- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Boosted mutation-based Harris hawks optimizer for parameters identification of single-diode solar cell models
摘要： In order to realize the performance of the PV model before being installed, it is often indispensable to develop reliable and accurate parameter identification methods for dealing with the PV models. Up to now, several stochastic methods have been proposed to analyze the feature space of this problem. However, some of the stochastic-based methods may present unsatisfactory results due to their insufficient exploration and exploitation inclinations, and the multimodal and nonlinearity existed in PV parameters extraction problems. In this paper, a Boosted Harris Hawk’s Optimization (BHHO) technique is proposed to achieve a more stable model and effectively estimate the parameters of the single diode PV model. The BHHO method combines random exploratory steps of evolution inspired by the flower pollination algorithm (FPA) and a powerful mutation scheme of the differential evolution (DE) with 2-Opt algorithms. The proposed strategies not only help BHHO algorithm to accelerate the convergence rate but also assist it in scanning new regions of the search basins. The results demonstrate that the proposed BHHO is more accurate and reliable compared to the basic version and several well-established methods. The BHHO method was rigorously validated by using real experimental data under seven sunlight and temperature conditions. Furthermore, the statistical criteria indicate that the proposed BHHO method has lower errors among other peers, which is highly useful for real-world applications.
关键词： I–V characteristics,Photovoltaic module,Harris hawks optimization,Parameter extraction,Single-diode model
更新于2025-09-19 17:13:59
-
Analysis of moisture-induced degradation of thin-film photovoltaic module
摘要： To enhance the reliability of the thin-film solar cell technologies, it is required to analyze and understand the moisture-induced degradation. In this study, the moisture induced degradation of glass-to-glass CIGS module are comprehensively analyzed. CIGS modules are fabricated and tested under damp-heat conditions with periodical measurement of the electrical characteristics. Individual layers of the module are also investigated experimentally and the moisture induced degradation is discussed. A modified method to extract the diode model parameters from degraded I–V curves is proposed and applied to the degraded data. Finally, the degradation rates are modelled and the effect of model parameters degradation on the power of module are quantitatively compared. It suggests that the power degradation of CIGS module under the damp-heat environment is more affected by the enhanced recombination of the absorber layer than the degradation of the metal layer or the leakage over layers.
关键词： Reliability,Diode model parameter extraction,Moisture-induced degradation,Thin-film photovoltaics,CIGS
更新于2025-09-19 17:13:59
-
Coyote optimization algorithm for the parameter extraction of photovoltaic cells
摘要： In this paper, a new and powerful metaheuristic optimization technique known as the Coyote Optimization Algorithm (COA) is proposed for the parameter extraction of the PV cell/module. It is utilized to identify the parameters of the single diode and two-diode models. Inspired by the social norms adopted by the coyotes to ensure the survivability of their species, the COA possesses several outstanding merits such as low number of control parameters, ease of implementation and diverse mechanisms for balancing exploration and exploitation. For physically meaningful solutions, a set of parametric constraints is introduced to prevent the coyotes from straying outside of the predefined boundaries of the search space. Extensive tests indicate that the proposed optimizer exhibits superior accuracy compared to other state-of-the-art EA-based parameter extraction methods. It achieved root-mean-square error (RSME) as low as 7.7301E-04 A and 7.3265E-04 A, for the single-diode and two-diode models, respectively. Moreover, the algorithm maintains outstanding performance when tested on an assortment of modules of different technologies (i.e. mono-crystalline, poly-crystalline, and thin film) at varying irradiance and temperature. The standard deviations (STDs) of the fitness values over 35 runs are measured to be less than 1 × 10?5 for both models. This suggests that the results produced by the algorithm are highly consistent. With these outstanding merits, the COA is envisaged to be a competitive option for the parameter extraction problem of PV cell/module.
关键词： Equivalent circuit model,Solar photovoltaic,Evolutionary algorithm,Coyote optimization algorithm,Parameter extraction
更新于2025-09-16 10:30:52
-
[IEEE 2019 Innovations in Power and Advanced Computing Technologies (i-PACT) - Vellore, India (2019.3.22-2019.3.23)] 2019 Innovations in Power and Advanced Computing Technologies (i-PACT) - A Novel Optimization Method for Parameter Extraction of Industrial Solar Cells
摘要： Triple diode model is used in the present work for making a lumped parameter equivalent circuit for solar photovoltaic (PV) model. Flower pollination optimization algorithm (FPOA) is used for finding out various parameters of the solar cell. The theoretical values considering the estimation are not the same as the industrial samples of double diode model. Many current components of solar cells were not found by the two diode model correctly whereas a triple diode model can extract the data accurately. The FPOA is being used to extract different parameters of the given triple diode model. The success of the FPOA optimization process is that it performs the local and global search within the single stage to extract the parameters. Simulation is carried out and the performance of the FPOA is compared with two other optimization techniques such as differential evolution (DE) method and particle swarm optimization (PSO) method. Comparison result shows that the triple diode model including FPOA provides superior performance than the double and single diode model. Moreover, huge silicon solar cells could be explained easily by the triple diode model.
关键词： parameter extraction,diode model,solar cell,photovoltaic array,optimization algorithm
更新于2025-09-16 10:30:52
-
Evolutionary multi-task optimization for parameters extraction of photovoltaic models
摘要： As the demand for solar energy increases dramatically, the optimization and control of photovoltaic systems become increasingly important, accurate and reliable parameter identification of photovoltaic models is always required, which proposes an urgent need for accurate and robust algorithms. To this end, many heuristic algorithms have been proposed to extract the parameters of different photovoltaic models. However, they only extract the parameters of one model in a single run, which is inconsistent with the human ability to solve multiple tasks simultaneously and ignores the useful information derived from different models. Therefore, in this paper an evolutionary multi-task optimization algorithm is proposed to extract the parameters of multiple different photovoltaic models simultaneously. To be specific, the helpful information found by the population is transferred through the cross-task crossover to improve the performance in terms of solution quality and convergence rate of the population. The proposed algorithm is evaluated by extracting the parameters of three different models simultaneously, i.e., single diode, double diode, and photovoltaic module model. Comprehensive results demonstrate that the proposed algorithm has better performance with respect to the accuracy and robustness in comparison with other state-of-the-art algorithms.
关键词： Differential evolution,Parameter extraction,Evolutionary multi-task optimization,Photovoltaic models
更新于2025-09-16 10:30:52
-
A capacitor based fast I-V characteristics tester for photovoltaic arrays
摘要： In order to efficiently evaluate the operating status of photovoltaic (PV) arrays, a design of fast current-voltage (I-V) characteristic tester is proposed in this paper. The tester uses the dynamic capacitor charging method to quickly sweep I-V characteristic curves. Then, a new artificial bee colony and Nelder-Mead simplex (ABC-NMS) hybrid algorithm is used to extract parameters of the single diode model of PV arrays. The experimental results show that the tester can quickly measure high-quality I-V curves of PV array and achieve accurate model parameters extraction. In addition, the root mean square error (RMSE) of curve fitting can be used to effectively indicate the partial shading condition.
关键词： I-V characteristics testing,ABC-NMS algorithm,dynamic capacitor charging,PV arrays,parameter extraction,partial shading
更新于2025-09-12 10:27:22
-
A new approach for parameter estimation of the single-diode model for photovoltaic cells/modules
摘要： Solar energy has become a popular renewable energy source, leading to wide use of photovoltaic (PV) cells/modules in energy production. For this reason, realistic modeling of PVs and determining the equivalent circuit parameters is of great importance in terms of planning and operation. Hence, in this study, an analytical model for identifying the single-diode equivalent circuit parameters; series resistance ( Rs ), shunt resistance ( Rp ), diode ideality factor ( a ), diode reverse-saturation current ( Io ), and photon current ( Ipv ) for PV cells/modules is developed without neglecting any term. In order to test the accuracy of the model, a number of PV modules from different manufacturers are taken into account and the results are compared with those obtained by using such analytical models given in the literature. Current-voltage (I-V ) characteristics of the PV modules, which are studied here, are also simulated by comparing with the experimental I-V curves provided by the manufacturers. Results show that the values of the parameters obtained for the PV modules are consistent with those extracted by using other analytical models. In addition, I-V curves created by using the obtained parameters are in full agreement with the experimental data. The curves also show a high degree of compatibility with the ones created by using the optimal parameters of the two-diode models given in the literature. Moreover, the proposed model provides a great advantage in estimating equivalent circuit parameters in terms of ease of use, requirements for input data, dependency on initial conditions as well as considering the parameters which are neglected in such methods given in the literature.
关键词： Photovoltaic cells/modules,single-diode model,mathematical modeling,parameter extraction
更新于2025-09-12 10:27:22
-
Parameters Extraction of Photovoltaic Models Using an Improved Moth-Flame Optimization
摘要： Photovoltaic (PV) models’ parameter extraction with the tested current-voltage values is vital for the optimization, control, and evaluation of the PV systems. To reliably and accurately extract their parameters, this paper presents one improved moths-flames optimization (IMFO) method. In the IMFO, a double flames generation (DFG) strategy is proposed to generate two different types of target flames for guiding the flying of moths. Furthermore, two different update strategies are developed for updating the positions of moths. To greatly balance the exploitation and exploration, we adopt a probability to rationally select one of the two update strategies for each moth at each iteration. The proposed IMFO is used to distinguish the parameter of three test PV models including single diode model (SDM), double diode model (DDM), and PV module model (PMM). The results indicate that, compared with other well-established methods, the proposed IMFO can obtain an extremely promising performance.
关键词： moth-flame optimization,photovoltaic model,parameter extraction,double flames generation (DFG) strategy
更新于2025-09-11 14:15:04
-
Application of Supply-Demand-Based Optimization for Parameter Extraction of Solar Photovoltaic Models
摘要： Modeling solar photovoltaic (PV) systems accurately is based on optimal values of unknown model parameters of PV cells and modules. In recent years, the use of metaheuristics for parameter extraction of PV models gains more and more attentions thanks to their efficacy in solving highly nonlinear multimodal optimization problems. This work addresses a novel application of supply-demand-based optimization (SDO) to extract accurate and reliable parameters for PV models. SDO is a very young and efficient metaheuristic inspired by the supply and demand mechanism in economics. Its exploration and exploitation are balanced well by incorporating different dynamic modes of the cobweb model organically. To validate the feasibility and effectiveness of SDO, four PV models with diverse characteristics including RTC France silicon solar cell, PVM 752 GaAs thin film cell, STM6-40/36 monocrystalline module, and STP6-120/36 polycrystalline module are employed. The experimental results comparing with ten state-of-the-art algorithms demonstrate that SDO performs better or highly competitively in terms of accuracy, robustness, and convergence. In addition, the sensitivity of SDO to variation of population size is empirically investigated. The results indicate that SDO with a relatively small population size can extract accurate and reliable parameters for PV models.
关键词： parameter extraction,cobweb model,solar photovoltaic models,supply-demand-based optimization,metaheuristic
更新于2025-09-11 14:15:04
-
Modified Search Strategies Assisted Crossover Whale Optimization Algorithm with Selection Operator for Parameter Extraction of Solar Photovoltaic Models
摘要： Extracting accurate values for involved unknown parameters of solar photovoltaic (PV) models is very important for modeling PV systems. In recent years, the use of metaheuristic algorithms for this problem tends to be more popular and vibrant due to their e?cacy in solving highly nonlinear multimodal optimization problems. The whale optimization algorithm (WOA) is a relatively new and competitive metaheuristic algorithm. In this paper, an improved variant of WOA referred to as MCSWOA, is proposed to the parameter extraction of PV models. In MCSWOA, three improved components are integrated together: (i) Two modi?ed search strategies named WOA/rand/1 and WOA/current-to-best/1 inspired by di?erential evolution are designed to balance the exploration and exploitation; (ii) a crossover operator based on the above modi?ed search strategies is introduced to meet the search-oriented requirements of di?erent dimensions; and (iii) a selection operator instead of the “generate-and-go” operator used in the original WOA is employed to prevent the population quality getting worse and thus to guarantee the consistency of evolutionary direction. The proposed MCSWOA is applied to ?ve PV types. Both single diode and double diode models are used to model these ?ve PV types. The good performance of MCSWOA is veri?ed by various algorithms.
关键词： metaheuristic,solar photovoltaic,whale optimization algorithm,parameter extraction
更新于2025-09-11 14:15:04