Maximum Power Point Tracking of Multi-String Photovoltaic Array via Simultaneous Perturbation Stochastic Approximation

Author(s):  
Yan Xiao ◽  
Yaoyu Li ◽  
John E. Seem ◽  
Kaushik Rajashekara

This paper presents a Maximum Power Point Tracking (MPPT) strategy for multi-string photovoltaic (PV) systems using the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. The multi-string PV system considered is a decentralized control configuration, controlling the voltage reference to each PV module but based on the feedback of the total power at the DC bus. This requires only one pair of voltage and current measurements. The MPPT control problem for such topology of multi-string PV systems features a high input dimension, which can dramatically slow down the searching process for the real-time optimization process involved. The SPSA algorithm is considered in this study due to its remarkable capability of fast convergence for high dimensional search problems endorsed by various applications recently. Simulation study is performed for an 8-string PV system, and experimental study is performed for a 4-string PV system. Good performances are observed for both simulation and experimental results.

2015 ◽  
Vol 787 ◽  
pp. 227-232 ◽  
Author(s):  
L.A. Arun Shravan ◽  
D. Ebenezer

In recent years there has been a growing attention towards use of solar energy. Advantages of photovoltaic (PV) systems employed for harnessing solar energy are reduction of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behaviour of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. This paper reviews various MPPT methods based on three categories: offline, online and hybrid methods. Design of a PV system in a encoding environment has also been reviewed here. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.


Author(s):  
I. A. Elzein ◽  
Yu. N. Petrenko

In this article an extended literature surveying review is launched on a set of comparative studies of maximum power point tracking (MPPT) techniques. Different MPPT methods are addressed with an ultimate aim of how to be maximizing the PV system output power by tracking Pmax in a set of different operational circumstances. In this paper maximum power point tracking, MPPT techniques are reviewed on basis of different parameters related to the design simplicity and/or complexity, implementation, hardware required, and other related aspects.he technology of solar systems has been booming for a while due to its ability to replace current fossil fuels like coal and gas for generation of electricity that produce air, water, and land pollution. In addition it decreased the issue of global warming and climate changes substantially due to being produced in a clean environmental manner and was proved to be an Eco-friendly resource of energy. The photovoltaic systems’ manufacturing process has been improving continuously over the last decade and photovoltaic systems have become an interesting solution. Precisely, PV systems are constituted from arrays of photovoltaic cells, choppers (mainly buck-boost or boost DC/DC converter), MPPT control systems and storage devices and/or grid connections. To improve the efficiency of such systems, various studies have been performed. The demand of PV generation systems seems to be increased for both standalone and grid-connected modes of PV systems. Therefore, an efficient maximum power point tracking (MPPT) technique is necessary to initialize the process of tracking the maximum power point MPP at all environmental conditions and then force the PV system to operate at that MPP point.


Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 816 ◽  
Author(s):  
Jae-Sub Ko ◽  
Jun-Ho Huh ◽  
Jong-Chan Kim

This paper presents an overview of the maximum power point tracking (MPPT) methods for photovoltaic (PV) systems used in the Micro Grids of PV systems. In the PV system, the output varies nonlinearly with temperature and radiation, and the point at which power is maximized appears accordingly. The MPPT of the PV system can improve output by about 25%, and it is very important to operate at this point at all times. Various methods of tracking the MPP of the PV system have been studied and proposed. In this paper, we discuss commonly used methods for the MPPT of PV systems, methods using artificial intelligence control, and mixed methods, and present the characteristics, advantages, and disadvantages of each method.


2013 ◽  
Vol 648 ◽  
pp. 311-314
Author(s):  
Xu Dong Guo ◽  
Jian Yang ◽  
Mi Dong ◽  
Mei Su ◽  
Qun Tai Shen

Maximum power point tracking (MPPT) control could significantly increase the overall reliability and conversion efficiency of grid-connected photovoltaic (PV) systems, so it can reduce energy loss in the photoelectric conversion. In this paper, a new MPPT (Zero Average Incremental Conductance) control algorithm is proposed. This method has the advantages of traditional IncCond MPPT. Moreover, it is stable against interference and not sensitive to system models. Therefore the proposed algorithm could be available and widely used in practical MPPT systems. A 200W grid-connected PV system prototype is built in lab. Experiment results verify the effectiveness of the proposed MPPT method.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7453
Author(s):  
Maria I. S. Guerra ◽  
Fábio M. Ugulino de Araújo ◽  
Mahmoud Dhimish ◽  
Romênia G. Vieira

Classic and intelligent techniques aim to locate and track the maximum power point of photovoltaic (PV) systems, such as perturb and observe (P&O), fuzzy logic (FL), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFISs). This paper proposes and compares three intelligent algorithms for maximum power point tracking (MPPT) control, specifically fuzzy, ANN, and ANFIS. The modeling of a single-diode equivalent circuit-based 3 kWp PV plant was developed and validated to achieve this purpose. Then, the MPPT techniques were designed and applied to control the buck–boost converter’s switching device of the PV plant. All three methods use the ambient conditions as input variables: solar irradiance and ambient temperature. The proposed methodology comprises the study of the dynamic response for tracking the maximum power point and the power generated of the PV systems, and it was compared to the classic P&O technique under varying ambient conditions. We observed that the intelligent techniques outperformed the classic P&O method in tracking speed, tracking accuracy, and reducing oscillation around the maximum power point (MPP). The ANN technique was the better control algorithm in energy gain, managing to recover up to 9.9% power.


2020 ◽  
pp. 1-11
Author(s):  
Mahmoud N. Ali

Abstract This paper proposes a novel algorithm to combine two or more techniques of maximum power point tracking (MPPT) to increase the output dc power and the efficiency of photovoltaic (PV) arrays. Different MPPT methods have dissimilar responses for the same environmental circumstances. The combination of multiple methods has the advantage of ever acquiring maximum power as the environmental conditions change. The proposed algorithm is used for enhanced selection of the best suitable duty cycle of the combined methods, based on the power-voltage characteristics, to get the best tracking response. Multiple classical and/or artificial intelligence (AI) based MPPT methods can be combined based on this selection algorithm. To demonstrate its effectiveness, two examples are illustrated. The first one is the combination of two classical MPPT methods, which are the incremental conductance (INC) and the perturb-and-observe (P&O). The second example is to combine two AI based MPPT, which are the artificial neural network (ANN) and the fuzzy logic control (FLC). The simulation results of the application of the proposed algorithm to a grid-connected PV system model justify its capability to acquire better static and dynamic responses than the combined MPPT methods.


Author(s):  
Imad A. Elzein ◽  
Yuri N. Petrenko

In this article an extended literature surveying review is conducted on a set of comparative studies of maximum power point tracking (MPPT) techniques.  Different MPPT methods are conducted with an ultimate aim of how to be maximizing the PV system output power by tracking Pmax in a set of different operational circumstances. In this paper maximum power point tracking, MPPT techniques are reviewed on basis of different parameters related to the design simplicity and or complexity, implementation, hardware required, and other related aspects.


Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2521
Author(s):  
Alfredo Gil-Velasco ◽  
Carlos Aguilar-Castillo

There are multiples conditions that lead to partial shading conditions (PSC) in photovoltaic systems (PV). Under these conditions, the harvested energy decreases in the PV system. The maximum power point tracking (MPPT) controller aims to harvest the greatest amount of energy even under partial shading conditions. The simplest available MPPT algorithms fail on PSC, whereas the complex ones are effective but require high computational resources and experience in this type of systems. This paper presents a new MPPT algorithm that is simple but effective in tracking the global maximum power point even in PSC. The simulation and experimental results show excellent performance of the proposed algorithm. Additionally, a comparison with a previously proposed algorithm is presented. The comparison shows that the proposal in this paper is faster in tracking the maximum power point than complex algorithms.


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