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Maximum power point tracking

About: Maximum power point tracking is a research topic. Over the lifetime, 29012 publications have been published within this topic receiving 484836 citations. The topic is also known as: MPPT & MPP.


Papers
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01 Jan 2015
TL;DR: In this article, the simulation of interleaved boost converter (IBC) with Perturb and Observe (P&O) MPPT for photovoltaic system is analyzed.
Abstract: The output power of Photovoltaic (PV) module/array varies due to the changes in atmospheric conditions and this result in variation of maximum power point (MPP). The Maximum Power Point Tracking (MPPT) algorithms are used for converter control so as to adjust the operating point the converter circuit to transfer the maximum power to the load. This paper presents the simulation of interleaved boost converter (IBC) with Perturb and Observe (P&O) MPPT for Photovoltaic system. The PV power system with a two phase IBC is analyzed in this work. The converter circuit is connected with the generalized photovoltaic model and simulated for various atmospheric conditions with and without MPPT controller. The model is simulated in MATLAB and the results are generated for various test conditions. The output power of the converter with and without MPPT is compared with the actual output power of the PV module and the results are discussed.

10 citations

Patent
28 Oct 2002
TL;DR: In this paper, a wide gap semiconductor having high mobility is used for the DC-DC converter FETs in the inverter system to enhance the efficiency of conversion of energy generated by solar cells.
Abstract: PROBLEM TO BE SOLVED: To provide an inverter system higher in energy conversion efficiency in an energy conversion system for photovoltaic power generation using solar cells or the like. SOLUTION: A wide gap semiconductor having high mobility is used for the DC-DC converter FETs in the inverter system. Thus, the efficiency of conversion of energy generated by solar cells is enhanced. COPYRIGHT: (C)2004,JPO

10 citations

Proceedings ArticleDOI
03 Jun 2013
TL;DR: In this paper, the authors proposed a single stage boost converter with multiple inputs that can efficiently decimate generated energy to charge a battery, which is called Multi-Input-Single Control (MISC) converter.
Abstract: Renewable power and storage have made DC based domestic distribution an attractive alternative for future homes. Due to low power rating of the system, it is very important to reduce number of converter stages and use the generated energy efficiently. Therefore, instead of using different dedicated converters from various uni-directional renewable sources, this paper proposes a single stage boost converter with multiple inputs that can efficiently decimate generated energy to charge a battery. This philosophy of interfacing renewable sources will have commercial value when some of the additional sources are not large enough to mandate a dedicated converter. The converter is called Multi-Input-Single Control (MISC) converter. The converter varies the duty cycle based on optimum operation of the largest power source (e.g., MPP in case of solar panel), where as the other smaller unidirectional sources act as slave. As per the characteristic of the source, the proposed converter works under various operating modes which are discussed in this paper. The concept is validated using a laboratory prototype for different operating scenarios with a solar panel as a master source working under MPPT.

10 citations

Patent
06 Sep 2013
TL;DR: In this article, a method for controlling a sensorless online neural network for a wind power generation control system is provided to apply an online NN adaptive control algorithm for the maximum power point tracking (MPPT) of a wind energy generation system.
Abstract: PURPOSE: A method for controlling a sensorless online neural network for a wind power generation control system is provided to apply an online neural network adaptive control algorithm for the maximum power point tracking (MPPT) of a wind power generation system CONSTITUTION: A method for controlling a sensorless online neural network for a wind power generation control system includes: a step of modeling mechanical power generated by a wind turbine, computing a tip-speed ratio (TSR), calculating torque due to a wind force, computing a wind energy conversion system (WECS) first model equation, and then modeling a nonlinear control equation corresponding to the uncertainty and nonlinearity of a WECS system; and a step of determining an ideal control input through an ideal nonlinear input/output linearization controller, measuring a differential value for an actual wind velocity using a differential estimator, identifying torque due to an unknown wind force through radial-basis function network (RBFN), designing a controller based on the output value of the differential estimator and the ideal control input, selecting Lyapunov function, and then implementing a control algorithm analyzing stability

10 citations

Patent
07 Dec 2006
TL;DR: In this article, a converter for electrical power recovery for supplying power to a load includes an in-house power generation device that supplies power in cooperation with input terminal power at a power input terminal.
Abstract: This converter for electrical power recovery ( 1 ) for supplying power to a load ( 6 ) includes an in-house power generation device ( 5 ) for supplying power in cooperation with input terminal power at a power input terminal ( 2 ). Moreover, it includes a thermal storage unit ( 12 ) which, when surplus power is generated in a state in which a target value for input terminal power is set to zero, thermally stores this power. Furthermore, a control unit ( 9 ) is included which, when surplus power is generated, decides whether or not breakage of a wire of a CT ( 7 ) has occurred by raising the target value for the input terminal power from zero to a predetermined value, and by deciding whether or not the power input terminal current is somewhat elevated from zero.

10 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023967
20222,114
20211,257
20201,633
20191,779
20181,889