Solar Engineering Of Thermal Processes

This paper presents a comprehensive overview on various maximum power point tracking (MPPT) techniques, which have been recently designed, simulated and/or experimentally validated in the PV literature. The primary goal of each MPPT technique is to optimize the output of shaded/unshaded photovoltaic (PV) array under static and dynamic weather conditions. Though each MPPT technique has its own pros and cons, an optimized MPPT technique is characterized in many aspects like hardware and software simplicity, implementation, cost effectiveness, sensors required, popularity, accuracy and convergence speed. In this paper the rating of various MPPT methods has been done based on the benchmark P&O method. The rating criteria is separately calculated for the techniques that are capable to work in full-sun and partial shading conditions. A rule based table is set to evaluate the MPPT against the algorithm's complexity, hardware implementation, tracking speed, and steady state accuracy or detection of global maximum. Moreover, special consideration has been given to bio-inspired MPPT algorithms. The bio-inspired algorithms are compared side by side with their specific application in PV system. A tree diagram is also designed to see the emergence of partial shading algorithms over a period of time. The traits presented in this paper are novel and provide bottom-line for the researchers to select and implement an appropriate MPPT technique.

Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review

Maximum power point tracking (MPPT) control techniques play a vital role in efﬁciency improvement of photovoltaic (PV) systems. It is mainly used to extract maximum possible power of the PV modules under both variable climatic and partial shaded condition (PSC). From literature, various types of MPPT techniques have been developed to track the maximum power point efficiently, ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and drawbacks. This paper focuses mainly on a review on advancements of global maximum power point tracking (GMPPT) techniques of photovoltaic (PV) system subjected to partial shading conditions (PSC) to help the users to make the right choice when designing their system. The most recent and selected MPPT methods are discussed and classified as optimization, hybrid, mathematical model based methods and other GMPPT methods. This study will serve as interesting guide for researchers working on PV system field.

A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions

A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system is presented in this paper. In recent years, there has been a growing attention toward mitigation of partial shading effect of the PV system through using modern optimization. The field of tracking MPP of the PV system attracts huge attention from the researchers, as it is the best way to increase PV plant efficiency. Under non-uniform solar irradiance, the power against voltage characteristics of PV array have more than one MPP. This condition leads to extra complications to track MPP and decreases the efficiency of the PV system. Traditional MPPT methods are typically used to increase the harvested energy of PV under normal conditions without any problems. The key drawback of such methods is failing extraction of global MPP under actual weather conditions that sometimes under shadowing condition. Several global MPPT methods based on modern optimization are presented for extracting global MPP in case of shadowing condition. The essential target of this work is not limited to present an integrated specific review on the state-of-the-art of these techniques; but also a comprehensive statistical evaluation of twenty optimizers that represent high percent of all the reported techniques is performed with changing shading scenarios. This work serves as a source of valuable information for researchers and engineers working with PV systems to keep abreast with the modern advance in the field of tracking MPP of PV system.

A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system

A photovoltaic system is highly susceptible to partial shading. Based on the functionality of a photovoltaic system that relies on solar irradiance to generate electrical power, it is tacitly assumed that the maximum power of a partially shaded photovoltaic system always decreases as the shading heaviness increases. However, the literature has reported that this might not be the case. The maximum power of a partially shaded photovoltaic system under a fixed configuration and partial shading pattern can be highly insusceptible to shading heaviness when a certain critical point is met. This paper presents an investigation of the impact of partial shading and the critical point that reduce the susceptibility of shading heaviness. Photovoltaic string formed by series-connected photovoltaic modules is used in this research. The investigation of the P-V characteristic curve under different numbers of shaded modules and shading heaviness suggests that the photovoltaic string becomes insusceptible to shading heaviness when the shaded modules irradiance reaches a certain critical point. The critical point can vary based on the number of the shaded modules. The formulated equation in this research contributes to determining the critical point for different photovoltaic string sizes and numbers of shaded modules in the photovoltaic string.

https://www.mdpi.com/1996-1073/11/7/1860/pdf

Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String

A New MPPT-based ANN for Photovoltaic System under Partial Shading Conditions

Numerical model and experimental validation of the electrical and thermal performances of photovoltaic/thermal plant

Integrating the Internet of Things (IoT) technology in solar photovoltaic (PV) systems is considered as an important aspect for monitoring, supervising and performances evaluation. The main aim of this work is to design a low-cost monitoring system for the maximum power point tracking (MPPT) in a PV system. Two electronics board have been developed: a data-acquisition sensing and a DC-DC boost converter. The designed monitoring board consists of an embedded board (Arduino Mega 2560 based upon ATmega2560), current and voltage sensors, voltage regulator Mini BEC, LCD Display, and a WiFi module ESP8266 to transmit the monitored data ( $I_{PV}, V_{PV}, V_{L}, I_{L}$ and $D$ ) on the internet. In addition, a website has been also designed to store and display the monitored data in real time. The designed prototype has been verified experimentally at Renewable Energy Laboratory (REL) of Jijel University, Algeria. Based on the monitored data the users can check easily if the system works well or not by just comparing the measured output power with the one expected by a model.

A low-cost monitoring system for maximum power point of a photovoltaic system using IoT technique

Photovoltaic (PV) modules suffer from a reduction of electric conversion due to the high operating temperatures of the PV cells. Hybrid photovoltaic/thermal (PV/T) technology represents an effective solution for cooling the PV cells. This paper discusses a theoretical study on a novel bi-fluid PV/T collector. One dimensional steady-state numerical model is developed, and computer simulations are performed using MATLAB. This numerical model is based on a pilot PV/T plant, installed in the Campus of the University of Catania, and was experimentally validated. The design of the proposed bi-fluid PV/T is based on a commercial WISC PV/T collector, to which are added an air channel, an aluminum absorber with fins, and a layer of thermal insulation. The analysis of the thermal behavior of the proposed collector is carried out as a function of the flow rate of the two heat transfer fluids (air and water). Finally, the comparative analysis between the conventional water-based PV/T collector, namely PV/T, and the bi-fluid (water/air-based) WISC PVT, namely PV/Tb, is presented for both winter and summer days. For the investigated winter day, the numerical results show an overall improvement of the performance of the bi-fluid PV/T module, with an increase of thermal energy transferred to the liquid side of 20%, and of 15.3% for the overall energy yield in comparison to the conventional PV/T collector. Instead, a loss of 0.2% of electricity is observed. No performance improvements were observed during the summer day.

Electrical and Thermal Performances of Bi-Fluid PV/Thermal Collectors

Over many years, a number of tracking control methods of the maximum power point (MPPT) from the photovoltaic (PV) systems have been developed. The performances of these methods under varying environmental conditions vary in terms of energy capture, conversion efficiency, response time and reliability. This paper presents a comparative analysis between different MPPT, that are perturb-and-observe (P&O), incremental conductance(INC), fuzzy logic controller (FLC) and artificial neural networks (ANN). A model of PV module and DC/DC boost converter with the different techniques of MPPTs was simulated using MATLAB/Simulink environment. The simulation results show that the artificial neural networks (ANN) MPPT technique is more efficient when compared to other techniques and presents an estimated fast response of 98.41.

Bekkay Hajji

Papers

A New MPPT-based ANN for Photovoltaic System under Partial Shading Conditions

Numerical model and experimental validation of the electrical and thermal performances of photovoltaic/thermal plant

A low-cost monitoring system for maximum power point of a photovoltaic system using IoT technique

Electrical and Thermal Performances of Bi-Fluid PV/Thermal Collectors

Comparative study of different MPPT methods for photovoltaic system