Maximum Power Point Tracking Control for Photovoltaic System Using Neural Fuzzy

Putri, Ratna Ika; Rifai, Mohammed B.

doi:10.7763/ijcee.2012.v4.454

Cited by 13 publications

(7 citation statements)

References 4 publications

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“…At present worldwide have an energy crisis so that renewable energy is a necessary solution to conventional resources problems [1]. Photovoltaic (PV) energy is highly recommended in electrical power applications.…”

Section: Introductionmentioning

confidence: 99%

VHDL Based Maximum Power Point Tracking of Photovoltaic Using Fuzzy Logic Control

Atia¹,

Tolba²

2017

IJECE

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It is important to have an efficient maximum power point tracking (MPPT) technique to increase the photovoltaic (PV) generation system output efficiency. This paper presents a design of MPPT techniques for PV module to increase its efficiency. Perturb and Observe method (P&O), incremental conductance method (IC), and Fuzzy logic controller (FLC) techniques are designed to be used for MPPT. Also FLC is built using MATLAB/ SIMULINK and compared with the FLC toolbox existed in the MATLAB library. FLC does not need knowledge of the exact model of the system so it is easy to implement. A comparison between different techniques shows the effectiveness of the fuzzy logic controller techniques. Finally, the proposed FLC is built in very high speed integrated circuit description language (VHDL). The simulation results obtained with ISE Design Suite 14.6 software show a satisfactory performance with a good agreement compared to obtained values from MATLAB/SIMULINK. The good tracking efficiency and rapid response to environmental parameters changes are adopted by the simulation results.

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Section: Introductionmentioning

confidence: 99%

VHDL Based Maximum Power Point Tracking of Photovoltaic Using Fuzzy Logic Control

Atia¹,

Tolba²

2017

IJECE

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“…In the meantime, optimizing delivery of electrical power from the PV system to the utility grid is done by inverter control. Currently, the study of MPPT control to maximize the power output of the PV has grown rapidly [1][2][3][4]. The Perturb-and-Observe (P&O) method has been developed by K. Chomsuwan et al (1995) The inverter control is required by the PV system to optimize the delivery of power to the utility grid.…”

Section: Introductionmentioning

confidence: 99%

Optimization Active and Reactive Power Flow for PV Connected to Grid System Using Newton Raphson Method

et al. 2015

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The application of solar power plants connected to the utility grid could be one solution in reducing the use of fossil fuels as primary energy power plants.Currently, the use of solar energy to supply electricity on the on-grid area is growing rapidly. This paper proposes a simple method to optimize the power delivery of photovoltaic (PV) system to the utility grid. Two variables, the inverter output voltage V int and power angle , is determined from the roots of two simultaneous Eq., active and reactive power in order to find the maximum and minimum reactive power. Newton Raphson method used to solve the roots of the two Eq. simultaneously. The value of V int corresponding to the root equation is done by adjusting the amplitude modulation of the inverter.Hence, the set is done by shifting the phase angle of the reference wave of the inverter. In this model, 10 PV modules type of ND T060M1 with a 60 Wp capacity are used. The simulation results using SIMULINK-MATLAB have a pretty good performance. The voltage at the PCC point has reached its stable value at 220Volt . Simulation results have shown the maximum value of the active power system at 1000 W/m 2 irradiation was 408 W, as the reactive power is needed only 11. 82 Var. The solar power can work in a power factor approaching unity with the application of the proposed method is suggested.

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“…There are many MPPT techniques could be found in literatures: Perturb and Observe (P & O) [4][5][6]; Incremental Conductance (IC) [7]; Fuzzy Logic [8], [9]; and Artificial Neural Network [10], [11]. The P&O method is widely used because of the simplicity and easy to be implemented.…”

Section: Introductionmentioning

confidence: 99%

“…A Digital Signal Processor (DSP) module was employed in [5] and [9]. Software modeling was used in [7], [8], [10], [11]. There are two different approaches on software modeling: circuit model and equation model.…”

Section: Introductionmentioning

confidence: 99%