MPPT techniques for photovoltaic applications

Eltawil, Mohamed A.; Zhao, Zhengming

doi:10.1016/j.rser.2013.05.022

Cited by 391 publications

(154 citation statements)

References 78 publications

Supporting

Mentioning

151

Contrasting

Unclassified

Order By: Relevance

“…The choice of a PLC in autonomous systems relies on the device's functional ability to operate independently, based on (its own) programming structure, such as the well-known MPPT algorithm, referred to in the literature [12,13].With this in mind, authors would be looking for new control and operational components for PLC interaction [14] II.…”

Section: The Voltage Ratio At Extensive Cloudiness (Averaged Value mentioning

confidence: 99%

A Novel Implementation for efficient PLC based low-power photovoltaic generation plants

Hemavani¹,

Dillibabu²

2017

Nctet-2k17

View full text Add to dashboard Cite

show abstract

Section: The Voltage Ratio At Extensive Cloudiness (Averaged Value mentioning

confidence: 99%

A Novel Implementation for efficient PLC based low-power photovoltaic generation plants

Hemavani¹,

Dillibabu²

2017

Nctet-2k17

View full text Add to dashboard Cite

show abstract

“…Among these techniques, the IC algorithm is the simplest and most effective technique that is used widely. The IC algorithm is the fastest in MPPT under rapid weather changing conditions and the power oscillation is negligible at the maximum power point [22]. For this reason, the IC algorithm method is used in this work.…”

Section: Pv Array Modelmentioning

confidence: 99%

A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System

et al. 2017

View full text Add to dashboard Cite

Solar power generation is intermittent in nature. It is nearly impossible for a photovoltaic (PV) system to supply power continuously and consistently to a varying load. Operating a controllable source like a fuel cell in parallel with PV can be a solution to supply power to variable loads. In order to coordinate the power supply from fuel cells and PVs, a power management system needs to be designed for the microgrid system. This paper presents a power management system for a grid-connected PV and solid oxide fuel cell (SOFC), considering variation in the load and solar radiation. The objective of the proposed system is to minimize the power drawn from the grid and operate the SOFC within a specific power range. Since the PV is operated at the maximum power point, the power management involves the control of SOFC active power where a proportional and integral (PI) controller is used. The control parameters of the PI controller K p (proportional constant) and T i (integral time constant) are determined by the genetic algorithm (GA) and simplex method. In addition, a fuzzy logic controller is also developed to generate appropriate control parameters for the PI controller. The performance of the controllers is evaluated by minimizing the integral of time multiplied by absolute error (ITAE) criterion. Simulation results showed that the fuzzy-based PI controller outperforms the PI controller tuned by the GA and simplex method in managing the power from the hybrid source effectively under variations of load and solar radiation.

show abstract

“…Due to nonlinear I-V and P-V characteristics of the PV array, the MPPT becomes more challenging. Such non-linear and non-minimum phase characteristics further confuse the MPPT of the boost converter [5]. To overcome these problems, different conventional and intelligent MPPT algorithms have been proposed such as Incremental Conductance (IC) [6][7][8], Open Circuit Voltage (OCV) [9], Short Circuit Current (SCC) [10], Perturb and Observe (P&O) [11], fuzzy logic [12][13][14][15], feedback linearization [16], neural network [17][18][19][20][21][22], neuro-fuzzy [23][24][25] and sliding mode [26,27].…”

Section: Introductionmentioning

confidence: 99%

Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Hassan

Kamal

et al. 2017

Energies

View full text Add to dashboard Cite

An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT) techniques, a high performance neuro-fuzzy indirect wavelet-based adaptive MPPT control is developed in this work. The proposed controller combines the reasoning capability of fuzzy logic, the learning capability of neural networks and the localization properties of wavelets. In the proposed system, the Hermite Wavelet-embedded Neural Fuzzy (HWNF)-based gradient estimator is adopted to estimate the gradient term and makes the controller indirect. The performance of the proposed controller is compared with different conventional and intelligent MPPT control techniques. MATLAB results show the superiority over other existing techniques in terms of fast response, power quality and efficiency.

show abstract

MPPT techniques for photovoltaic applications

Cited by 391 publications

References 78 publications

A Novel Implementation for efficient PLC based low-power photovoltaic generation plants

A Novel Implementation for efficient PLC based low-power photovoltaic generation plants

A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System

Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Contact Info

Product

Resources

About