Maximum Power Point Tracking Based on SVR and GA

2014 ◽  
Vol 687-691 ◽  
pp. 3231-3234
Author(s):  
Zhi Guang Tian ◽  
Lin Tian ◽  
Jian He ◽  
Zhen Hua Huang ◽  
Da Hai Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Support Vector ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Best Parameters

With the increasing application of Photovoltaic (PV) power system, it is important to make PV system always achieve its maximum power output, so maximum power point tracking (MPPT) technique develops. Based on Support Vector Regression (SVR) and Genetic Algorithm (GA), a novel MPPT method is proposed in this paper. The SVR model uses the solar radiation and temperature as two inputs, and uses the voltage at maximum power point (MPP) as output. Furthermore, GA is introduced to search the best parameters for SVR. Results validate the effectiveness of the proposed MPPT method.

scholarly journals Maximum Power Point Tracking for a PV System Using Tuned Support Vector Regression by Particle Swarm Optimization

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
Ahmed G. Abo-Khalil ◽  
◽  
Keyword(s):  
Support Vector Regression ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Support Vector ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The photovoltaic (PV) system is always operated at the maximum power point (MPP) condition irrespective of the fluctuations in PV voltage. The maximum power point tracking (MPPT) employed in PV system is not effective during the presence of current ripple as normal tracking becomes increasingly complex during fluctuation in solar irradiation or due to change in MPP condition. This paper proposes a high-efficiency power point tracking algorithm to minimize the current ripple and power oscillation around the maximum power point. The developed algorithm is based on particle swarm optimization-support vector regression (PSO-SVR) technique. The proposed algorithm is implemented to select and tune the Support Vector Regression (SVR) parameters such as kernel parameters, variance, and the penalty factor for predicting the irradiation level as well as to determine the PV voltage corresponding of maximum power point. The PSO method is used to accelerate the process of optimizing the SVR parameters at different conditions and get knowledge about the corresponding global optimum. From the experimental results,the efficiency of maximum power point tracking is found to be 99.8%. The proposed algorithm PSO-SVR shows a better performance than using SVR alone. The stability and accuracy of MPPT have been validated during the rapid fluctuation of solar irradiation in the range of 25% to 100%.

Assessing Under Varying Circumstances the Behavior of Photovoltaic Systems of Maximum Power Point Methods.

2019 ◽  
Vol 1 (2) ◽  
pp. 45-51
Author(s):  
Imad A. Elzein ◽  
Yuri N. Petrenko
Keyword(s):  
Comparative Studies ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
System Output ◽  
Power Point ◽  
Design Simplicity

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.

Maximum Power Point Tracking (MPPT) for a Solar Photovoltaic System: A Review

2015 ◽  
Vol 787 ◽  
pp. 227-232 ◽  
Author(s):  
L.A. Arun Shravan ◽  
D. Ebenezer
Keyword(s):  
Solar Energy ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Nonlinear Behaviour ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

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.

A brief overview of maximum power point tracking algorithm for solar PV system

2021 ◽  
Author(s):  
C. Pavithra ◽  
Pooja Singh ◽  
Venkatesa Prabhu Sundramurthy ◽  
T.S. Karthik ◽  
P.R. Karthikeyan ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Tracking Algorithm ◽  
Maximum Power ◽  
Solar Pv ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Solar Pv System ◽  
Power Point

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

2013 ◽  
Author(s):  
Yan Xiao ◽  
Yaoyu Li ◽  
John E. Seem ◽  
Kaushik Rajashekara
Keyword(s):  
Stochastic Approximation ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Simultaneous Perturbation Stochastic Approximation ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

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.

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