Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller

By Mummadi Veerachary, Tomonobu Senjyu, K. Uezato. IEEE transactions on industrial electronics (1982. Print), 2003

484 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/a1042102b758a06bcaba212d77a1cd0fe6c72b39

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Citations in the corpus

T-S Fuzzy Maximum Power Point Tracking Control of Solar Power Generation Systems (2010, methodology): “tracking (MPPT), such as perturb-and-observe method [3]–[5], incremental conductance method [6], curve fitting method [7], fuzzy logic methods [8]–[11], neural networks [12]–[ 14 ], etc.”
Reliability Issues in Photovoltaic Power Processing Systems (2008, methodology): “Furthermore, the digital MPPT realizations are characterized by several important advantages such as: 1) sensing/ monitoring of PV as well as environmental quantities becomes easier; 2) possibility to realize adaptive MPPT schemes using fuzzy-neuro concepts [78]‐[ 81 ]; 3) decision making as well as”
Stability study of variable step size incremental conductance/impedance MPPT for PV systems (2011, background): “The subject of MPPT has been lectured in different ways in the literature: examples of fuzzy logic, exteremum seeking, neural network, pilot cells have been proposed in [3] – [5].”
Maximum Power Point Tracking Control of Photovoltaic Systems: A Polynomial Fuzzy Model-Based Approach (2018, methodology): “Conventional MPPT control approaches involve perturb and observe approach [3], an incremental conductance method [8], a maximum power voltage (MPV)-based approach [9], [10], a proportional integral (PI) controller [11], and a fuzzy logic method [12], [13].”
A Variable Step Size INC MPPT Method for PV Systems (2008, methodology): “Moreover, fuzzy and neural network methods [10], [ 11 ] that focus on the nonlinear characteristics of PV array provide a good alternative for the MPPT control.”
Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter (2011, background): “On the other hand, some MPPTs are more rapid and accurate and, thus, more impressive, which need special design and familiarity with specific subjects such as fuzzy logic [20] or neural network [21] methods.”
An Adaptive System for Optimal Solar Energy Harvesting in Wireless Sensor Network Nodes (2008, unknown): “, see [9], [10], [11].”
Efficiency Optimization of a DSP-Based Standalone PV System Using Fuzzy Logic and Dual-MPPT Control (2012, methodology): “Other methods such as the incremental Conductance (INC) technique [28]–[31], the neural network (NN) technique [32]–[34] and fuzzy logic controller technique [35]–[38] have been also widely reported.”
Optimization of Photovoltaic Power Systems (2012, background): “The fill factor is defined as follows FF ¼ PMPP Voc Isc ¼ VMPP:IMPP Voc Isc ð1:10Þ”
Parallel-Connected Solar PV System to Address Partial and Rapidly Fluctuating Shadow Conditions (2009, methodology): “Many MPPT methods have been reported, such as perturb and observe [8]–[12], incremental conductance [13], [14], neural network based [15], [16], fuzzy logic control [17], [18], etc.”