sets of "gene" encodings. The system is equipped with a gene-phenotype parser that decodes the chromosome sequence into a specific circuit model parameter perturbation scheme and drives the simulation engine to generate a strictly corresponding IV curve, realizing the programmed and batch generation of arbitrarily complex and customized defect morphologies.

[0052] The photovoltaic cell equivalent circuit model is a single-diode or dual-diode equivalent circuit model that has been verified in engineering.

[0053] Example 2: This embodiment provides a simulation generation method for IV curve simulation, applied to the simulation generation system described in Embodiment 1, see reference. Figure 2 The method includes the following steps: S1: Receive a set of key operating condition characteristic data points of photovoltaic modules under standard defect-free conditions provided by external equipment (such as inverters or IV testers). The set of key operating condition characteristic data points includes at least short-circuit points, open-circuit points, and maximum power points. S2: Based on the engineering-verified equivalent circuit model of a single-diode or dual-diode photovoltaic cell, a closed nonlinear equation system with core physical parameters as unknowns is constructed. A hybrid solution algorithm combining analytical derivation and numerical iteration is adopted to reverse derive the baseline values ​​of photogenerated current, diode reverse saturation current, series resistance, parallel resistance and diode ideality factor under standard operating conditions. S3: Obtain the preset defect types and their corresponding parameter perturbation strategies. Defect types include large steps, small steps, low voltage, low current, round knee, increased slope, decreased slope, local occlusion, ideal factor anomaly, and reverse saturation current anomaly. It supports simulation of single defects and composite defects. S4: According to the parameter perturbation strategy, the baseline values ​​of the core physical parameters are perturbed in a directional and quantitative manner to obtain perturbed physical parameters adapted to the defect type; S5: Based on the physical parameters after the disturbance, solve the equivalent circuit equation of the photovoltaic cell, use an efficient iterative calculation method to approximate the minimum error response voltage, and generate an IV curve corresponding to the defect type and with continuously adjustable defect degree.

[0054] In step S3, the parameter perturbation strategy includes: When simulating the "low current" defect, a global photoelectric conversion efficiency scaling transformation method is used to linearly scale the entire IV curve family in the current axis direction; When simulating the "low voltage" defect, a system topology reduction method is used to reduce the maximum output voltage of the system by reducing the number of effective series components; When simulating the "partial shading" defect, a subconducting threshold current mismatch network is established, and the voltage solution range is extended to cover the reverse bias operating region of the component. When simulating the "large step" defect, a discretized strong mismatch current distribution vector is constructed, and a step-like differential setting is applied to the photocurrent of the components in the string. When simulating the "small step" defect, a high-density micro-mismatch irradiance profile is generated, and a small-amplitude short-circuit current disturbance is applied. When simulating the "increased slope" defect, reduce the parallel resistance of the equivalent circuit; When simulating the "decreasing slope" defect, increase the series resistance of the equivalent circuit; When simulating the "round knee" defect, the maximum power point parameter is corrected in conjunction with the fill factor and degradation factor. When simulating the "ideal factor anomaly" defect, the diode's ideal factor is adjusted to reconstruct its characteristics; When simulating the "reverse saturation current anomaly" defect, increase the reverse saturation current parameter of the diode.

[0055] Example 3: This embodiment provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the simulation generation method for IV curve simulation as described in Embodiment 2, specifically: When the processor executes the computer program, it receives a set of key operating condition feature data points under the standard defect-free state of the photovoltaic module, reverse deduces the benchmark value of the core physical parameters based on the equivalent circuit model of the photovoltaic cell, obtains the preset defect type and corresponding parameter perturbation strategy, perturbs the benchmark value of the core physical parameters to obtain the perturbated parameters, and solves the equivalent circuit equation to generate the IV curve of the corresponding defect type. The computer-readable storage medium can store program data required for the simulation system to run, such as defect gene coding library, fault-symptom mapping matrix, multi-physics field coupling parameter mapping relationship, and equivalent circuit model solving algorithm. It supports the simulation system to generate IV curves of 10 types of single defects and multiple composite defects in batches, as well as gradient and continuous simulation output of defect degree.

[0056] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A simulation generation system for IV curve simulation, characterized in that, include: IV curve simulation platform, used to provide a computing environment; The IV curve simulation generation system is deployed on the IV curve simulation platform and is used to simulate and generate IV curves for various defect types. The IV curve simulation generation system includes: The parameter self-calibration engine is used to receive the key operating condition feature data point set of photovoltaic modules under standard defect-free conditions, and reverse deduce the benchmark values ​​of core physical parameters under standard operating conditions based on the equivalent circuit model of photovoltaic cells. The defect simulation module is used to perturb the baseline value of the core physical parameters according to the preset defect type, so as to obtain the perturbed physical parameters. The curve generation engine is used to solve the equivalent circuit equation of the photovoltaic cell based on the perturbated physical parameters and generate IV curves corresponding to the defect types.

2. The simulation generation system according to claim 1, characterized in that, The key operating condition characteristic data point set includes at least short-circuit point, open-circuit point, and maximum power point; the core physical parameters include photocurrent, diode reverse saturation current, series resistance, parallel resistance, and diode ideality factor.

3. The simulation generation system according to claim 1, characterized in that, The defect simulation module can simulate and generate IV curves for at least 10 types of defects, including: large step, small step, low voltage, low current, rounded knee, increased slope, decreased slope, local occlusion, ideal factor anomaly, and reverse saturation current anomaly.

4. The simulation generation system according to claim 3, characterized in that, The defect simulation module employs one or more of the following parameter perturbation strategies for different types of defects: To address the "large step" defect, a discrete strong mismatch current distribution vector is constructed to apply a stepped difference setting to the photocurrent of photovoltaic modules at different locations within the string. To address the "increased slope" defect, the parallel resistance in the equivalent circuit model is reduced to simulate it. To address the "decreased slope" defect, the series resistance in the equivalent circuit model is increased to simulate it. To address the "round knee" defect, the maximum power point current and voltage are corrected by linkage, and a fill factor and degradation factor are introduced for simulation.

5. The simulation generation system according to claim 1, characterized in that, The system also includes a multiphysics coupling module for: Establish a mapping relationship between the internal temperature distribution field of the component and the series resistance and diode ideality factor in the equivalent circuit model. Based on the thermal simulation results under non-uniform temperature rise scenarios, dynamically correct the circuit parameters; and / or, By using humidity diffusion simulation and dielectric aging equations, the lower limit of the internal insulation resistance of the component is predicted and mapped to the parallel resistance degradation parameter in the equivalent circuit.

6. The simulation generation system according to claim 1, characterized in that, The defect simulation module is also used to generate IV curves for composite defects. It establishes a fault-symptom mapping matrix and uses a partitioned-coupled iterative solver to collaboratively process parameter perturbations corresponding to multiple defects in a single simulation, thereby generating IV curves that simultaneously possess multiple defect characteristics.

7. The simulation generation system according to claim 1, characterized in that, The defect simulation module introduces a "defect gene" encoding mechanism, which defines a set of core defect gene parameters for each type of defect. By editing the chromosome sequence composed of multiple sets of defect gene parameters, the type, degree and combination of various defects can be specified, and the gene-phenotype parser decodes them into specific circuit model parameter perturbation schemes.

8. The simulation generation system according to claim 1, characterized in that, The photovoltaic cell equivalent circuit model is a single-diode or dual-diode equivalent circuit model that has been verified in engineering.

9. A simulation generation method for IV curve simulation, characterized in that, Applied to the simulation generation system as described in any one of claims 1-8, the method includes the following steps: S1: Receive the set of key operating condition feature data points of photovoltaic modules under standard defect-free conditions; S2: Based on the equivalent circuit model of photovoltaic cells, the baseline values ​​of core physical parameters under standard operating conditions are derived in reverse. S3: Obtain the preset defect type and its corresponding parameter perturbation strategy; S4: According to the parameter perturbation strategy, the baseline value of the core physical parameter is perturbed to obtain the perturbed physical parameter; S5: Based on the physical parameters after the disturbance, solve the equivalent circuit equation of the photovoltaic cell and generate the IV curve corresponding to the defect type.

10. The simulation generation method according to claim 9, characterized in that, In step S3, the parameter perturbation strategy includes: When simulating the "low current" defect, a global photoelectric conversion efficiency scaling method is used to linearly scale the entire IV curve family in the current axis direction. When simulating the "low voltage" defect, a system topology reduction method is used to reduce the maximum output voltage of the system by reducing the number of effective series components; When simulating the "partial shading" defect, a subconducting threshold current mismatch network is established, and the voltage solution range is extended to cover the reverse bias operating region of the component.

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