A neural fuzzy based maximum power point tracker for a photovoltaic system

Otieno, Christopher A.; Nyakoe, George N.; Wekesa, Cyrus Wabuge

doi:10.1109/afrcon.2009.5308552

Cited by 35 publications

(21 citation statements)

References 8 publications

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“…In Taiwan's subtropical outdoor environment, the average solar radiation and temperature are approximately 0.20 -0.80 kW/m 2 and 30 -40°C, respectively, during the summer season. For various radiation and temperature values, the MPPT algorithm [1][2][3][18][19] can be employed to control the DC-DC boost converter until the desired MOP and output voltage is reached. In this study, an ICM based method [1,3] is used to estimate the desired output and adjust the boost converter's duty ratio to match the maximum point.…”

Section: Resultsmentioning

confidence: 99%

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

Chang¹,

Pai²,

Chou³

et al. 2018

Preprint

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Abstract: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 are parameterized to quantify the degradation between maximum power and metered output power. Bidirectional hetero-associative memory (BHAM) networks are then used to locate multiple faults within the entire PV field. For a rooftop PV system with two strings, experimental results demonstrate that the proposed model has computational efficiency for real-time applications and that its algorithm is easily implemented in a mobile intelligent vehicle.

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Section: Resultsmentioning

confidence: 99%

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

Chang¹,

Pai²,

Chou³

et al. 2018

Preprint

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“…These factors directly relate to the duty ratio adjustment of the dc/dc converter. Since conventional MPPT algorithms are unable to meet those requirements (Otieno et al, 2009;Yu, 2007), adaptive MPPT approaches have been proposed recently, including fuzzy logic based MPPT (Veerachary et al, 2003;Khaehintung et al, 2004), neural networks MPPT (Hussein et al, 2002;Sun et al, 2002) and ripple correlation control MPPT (Midya et al, 1996), etc. All of them basically belong to a "discrete" adaptive MPPT technique.…”

Section: Fast and Reliable Adaptive Mppt Techniquesmentioning

confidence: 99%

Fast and Robust Maximum Power Point Tracking for Solar Photovoltaic Systems

Zheng¹,

Li²

2016

American Journal of Engineering and Applied Sciences

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Solar Photovoltaic (PV) energy is becoming an increasingly important part of the world's renewable energy. In order to develop technology for efficient energy conversion from a solar PV system, this paper studies typical Maximum Power Point Tracking (MPPT) control techniques used in solar PV industry and then proposes a close-loop and adaptive MPPT method for reliable and rapid extraction of solar PV power. The paper emphasizes especially on how the proposed and conventional adaptive MPPT methods perform under highly variable weather and solar irradiation conditions in a digital control environment. A computer simulation system is developed by using SimPowerSystems and Opal-RT real-time simulation technology which allows for fast and efficient investigations of the MPPT algorithms under high switching frequency conditions for power converters. A hardware experiment system is built to validate and compare the proposed and conventional MPPT techniques in a more practical condition. Advantages, disadvantages and properties of different MPPT methods are compared and studied, evaluated.

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“…In addition, ANFIS can generate the fuzzy rules automatically. Various ANFIS-based MPPT methods have been proposed to achieve MPPT [20][21][22][23][24]. The input variables and the output variables are different from one configuration to another.…”

Section: Introductionmentioning

confidence: 99%

“…The disadvantage of this method is that the need for interrupting the PV system to measure the open circuit voltage and need to short circuit the PV module terminals to measure the short circuit current, which finally increases the system losses. Some other papers use the solar radiation and temperature as input variables, and the output variable is the voltage at maximum power (V MPP ) or the maximum power itself (P MPP ) [21,23,24]. However, measuring irradiance level by solar radiation sensor is not the exact solar radiation incident on the PV module since the aging of the PV modules as well as the partial shading is not taken into considerations.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Practical Implementation of ANFIS-Based MPPT Method for PV Applications Using Isolated Ćuk Converter

Noman

Addoweesh

Alolah

2017

International Journal of Photoenergy

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Photovoltaic (PV) module behavior is not linear in nature with respect to environmental conditions and hence exhibits nonlinear PV curves. There is only a single point in the nonlinear PV curve at which the power is maximum. Therefore, special methods have been proposed to track this maximum power point (MPP). This paper proposed an intelligent method for MPP tracking (MPPT) based on adaptive neuro-fuzzy inference system (ANFIS) controller. The proposed system consists of a PV module connected to a DC-DC isolated Ćuk converter and load. A MATLAB/SIMULINK-based MPPT model is built to test the behavior of the proposed method. The proposed method is tested under different weather scenarios. Simulation results exhibit the successful tracking of the proposed method under all ambient conditions. Comparison of the tracking behavior of the proposed method with the perturb and observe method is also presented in the simulation results. In addition, a 220 W prototype with the help of dSPACE 1104 data acquisition system is built and tested under practical weather conditions on a sunny day as well as on a cloudy day. Experimental results are presented to verify the effectiveness of the proposed method. These results exhibit satisfactory performance under different practical weather conditions.

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A neural fuzzy based maximum power point tracker for a photovoltaic system

Cited by 35 publications

References 8 publications

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

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

Fast and Robust Maximum Power Point Tracking for Solar Photovoltaic Systems

Simulation and Practical Implementation of ANFIS-Based MPPT Method for PV Applications Using Isolated Ćuk Converter

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