A linear identification of diode models from single I-V characteristics of PV panels

This paper presents a novel approach on diode model parameters identification from the I-V characteristics of PV panels. Other than the prevailing methodology of solving a group of nonlinear equations from a few points on the I-V curve, the proposed one views the diode model as the equivalent output of a dynamic system. From this new viewpoint, diode model parameters are linked to the transfer function (after Laplace transform) of the same dynamic system whose parameters are then identified by a simple integral-based linear square. Indoor flash test shows the accuracy and effectiveness of the proposed method, and outdoor module testing shows its ability of online monitoring and diagnostics. Comparisons to the methods of Lambert W function and evolution algorithms are also included

Analysis of single-diode and improvement of double-diode photovoltaic source modelling methods and techniques

Modelling of photovoltaic systems is essential for designers of solar generation plants to do a yield analysis that accurately predicts the expected power output under changing environmental conditions. There are a few different models which are used and they all differ in their implementation and also on the accuracy. The main aim of this thesis is to analyse different PV modelling methods which are based on the single-diode and double-diode models. The study carried out, falls under two sections. The first study was to figure out which single-diode model produces the most accurate results. The second study is extended to double-diode models. Here, the thesis goes on to propose a different PV modelling method which is based on the double-diode representation of a PV module that will be verified and compared with other models and experimental data. An analysis of the various different single-diode models is done based on two commercially available PV modules: SQ80 and the KC200GT, in which the simulated results are compared with the characteristics extracted from the datasheets. Parameter estimation techniques within a modelling method are generally used to estimate the five unknown parameters in the single-diode model. Two sets of estimated parameters were used to plot the I-V characteristics of two PV modules, SQ80 and KC200GT, for the different sets of modelling equations which are classified into models 1 to 5 in this study. Each model is based on the different combinations of diode saturation current and photo generated current, plotted under varying irradiance and temperature. Modelling was done using Matlab/Simulink software and the results from each model were first verified for correctness against the results produced by their respective authors, then a comparison was made amongst the different models (models 1 to 5) with respect to experimentally measured and datasheet I-V curves. The SQ80 module is also connected in the lab and experimental values are measured from it under different environmental conditions. A comparison is then made using the different modelling methods with the experimental data to evaluate the accuracy of the models. In the second study, the new proposed double-diode PV modelling method is also implemented using datasheet information for three commercial PV modules made from different technologies: mono-crystalline, poly-crystalline and thin-film technology. This method is an improvement on an existing method and is more accurate. A comparison is made with the characteristics extracted from the datasheet to verify that it produces accurate results. A comparison of this modelling method is also made with the experimentally measured data from the SQ80 PV module. The results obtained were used to draw conclusions on which combination of parameter extraction and modelling method best emulates the manufacturer's characteristics

A Survey of Algorithms, Applications and Trends for Particle Swarm Optimization

Particle swarm optimization (PSO) is a popular heuristic method, which is capable of effectively dealing with various optimization problems. A detailed overview of the original PSO and some PSO variant algorithms is presented in this paper. An up-to-date review is provided on the development of PSO variants, which include four types i.e., the adjustment of control parameters, the newly-designed updating strategies, the topological structures, and the hybridization with other optimization algorithms. A general overview of some selected applications (e.g., robotics, energy systems, power systems, and data analytics) of the PSO algorithms is also given. In this paper, some possible future research topics of the PSO algorithms are also introduced.This research received no external funding

Enhancing the Modeling and Efficiency of Photovoltaic Systems

Solar energy is a strong contender among the sustainable alternatives that offer practical potential for replacing increasingly depleted fossil fuels and supplying the world’s growing energy demands. However, despite its sustainability, the spread of its use has been limited due to the high costs arising from its inadequate efficiency. With this challenge as motivation, the goal of the research presented in this thesis was to contribute to the expansion of the utilization of photovoltaic (PV) systems. To achieve this goal, the work was approached from two perspectives: 1) facilitation of research into PV systems through the enhancement of existing PV models and simulation tools, which are highly complex and necessitate substantial computational effort, and 2) improvement of the efficiency of PV systems through the development of new techniques that mitigate power losses in PV systems. With respect to the first perspective, two innovative modeling approaches are introduced. The first, a new circuit model for PV systems, features accuracy comparable to that of existing models but with a reduced computational requirement. The proposed model mimics the accuracy of existing models without their dependency on a transcendental implicit equation, thus providing a shorter computational time without sacrifying the accuracy. The second modeling approach, which was developed for use in model-based online applications, involved the creation of a fast tool for estimating the power peaks of the power-voltage curves for partially shaded PV systems. Utilizing a PV circuit model for estimating the power peaks in large PV systems through the simulation of their entire power curve consumes extensive computational time, which is unacceptable for online applications even with the use of the proposed circuit model mentioned above. Rather than employing a PV circuit model to find the power peaks, the proposed tool relies on simple rules that govern the formation of power peaks in a partially shaded PV system as a means of establishing the power peaks directly, thus significantly reducing the time required. The second perspective led to the development of three methods for reducing different types of power losses prevalent in PV systems. The first is an MPPT technique for use with partially shaded PV systems that exhibit multiple power peaks in their output power curves. The proposed MPPT is uniquely distinguishable because of its ability to eliminate misleading power losses in PV systems. Rather than searching and scanning heuristically for the GMPP, it employs the fast modeling tool mentioned above to calculate the location of the GMPP deterministically, thus avoiding the need for curve scanning. The irradiance values required by the modeling tool are estimated innovatively using captured images of the PV modules obtained by an optical camera. The objective of the second was to reduce the mismatch power losses common in partially shaded PV systems through the development of an improved PV reconfiguration method. The reconfiguration proposed in this thesis is produced by a simple algorithm that establishes a better configuration and requires only negligible computational time for ensuring the minimization of mismatch power losses. The third is an enhanced maximum power point tracker (MPPT) for reducing tracking power losses in PV systems that operate under rapidly changing irradiance levels. The proposed method combines model-based and heuristic techniques in order to accelerate the tracking speed and thus decrease this type of loss. In the proposed MPPT, the temperature measurements typically necessary in any model-based PV application have been eliminated through reliance on a new set of equations capable of estimating the temperature through the utilization of current and voltage measurements

Optimizing photovoltaic model parameters for simulation

Photovoltaic (PV) model is used in simulation study to validate the system design of a PV system. With an accurate PV model for use in circuit orientated software, the behavior of PV array under different environmental conditions can be observed for study. In this paper, the unknown parameters of a single diode PV model are identified using the Particle Swarm Optimization (PSO) approach with log barrier constraint. The proposed method has been applied to a PV module KC65T and has shown accurate modeling result