A two stage successive estimation based maximum power point tracking technique for photovoltaic modules

Solar photovoltaic (PV) system contributes a significant role in meeting power requirements and helps the decentralization of power generation and distribution. The output of the individual photovoltaic module depends on local temperature and irradiance. Since the variation of these parameters depends on the environmental factors, it is difficult to obtain maximum power in all instances. The maximum power point tracking (MPPT) technique is used for tracking the maximum power available at a particular instant. This paper presents the maximum power extraction from a photovoltaic system using Artificial Intelligence (AI) techniques. AI based methods provide a fast dynamic response with high accuracy and mitigate the effects of partial shading. A comparative study is performed for various AI based MPPT techniques such as Fuzzy, Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS). PV module output is interfaced with the resistive load through the Z-Source inverter (ZSI). The ZSI boost the input voltage and provides an AC output voltage. The AI based MPPT techniques have been investigated with conventional Z-source Inverter (ZSI) and Switched Inductor Z-Source inverter (SL-ZSI). A simple boost control technique is employed to control, both conventional and SL Z-source inverter. The performance of the system is verified using MATLAB Simulink.

Renewable energy is an attractive solution for water pumping systems particularly in isolated regions where the utility grid is unavailable. An attempt is made to improve the performance of solar photovoltaic water pumping system (SPVWPS) under partial shading condition. Under this condition, the power versus voltage curve has more than one maximum power point (MPP), which makes the tracking of global MPP not an easy task. Two MPP tracking (MPPT) strategies are proposed and compared for tracking MPP of SPVWPS under shading condition. The first method is based on the classical perturb and observe (P&O) and the other method is based on a Salp Swarm Algorithm (SSA). Based on extensive MATLAB simulation, it is found that the SSA method can provide higher photovoltaic (PV) generated power than the P&O method under shading condition. Consequently, the pump flowrate is increased. But, under normal distribution of solar radiation, both MPPT techniques can extract the maximum power but SSA is considered a time-consuming approach. Moreover, SSA is compared with particle swarm optimization (PSO) and genetic algorithm (GA). The obtained results ensure the superiority of SSA compared with PSO and GA. SSA has high successful rate of reaching true global MPP.

Photovoltaic (PV) systems are gradually becoming the key renewable source of electrical energy. But the nonlinear characteristics of the PV module require special techniques to harvest maximum power. The techniques used to track the Maximum Power Point (MPP) from the nonlinear I-V characteristics through power electronic circuits are known as Maximum Power Point Tracking (MPPT) techniques. Although enormous MPPT techniques have been anticipated in literature, each endures its own advantages and disadvantages. This paper proposes a novel hybrid technique to enhance the performance of Incremental conductance (InC) technique. Our proposed technique removes the limitations of InC under rapid changing environmental condition. It improves the efficiency and reduces the oscillation power loss under steady state. A hybrid combination of variable-step sized Incremental Conductance with Fractional Short Circuit Current (FSCC) technique is proposed in this research work. Initially, the FSCC forces the PV system to work near MPP and then InC technique track the exact peak. Matlab/Simulink software is used to implement the proposed hybrid technique. Finally, the results verify its superior performance under rapidly changing environmental conditions.

Herein, the voltage and current output characteristics of a laser photovoltaic (PV) module applied to a wireless power transmission system using a laser beam are analyzed. First, an experiment is conducted to obtain the characteristic data of the voltage and current based on the laser output power of the laser PV module, which generates the maximum power from the laser beam at a wavelength of 1080 nm; subsequently, the small-signal voltage and current characteristics of the laser PV module are analyzed. From the analysis results, it is confirmed that the laser PV module has a characteristic in which the maximum power generation point varies according to the power level of the laser beam. In addition, similar to the solar cell module, it is confirmed that the laser PV module has a current source and a voltage source region, and it shows a small signal resistance characteristic having a negative value as the operating point goes to the current source region. In addition, in this paper, by reflecting these electrical characteristics, a method for designing the controller of a power converter capable of charging a battery while generating maximum power from a PV module is proposed. Since the laser PV module corresponds to the input source of the boost converter used as the power conversion unit, the small-signal transfer function of the boost converter, including the PV module, is derived for the controller design. Therefore, by designing a controller that can stably control the voltage of the PV module in the current source, the maximum power point, and voltage source regions defined according to the output characteristics of the laser PV module, the maximum power is generated from the PV module. Herein, a systematic controller design method for a boost converter for laser wireless power transmission is presented, and the proposed method is validated based on the simulation and experimental results of a 25-W-class boost converter based on a microcontroller unit control.

This paper presents a MATLAB-based modeling and simulation scheme suitable for studying the I-V and P-V characteristics of a PV under a nonuniform insolation due to partial shading. In the first, part a solar cell block is available in MATLAB®/Similink, which was used with many other blocks to plot I-V and P-V characteristics under variations of parameters considering one parameter variation at a time. The effect of variation of parameters such as series resistance, Rs, shunt resistance Rsh, diode parameter: diode saturation current, I0, could be seen on the characteristics of a solar cell. Effect of two environmental parameters of temperature and irradiance variations could also be observed from simulated characteristics. In the second part, the performance of a photovoltaic (PV) array is affected by temperature, solar insolation, shading. Often, the PV arrays get shadowed, completely or partially, by the passing clouds neighboring buildings, towers or by trees, etc. The situation is of a particular interest in a case of the large PV power plants. In the case of the shading the characteristics of the PV module are more complex with the several peak values. Under such conditions, it is very difficult to determine the maximum power point (MPP). Finally, MATLAB-programmed modeling and simulation of photovoltaic systems is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) systems. The proposed model facilitates simulating the dynamic performances of PV-based power systems and also has been validated by means of simulation study.

The modelling of photovoltaic (PV) solar panels requires electrical parameters which are dependent on the manufacturing materials and their physical properties. Manufacturers typically do not disclose detailed physical properties of the PV module, except for some electrical quantities such as open circuit voltage ( V oc ), short‐circuit current ( I sc ), maximum power point voltage ( V m ), maximum power point current ( I m ) and maximum power ( P M ). However, to model the PV panels comprehensively, it is necessary to determine other physical parameters, e.g., series resistance of PV cell ( R s ), shunt resistance of PV cell ( R Sh ) and diode ideality factor ( n ). This paper presents a generalised mathematical model of a PV panel utilising only the quantities provided in manufacturer's datasheet. The proposed modelling technique determines all the PV panel parameters without any explicit repetitive iteration. Although the developed model is general and can be implemented on any software platform, its implementation is demonstrated on a commercial electromagnetic transients simulation software electro magnetic transient including direct current power systems computer aided design. The electrical parameters obtained from the proposed PV panel model are validated for six different commercially available PV panels from their datasheet values and also from measurements provided by National Institute of Standards and Technology for solar irradiation and temperature at nonstandard test conditions.

In this paper, we investigate theoretically a radial n+/p silicon solar cell in steady state and monochromatic illumination. The purpose of this work is to analyze the effect of the cell base radius on its electrical parameters. The continuity equation in cylindrical coordinates is established and solved based on Bessel functions and boundaries conditions; this led us to the photovoltage and photocurrent density in the cell. The open circuit voltage and the short circuit current density are then deduced and analyzed considering the base radius. Based on J-V and P-V curves, series and shunt resistances, fill factor and maximum power point are derived and the conversion efficiency of the cell is deduced. We showed that short circuit current density, maximum power, conversion efficiency and shunt resistance decrease with increasing base radius contrary to the open circuit voltage, the fill factor and the series resistance.

Online extraction of physical parameters of photovoltaic modules in a building-integrated photovoltaic system

Purpose Silicon photovoltaics technology has drawbacks of high cost and power conversion efficiency. In order to extract the maximum output power of the module, maximum power point (MPP) is used by implying the nonlinear behavior of I-V characteristics. Different techniques are used regarding maximum power point tracking (MPPT). The paper aims to review the techniques of MPPT used in PV systems and review the comparison between Perturb and Observe (P&O) method and incremental conductance (IC) method that are used to track the maximum power and gives a comparative review of all those techniques. Design/methodology/approach A study of MPPT techniques for photovoltaic (PV) systems is presented. Matlab Simulink is used to find the MPP using P&O simulation along with IC simulation at a steady temperature and irradiance. Findings MATLAB simulations are used to implement the P&O method and IC method, which includes a PV cell connected to an MPPT-controlled boost converter. The simulation results demonstrate the accuracy of the PV model as well as the functional value of the algorithms, which has improved tracking efficiency and dynamic characteristics. P&O solution gave 94% performance when configured. P&O controller has a better time response process. As compared to the P&O method of tracking, the incremental conductance response rate was significantly slower. Originality/value In PV systems, MPPT techniques are used to optimize the PV array output power by continuously tracking the MPP under a variety of operating conditions, including cell temperature and irradiation level.

Solar cell has the current-voltage (I-V) characteristic which is affected by the radiation and the temperature. To obtain the maximum electricity from the solar cells, the power converters for PV (photovoltaic) module have a function called MPPT (maximum power point tracking). The dc voltage and current are controlled to track the maximum power point (MPP) where the PV modules feed the maximum output power. AC module is composed of a PV module and a module integrated converter (MIC). The output port is connected with the ac wiring. Each module can operate with tracking the own MPP. In case of AC module, the basic characteristic of the PV module is well-known by the manufacturer. Therefore the domain of MPP is approximately predicted. In this paper, a novel MPPT method for the MIC is proposed. The proposed method takes full advantage of the known PV module characteristic. The I-V plane is divided into two domains by a linear function. One includes MPPs and the other one never includes MPPs under the normal temperature and radiation conditions. The operating point can be rapidly approached to the MPP using the linear function. Around the MPP, the algorithm is switched to the IncCond method. Circuit experiments have been carried out. The measured time taken for the approach to the MPP is reduced from 22 % to 48 % compared to the conventional algorithm. The proposed method is quite simple so that it can be easily applied to various MPPT algorithms

This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

The advancement of human civilization has resulted in rapid industrialization, which has been accompanied by urbanization and globalization, resulting in increased global energy demand. This chapter examines the need for unconventional energy sources because conventional sources are depleted at a faster rate, appearing to be unable to fulfill rising energy demand on their own. The sun is a renewable energy source that can be considered one of the good solutions to the energy crisis. The photovoltaic (PV) cells are typically expensive and inefficient, so getting the most power out of them is one of the most important aspects of solar energy research. It is really essential to keep track of the Maximum Power Point (MPP). There are many conventional maximum power point tracking (MPPT) techniques for extracting maximum power from panel which are given in this chapter but most commonly used MPPT techniques like Perturb and Observe and Incremental Conductance techniques are explained in detail with their algorithms, graphs, simulation results, benefits and drawbacks.

Maximum Power Point Tracking (MPPT) techniques are used to maintain the photovoltaic (PV) panel operating point near its maximum power point (MPP). In general, the location of the MPP on the V-I plane is not known, but it can be reached, either through a-priori knowledge or by search algorithms. Lots of tracking algorithms have been presented in literature, and in the last years the focus has been moved on improving the performance during rapid changes without sacrificing the efficiency in steady state conditions. Model-based (MB) MPPT techniques guarantees excellent dynamic performance, since they locate MPP directly from a model of the PV panel in the present operating conditions, which are represented by solar radiation and temperature. In a recent paper the authors have presented a new approach to MPPT for PV panels which do not require a direct measurement of the solar radiation. In this work it will be shown how a simpler model can be employed to track MPP using an iterative technique. This method has been validated through experimentation.

Solar cells have a current-voltage (I-V) characteristic affected by the radiation and temperature. To obtain the maximum electricity from solar cells, the power converters for PV (photovoltaic) modules have a function called MPPT (maximum power point tracking). Under the various conditions, the dc input voltage or current is controlled to track the maximum power point (MPP) where the PV modules feed the maximum output power. A module integrated converter (MIC) is individually installed behind of a PV module. In this type, manufacturers can obtain the basic characteristics of the PV module in the manufacturing process. Therefore, the domain of MPP can be predicted. The plane division (PD) MPPT method takes full advantage of the known I-V characteristic. The I-V plane is divided into two domains by a PD function. One includes MPPs and the other one doesn't. Using the PD function, the operating point can rapidly approach the MPP. In this paper, a combination of two or three linear functions is proposed and tested. In circuit experiments, the measured approaching time to the MPPs is reduced from 87.0% to 65.0% for the combination of three linear functions compared to the IncCond algorithm. Based on the measured data, the proposed functions are also compared to the previous PD functions. Consequently, the square root function and the combination of three linear functions are superior to the others. The PD-MPPT, which can be easily added to various MPPT algorithms, is effective to accelerate the MPPT operation of the MIC

Predicting the performance of photovoltaic (PV) systems in industrial applications has become increasingly important due to the complex and non-linear behavior of PV modules. Accurate performance prediction is essential for optimizing energy production and ensuring system reliability. However, a significant challenge arises from the lack of critical information in manufacturer datasheets, which often do not include all the necessary details for precise PV module modeling. This limitation can hinder accurate analysis and system performance evaluation. Optimization methods are recommended to accurately determine the electrical and physical characteristics of PV cells and modules to address this issue. These methods enable detailed and precise analysis of current-voltage (I-V) and power-voltage (P-V) characteristics across various PV models, improving the overall modeling accuracy. Among these methods, the Rao-1 optimization technique has been selected and evaluated in this paper to solve this issue. It is specifically used to extract the unknown parameters of photovoltaic models, including the photo-generated current (Iph), diode ideality factor (n), series resistance (Rs), reverse saturation current (I0), and shunt resistance (Rsh). The effectiveness of the Rao-1 optimization method has been demonstrated through its successful application in estimating PV parameters across a wide range of datasets, ensuring its reliability and adaptability for various industrial scenarios.