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    Maximum power point tracking using hybrid fuzzy based p&o and back propagation (BP) neural network for photovoltaic system
    (2014-10-01)
    Konghuayrob, Poom
    ;
    Kaitwanidvilai, Somyot
    Photovoltaic system is one of the most popular renewable energy sources to solve the problem of energy crisis. The important problem of solar PV systems is their low efficiency and nonlinear output characteristics in the changing weather that causes the difficulty in tracking of maximum power. To overcome this problem, this paper proposes “Hybrid Fuzzy based P&O and Back Propagation (BP) neural network” for improving the efficiency and reducing the power oscillation of PV system. The proposed system composes of two parts which are fuzzy based P&O and Neural Network. The fuzzy based P&O is used to find the maximum power point (MPP) while the neural network is used to find the appropriate modulation index (ma). The proposed algorithm is adopted in the AC module flyback inverter in which modulation index (Δma) is used as the control variable to track the MPP of the PV array. Simulation results verify that the proposed technique can effectively track the power from PV system, and is better than the conventional P&O techniques
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    A novel fuzzy logic control technique tuned by particle swarm optimization for maximum power point tracking for a photovoltaic system using a current-mode boost converter with bifurcation control
    (2010-04-01)
    Khaehintung, Noppadol
    ;
    Kunakorn, Anantawat
    ;
    Sirisuk, Phaophak
    This paper presents a novel fuzzy logic control technique tuned by particle swarm optimization (PSO-FLC) for maximum power point tracking (MPPT) for a photovoltaic (PV) system. The proposed PV system composes of a current-mode boost converter (CMBC) with bifurcation control. An optimal slope compensation technique is used in the CMBC to keep the system adequately remote from the first bifurcation point in spite of nonlinear characteristics and instabilities of this converter. The proposed PSO technique allows easy and more accurate tuning of FLC compared with the trialand-error based tuning. Consequently, the proposed PSO-FLC method provides faster tracking of maximum power point (MPP) under varying light intensities and temperature conditions. The proposed MPPT technique is simple and particularly suitable for PV system equipped with CMBC Experimental results are shown to confirm superiority of the proposed technique comparing with the conventional PVVC technique and the trial-and-error based tuning FLC. © ICROS, KIEE and Springer 2010.
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    Grid-connected photovoltaic system with maximum power point tracking using self-organizing fuzzy logic controller
    (2005-12-01)
    Khaehintung, Noppadol
    ;
    Kangsajian, Chaiboon
    ;
    Sirisuk, Phaophak
    ;
    Kunakorn, Anatawat
    This paper presents the design of a controller for the maximum power point tracking of a grid-connected photovoltaic energy conversion system. A boost converter is used in the system to deliver the output from the solar array to DC-AC inverter, and feed the power into the AC grid. A self-organizing fuzzy logic controller is introduced for the tracking algorithm. The duty ratio for the operation of the boost converter is optimally adjusted in such a way that the maximum power point, which normally varies according to the environment, can be achieved. We demonstrate via the simulation results that our proposed technique outperforms over the conventional fuzzy logic controller in terms of tracking speed and transient response. Furthermore, the algorithm implementation can be done using a look-up table, hence a high-performance, cost-effective real-time maximum power point tracking can be simply realized. © 2005 IEEE.