Output Power Of Photovoltaic Array Research Articles

Improved Performance of an Asynchronous Motor Drive with a New Modified Incremental Conductance based MPPT Controller

This paper describes the improved performance of an asynchronous motor drive with a new modified Incremental conductance-based MPPT controller. In the last few decades, renewable energy sources are playing a dominant role in electricity generation as non-renewable energy sources are becoming extinguish and are the major cause of global warming. Photovoltaic (PV) energy is the most important energy resource since it is clean, pollution-free, and inexhaustible. Maximum power point tracking (MPPT) is used in photovoltaic systems to maximize the photovoltaic array output power with variable irradiances and variable temperature. The space vector modulation technique is used to reduce ripple content and fluctuation with improving efficiency. The algorithm used in MPPT is the Incremental Conductance method for a solar PV system to determine maximum output power.

Review of photovoltaic water pumping system research

Currently a considerable and the most economically justified potential of making the solar energy conversion more efficient and making the solar energy more attractive for consumers involves the coordination of the entire equipment from generation to consumption while considering all this equipment as a unified system and taking the degree of satisfaction of the consumer needs as the measure of efficiency. A photovoltaic water pumping system (PVWPS) is the first and one of few types of ground photovoltaic systems where the consumption equipment was always considered from the onset as part of the system. So a retrospective analysis of PVWPS research is of particular interest. This article contains the PVWPS research analysis beginning with the first research conducted in 1964–1966 to date. Discussed herein are the main problems that arose in the PVWPS development, operation, and optimization as well as options of their solution. Various areas of PVWPS improvement research were analyzed, including research involving photovoltaic array structure and photovoltaic modules interconnection; development and improvement of special structures of any components (pumps and invertors, etc.); improvement of photovoltaic array and electric motor interaction, electric motor and pump interaction against the backdrop of irradiance variation and in conjunction with consumption optimization and control improvement, to start with maximum power point tracing. It would make sense to aim further research involving cost reduction, productivity gain, and PVWPS service life extension at the expansion of the fields of PVWPS application, improvement of individual PVWPS components, and a more efficient use of water that is drawn. One of the prospective lines of PVWPS improvement and upgrading is to include them in the system of end user consumption equipment and assess the system efficiency not at the pump output and not in the point of end consumption equipment but after the water consumption. Studying PVWPS with the account of the fact that, in real conditions, the average output power of photovoltaic array depends not only on irradiance but also on the combined effect of all environmental conditions (climatic parameters, current state of atmosphere and air, surrounding objects, etc.) is of great importance, today.

An Improved Feasibility Analysis of Photovoltaic Array Configurations and Reconfiguration Under Partial Shading Conditions

—Globally, the shading phenomenon has been identified as one of the major issues relating to the successful and effective operation of photovoltaic (PV) system. Shading can be due to neighboring development, passing mists, fowls or winged animals’ litter, etc. that will decrease the generation of PV system. The PV generations under partial shading can be enhanced by suitably selecting PV array configuration and reconfiguration schemes. This article provides an extensive investigation of various PV array configurations and reconfiguration operating in partial shading conditions. The competence with reference to maximum power output, shading losses, fill factor, and mismatch losses of PV array configuration, i.e., Series-Parallel (SP), Honey-Comb (HC), Total Cross Tied (TCT), Bridge-linked (BL), and reconfiguration namely; Odd–Even (OE) are evaluated for four different shading case studies. The results are compared with 7 × 7 PV array configuration for the same shading cases. The investigation is expanded to identify the outcomes of incorporating a bypass diode in each module on power output. The investigations carried out also reveal that the shading scenario decides the maximum instantaneous power output of PV array. The outcomes exhibit that OE reconfiguration provides improved performance concerning to maximum power generation for all considered shading case studies.

A Cuckoo MPPT based SMC Control for Grid tied PV System

Maximum power point techniques (MPPT) are used in photovoltaic system to make full utilization of PV array output power. The output power of PV array is always changing with weather conditions i.e., solar irradiation and atmospheric temperature. PV cell generates power by converting sunlight into electricity. The electric power generated is proportional to solar radiation. PV cell can generate around 0.5 to 0.8 volts. During cloudy weather due to varying insolation levels the output of PV array varies. The MPPT is a process which tracks the maximum power from array and by increasing the duty cycle of the DC-DC boost converter, the output voltage of the system is increased. This paper presents the cuckoo mppt technique for PV system along with SMC controller methods in grid connected photovoltaic (PV) systems for optimizing the solar energy efficiency

Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns

The analysis and the assessment of interconnected photovoltaic (PV) modules under different shading conditions and various shading patterns are presented in this paper. The partial shading conditions (PSCs) due to the various factors reduce the power output of PV arrays, and its characteristics have multiple peaks due to the mismatching losses between PV panels. The principal objective of this paper is to model, analyze, simulate and evaluate the performance of PV array topologies such as series-parallel (SP), honey-comb (HC), total-cross-tied (TCT), ladder (LD) and bridge-linked (BL) under different shading patterns to produce the maximum power by reducing the mismatching losses (MLs). Along with the conventional PV array topologies, this paper also discusses the hybrid PV array topologies such as bridge-linked honey-comb (BLHC), bridge-linked total-cross-tied (BLTCT) and series-parallel total-cross-tied (SPTCT). The performance analysis of the traditional PV array topologies along with the hybrid topologies is carried out during static and dynamic shading patterns by comparing the various parameters such as the global peak (GP), local peaks (LPs), corresponding voltage and current at GP and LPs, fill factor (FF) and ML. In addition, the voltage and current equations of the HC configuration under two shading conditions are derived, which represents one of the novelties of this paper. The various parameters of the SPR-200-BLK-U PV module are used for PV modeling and simulation in MATLAB/Simulink software. Thus, the obtained results provide useful information to the researchers for healthy operation and power maximization of PV systems.

MPPT control of PV array based on PSO and adaptive controller

In general, photovoltaic (PV) array is not able to generate maximum power automatically, because some partial shading caused by trees, clouds, or buildings. Irradiation imperfections received by the PV array are overcome by applying maximum power point tracking (MPPT) to the output of the PV array. In order to overcome these partial shading problems, this system is employing particle swarm optimization (PSO) as MPPT method. It optimizes the output power of the solar PV array by Zeta converter. Output voltage of MPPT has high rate such that it needs stepdown device to regulate certain voltage. Constant voltage will be the input voltage of buck converter and controlled using adaptive PID. Adaptive control based on model reference adaptive control (MRAC) has design that almost same as the conventional PID structure and it has better performance in several conditions. The proposed system is expected to have stable output and able to perfectly emulate the response of the reference model. From the simulation results, it appears that PSO have high tracking accuracy and high tracking speed to reach maximum power of PV array. In the output voltage regulation, adaptive control does not have a stable error status and consistently follows the set point value.

Machine Learning Based Approaches for Modeling the Output Power of Photovoltaic Array in Real Outdoor Conditions

It is important to investigate the long-term performances of an accurate modeling of photovoltaic (PV) systems, especially in the prediction of output power, with single and double diode models as the configurations mainly applied for this purpose. However, the use of one configuration to model PV panel limits the accuracy of its predicted performances. This paper proposes a new hybrid approach based on classification algorithms in the machine learning framework that combines both single and double models in accordance with the climatic condition in order to predict the output PV power with higher accuracy. Classification trees, k-nearest neighbor, discriminant analysis, Naïve Bayes, support vector machines (SVMs), and classification ensembles algorithms are investigated to estimate the PV power under different conditions of the Mediterranean climate. The examined classification algorithms demonstrate that the double diode model seems more relevant for low and medium levels of solar irradiance and temperature. Accuracy between 86% and 87.5% demonstrates the high potential of the classification techniques in the PV power predicting. The normalized mean absolute error up to 1.5% ensures errors less than those obtained from both single-diode and double-diode equivalent-circuit models with a reduction up to 0.15%. The proposed hybrid approach using machine learning (ML) algorithms could be a key solution for photovoltaic and industrial software to predict more accurate performances.

Optimal Photovoltaic Array Dynamic Reconfiguration Strategy Based on Direct Power Evaluation

In actual operation, photovoltaic arrays inevitably encounter shadow problems, resulting in a power output decline and multiple peaks in the output characteristics. The effect of partial shade can be satisfactorily reduced by photovoltaic array reconfiguration. Almost all current reconfiguration techniques are based on the irradiance equalization principle. However, by analyzing the output characteristics of photovoltaic array, it is found that the irradiance equalization principle improves the output power by increasing only the minimum row current without considering the effect of the voltage, so the reconfiguration techniques based on this principle cannot obtain the global optimal configuration under some partial shading conditions. In order to maximize the output power of photovoltaic array under any partial shaded condition, this paper proposes a reconfiguration strategy based on direct power evaluation. In this approach, the reconfiguration problem is formulated as a 0-1 multi-knapsack problem, and a novel mathematical model is established to directly evaluate the maximum output power of photovoltaic array. Then, the optimal reconfiguration scheme is determined by solving the mathematical model. Finally, the effectiveness of the proposed reconfiguration strategy is proved in theory and simulations.

A real-time energy management method for electric-hydrogen hybrid energy storage microgrid based on DP-MPC

With increasing presence of intermittent energy resource in microgrid, it is so difficult to precisely predict the output of renewable resources and the load demand. In order to realize the economical operation of the system, an energy management method based on model predictive control (MPC) and dynamic programming (DP) algorithm is proposed. This method can reasonably distribute the energy of battery, fuel cell, electrolyzer and external grid, and maximize the output of distributed power supply while ensuring the power balance and cost optimization of the system. Based on the ultra-short-term forecast, the output power of photovoltaic array and the demand power of system load are predicted. The off-line global optimization of traditional dynamic programming is replaced by the repeated rolling optimization in a limited period of time to obtained power values of each unit in the energy storage system. Compared with the traditional DP, MILP-MPC and the logic based real-time management method, the proposed energy management method is proved to be feasible and effective.

Adaptive voltage control for MPPT-firefly algorithm output in PV system

In general, Photovoltaic (PV) array is not able to generate maximum power automatically, because some partial shading caused by trees, clouds, or buildings. Irradiation imperfections received by the PV array are overcome by applying Maximum Power Point Tracking (MPPT) to the output of the PV array. In order to overcome these partial shading problems, this system is employing Firefly Algorithm (FA) as MPPT method. It optimizes the output power of the solar PV array by Zeta Converter. Output voltage of MPPT has high rate such that it needs stepdown device to regulate certain voltage. Constant voltage will be the input voltage of Buck Converter and controlled using Adaptive PID. Adaptive control based on MRAC has design that almost same as the conventional PID structure and it has better performance in several conditions. The proposed system is expected to have stable output and able to perfectly emulate the response of the reference model. From the simulation results, it appears that FA have high tracking accuracy and high tracking speed to reach maximum power of PV array. In the output voltage regulation, adaptive control does not have a stable error status and consistently follows the set point value.

Quantitative estimation of mismatch losses in photovoltaic arrays under partial shading conditions

Partial shading can significantly reduce the output power of photovoltaic (PV) arrays due to mismatch losses. The mismatch losses mainly depend on the shading levels of shaded modules in the PV array. A judgment method for the states of the blocking diodes in PV modules under partial shading conditions is presented to quantify the electrical mismatch losses of PV arrays. A single diode model without any approximation is employed to find the electrical parameters of PV modules precisely from the manufacturer’s datasheet. The output characteristics of PV arrays at maximal power conditions are determined with the Lambert W function. The overall effect of the mismatch losses caused by partial shading on the output power of PV arrays with blocking diodes protection is analyzed in detail. Three types of PV arrays are utilized to quantify the mismatch losses in PV arrays under partial shading conditions. Simulation results indicate that the conventional crystalline technologies are more affected by partial shading than the thin-film technology. The PV arrays suffer from various degrees of power mismatch under partial shading conditions.

Optimal SuDoKu Reconfiguration Technique for Total-Cross-Tied PV Array to Increase Power Output Under Non-Uniform Irradiance

Partial shading condition drastically reduces the maximum power output of photovoltaic array. Partial shading occurs due to several factors, such as flying birds, trees, and passing clouds. Many ways can be mitigated partial shading problems in photovoltaic (PV) array. One among the way is reconfiguration techniques, namely reconfigure the location of PV modules in PV array based on irradiance levels in order to distribute shading effects and increasing maximum power. This paper proposed an optimal SuDoKu reconfiguration pattern for $9\times 9$ total-cross-tied (TCT) PV array to improve maximum power under partial shading conditions. In this approach, the physical location of PV modules in TCT array are rearranged based on optimal SuDoKu style without altering the electrical connections, so that the shading effects can distribute over the array. Further, the performance of proposed pattern investigated with existing SuDoKu pattern under different shading conditions by comparing the global maximum power point, mismatch losses, fill-factor, and efficiency using MATLAB-Simulink. Based on the results of this paper, it concluded that the proposed optimal SuDoKu reconfiguration arrangement is reducing the wiring arrangement and increasing the shading distribution over the array as compared to SuDoKu arrangement.

Improvements in Performance Analysis of Photovoltaic Systems: Array Power Monitoring in Pulse Width Modulation Charge Controllers

Various challenges should be considered when measuring photovoltaic array power and energy in pulse width modulation (PWM) charge controllers. These controllers are frequently used not only in stand-alone photovoltaic (SAPV) systems, but may also be found in photovoltaic (PV) self-consumption systems with battery storage connected to the electricity grid. An acceptable solution may be reached using expensive data acquisition systems (DASs), although this could be generally disproportionate to the relatively low cost of SAPV systems. Therefore, the aim of this paper is to develop new and effective monitoring techniques which will provide the PV array direct current (DC), output power (PA,dc), and PV array DC output energy (EA), thus avoiding the use of sophisticated DASs and providing high accuracy for the calculated parameters. Only transducers and electronic circuits that provide the average and true rms values of the PWM signals are needed. The estimation of these parameters through the aforementioned techniques showed high accuracy for both series and shunt PWM battery charge controllers. Normalized root mean square error (NRMSE) was lower than 2.4%, normalized mean bias error (NMBE) was between −1.5% and 1.1%, and mean absolute percentage error (MAPE) was within 1.6%.

A new model-based technique for fast and accurate tracking of global maximum power point in photovoltaic arrays under partial shading conditions

This paper presents a new model-based method to extract the global maximum power point (GMPP) of photovoltaic (PV) arrays under partial shading conditions (PSCs). In the proposed method, it is shown that independent of the pattern and intensity of the solar radiation, the position of the PV array GMPP voltage is always in the neighboring of one of the strings GMPP voltages in the PV array. Therefore, the number of local peak points tested in the proposed method is independent of the solar radiation pattern and is equal to the number of parallel strings in the PV array. As a result, for tracking of PV array GMPP in the PSCs, at first, the GMPP of each of PV strings is estimated. Next, by the numerical solution of the PV string nonlinear equations, the PV array output current and power are calculated corresponding to each of PV string GMPP voltages, and the voltage that results in the highest PV array output power is detected as the PV array GMPP voltage. Numerical results and comparative studies with similar methods confirm the satisfactory operation of the proposed technique.

Performance Comparison of Mismatch Power Loss Minimization Techniques in Series-Parallel PV Array Configurations

The mismatch in current-voltage (I-V) characteristics of photovoltaic (PV) modules causes significant power loss in a large PV array, which is known as mismatch power loss (MML). The PV array output power generation can be improved by minimizing MML using different techniques. This paper investigates the performance of different module arrangement techniques to minimize MML both for long series string (LSS) and long parallel branch (LPB) in series-parallel (SP) array configurations at uniform irradiance condition. To investigate the significance of MML LSS-SP configuration with dimensions: 1 × 40, 2 × 20, 4 × 10, 5 × 8 and LPB-SP configuration with dimensions: 40 × 1, 20 × 2, 10 × 4, 8 × 5 were used. A comparative analysis is made to find the effectiveness of MML reduction techniques on PV arrays with three different power ratings. Simulation results show that the PV modules arrangement obtained by the genetic algorithm (GA) and current based arrangement (Im) performed better than the arrangements obtained by all other techniques in terms of PV array output power and MML minimization. The performance of the proposed technique was analyzed for both LSS-SP and LPB-SP array configurations in 400 W, 3400 W, and 9880 W arrays. To substantiate the simulation results experiment was performed using a 400 W PV array in outdoor weather condition and obtained similar results. It was also observed that the percentage of recoverable energy (%RE) obtained by arranging the modules using the GA method was higher than Im based method for both LSS-SP and LPB-SP array configurations. A maximum %RE of 4.159 % was recorded for a 5 × 8 LSS-SP array configuration by applying the GA based MML reduction method.

IMPROVEMENT IN OUTPUT POWER BY DESIGNING ADAPTIVE REFERENCE CONTROL FOR BOOST CONVERTER IN SOLAR SYSTEM

Maximum power point tracking (MPPT) techniques are used in photovoltaic (PV) systems to maximize the PV array output power by tracking continuously the maximum power point (MPP) which depends on panels temperature and on irradiance conditions. In this work we have made a comparison between P & O algorithm with proposed adaptive reference algorithm. It has been concluded that The power output with adaptive reference algorithm at the load terminal is coming to be 6.5 kilo Watts approximately where as with P & O it is calculated to be 1.5 kilo watts approximately. Hence it is a better proposed algorithm as compared to traditional P & O technique

Design of Maximum Power Point Tracking for Solar Collector Drying System: An Experimental Study

<p class="Default"><span lang="EN-US">This research describes the performance of maximum power point tracking as a solar collector of PV system integration for agriculture product drying system. The system comprises of solar collector, tracking PV array, the battery bank, the micro controller and the DC converter. This system is design to enhance the work of solar collector in drying process.. This design is hoped to be an appropriate system in order to ensure the maximum result by providing solar radiation energy. This paper shows the experiment data of the voltage and power response in positioning the PV to yield a maximum photovoltaic array output power of solar drying system device.</span></p>

Hybrid method for short‐term photovoltaic power forecasting based on deep convolutional neural network

Photovoltaic (PV) electric power has been widely employed to satisfy rising energy demands because inexhaustible renewable energy is environmentally friendly. In order to mitigate the impact caused by the uncertainty of solar radiation in grid-connected PV systems, a hybrid method based on a deep convolutional neural network (CNN) is introduced for short-term PV power forecasting. In the proposed method, different frequency components are first decomposed from the historical time series of PV power through variational mode decomposition (VMD). Then, they are constructed into a two-dimensional data form with correlations in both daily and hourly timescales that can be extracted by convolution kernels. Moreover, the time series of residue from VMD is refined into advanced features by a CNN, which could reduce the data size and be easier for further model training along with meteorological elements. The hybrid model has been verified by forecasting the output power of PV arrays with diverse capacities in various hourly timescales, which demonstrates its superiority over commonly used methods.

Multiple Fault Location in a Photovoltaic Array Using Bidirectional Hetero-Associative Memory Network in Micro-Distribution Systems

In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination-based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes as input variables are parameterized to quantify the degradation between estimated maximum PV output power and metered PV output power, which can be categorized into normal condition, grounded faults, open-circuit faults, bridged faults, and mismatch faults. Bidirectional hetero-associative memory (BHAM) networks are then used to associate the inputs and locate multiple faults as output variables within the PV array. For a rooftop PV system with two strings, experimental results demonstrate that the proposed model has computational efficiency in learning and detection accuracies for real-time applications, and that its algorithm is easily implemented in a mobile intelligent vehicle.

Reconfiguration technique for Optimization of the Photovoltaic array output power under partial shading conditions

A partial shading condition is a case under which the PV array is exposed to many problems such as losses of the output power of the PV array, and the PV array has more than one maximum power point (MPP), which makes it so difficult to track the MPP. This paper presents the effect of different partial shading patterns on PV array characteristics and the effect on the output power of the PV array, and provides a comparative literature review on methods to mitigate these effects and the drawbacks of these methods. It also proposed a new reconfiguration strategy that increases the output power of the PV array by 13.8 % from the total power under shadow condition, and a new technique for enhancing the output power of the PV array by 20 % of the total power under fully illumining conditions by controlling the switch matrix between the photovoltaic array and adaptive batteries bank. This paper gives a solution for the problem of the difficulty of tracking the MPP, because the proposed strategy makes only one MPP. The simulation was carried out by using MATLAB Simulink under different shading patterns. Citation: Mohamed, A. M., Saafan, S. M., Attalla, A. M., and Elgohary, H. (2018). Reconfiguration technique for Optimization of the Photovoltaic array output power under partial shading conditions. Trends in Renewable Energy, 4, 111-124. DOI: 10.17737/tre.2018.4.2.0068