RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell

H. R. Kamath; A. K. Goswami; Aditya Kumar; R. S. Aithal; P. K. Singh

RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell

H. R. Kamath^*
, A. K. Goswami
, Aditya Kumar
, R. S. Aithal
, P. K. Singh

^*Corresponding author for this work

International Centre for Applied Sciences, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A Maximum power point tracking (MPPT) allows the photovoltaic module to operate at its maximum power point. It is done using a converter that regulates the power that is drawn from the converter. By varying the duty cycle of the switches, the energy transferred through the converter can be precisely controlled. This paper deals with simulation of estimator for a digital tracking system used for simulation of maximum power point PV tracker using KALMAN Filter. For the simulation Back-Propagation and Radial Basis Network are used as Artificial Neural Network (ANN) tool. The objective of this paper is to discuss the use of KALMAN filter as an estimator in the area of photovoltaic cell power tracking.

Original language	English
Title of host publication	IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011
Pages	1006-1011
Number of pages	6
Volume	2
Publication status	Published - 2011
Event	International MultiConference of Engineers and Computer Scientists 2011, IMECS 2011 - Kowloon, Hong Kong Duration: 16-03-2011 → 18-03-2011

Publication series

Name	IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011
Volume	2

Conference

Conference	International MultiConference of Engineers and Computer Scientists 2011, IMECS 2011
Country/Territory	Hong Kong
City	Kowloon
Period	16-03-11 → 18-03-11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

General Computer Science
General Engineering

Cite this

Kamath, H. R., Goswami, A. K., Kumar, A., Aithal, R. S., & Singh, P. K. (2011). RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell. In IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011 (Vol. 2, pp. 1006-1011). (IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011; Vol. 2).

@inproceedings{0e6be6b48f114eef801cae14e11c6737,

title = "RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell",

abstract = "A Maximum power point tracking (MPPT) allows the photovoltaic module to operate at its maximum power point. It is done using a converter that regulates the power that is drawn from the converter. By varying the duty cycle of the switches, the energy transferred through the converter can be precisely controlled. This paper deals with simulation of estimator for a digital tracking system used for simulation of maximum power point PV tracker using KALMAN Filter. For the simulation Back-Propagation and Radial Basis Network are used as Artificial Neural Network (ANN) tool. The objective of this paper is to discuss the use of KALMAN filter as an estimator in the area of photovoltaic cell power tracking.",

author = "Kamath, \{H. R.\} and Goswami, \{A. K.\} and Aditya Kumar and Aithal, \{R. S.\} and Singh, \{P. K.\}",

year = "2011",

language = "English",

isbn = "9789881925121",

volume = "2",

series = "IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011",

pages = "1006--1011",

booktitle = "IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011",

note = "International MultiConference of Engineers and Computer Scientists 2011, IMECS 2011 ; Conference date: 16-03-2011 Through 18-03-2011",

}

Kamath, HR, Goswami, AK, Kumar, A, Aithal, RS & Singh, PK 2011, RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell. in IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011. vol. 2, IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011, vol. 2, pp. 1006-1011, International MultiConference of Engineers and Computer Scientists 2011, IMECS 2011, Kowloon, Hong Kong, 16-03-11.

RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell. / Kamath, H. R.; Goswami, A. K.; Kumar, Aditya et al.
IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011. Vol. 2 2011. p. 1006-1011 (IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell

AU - Kamath, H. R.

AU - Goswami, A. K.

AU - Kumar, Aditya

AU - Aithal, R. S.

AU - Singh, P. K.

PY - 2011

Y1 - 2011

N2 - A Maximum power point tracking (MPPT) allows the photovoltaic module to operate at its maximum power point. It is done using a converter that regulates the power that is drawn from the converter. By varying the duty cycle of the switches, the energy transferred through the converter can be precisely controlled. This paper deals with simulation of estimator for a digital tracking system used for simulation of maximum power point PV tracker using KALMAN Filter. For the simulation Back-Propagation and Radial Basis Network are used as Artificial Neural Network (ANN) tool. The objective of this paper is to discuss the use of KALMAN filter as an estimator in the area of photovoltaic cell power tracking.

AB - A Maximum power point tracking (MPPT) allows the photovoltaic module to operate at its maximum power point. It is done using a converter that regulates the power that is drawn from the converter. By varying the duty cycle of the switches, the energy transferred through the converter can be precisely controlled. This paper deals with simulation of estimator for a digital tracking system used for simulation of maximum power point PV tracker using KALMAN Filter. For the simulation Back-Propagation and Radial Basis Network are used as Artificial Neural Network (ANN) tool. The objective of this paper is to discuss the use of KALMAN filter as an estimator in the area of photovoltaic cell power tracking.

UR - https://www.scopus.com/pages/publications/79960602224

UR - https://www.scopus.com/pages/publications/79960602224#tab=citedBy

M3 - Conference contribution

AN - SCOPUS:79960602224

SN - 9789881925121

VL - 2

T3 - IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011

SP - 1006

EP - 1011

BT - IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011

T2 - International MultiConference of Engineers and Computer Scientists 2011, IMECS 2011

Y2 - 16 March 2011 through 18 March 2011

ER -

RBF and BPNN combi model based KALMAN filter application for maximum power point tracker of PV cell

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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Cite this