Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control

Steven L. Brunton; Clarence W. Rowley; Sanjeev R. Kulkarni; Charles Clarkson

doi:10.1109/TPEL.2010.2049747

Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control

Steven L. Brunton, Clarence W. Rowley, Sanjeev R. Kulkarni, Charles Clarkson

Research output: Contribution to journal › Article › peer-review

288 Scopus citations

Abstract

This study develops a maximum power point tracking algorithm that optimizes solar array performance and adapts to rapidly varying irradiance conditions. In particular, a novel extremum seeking (ES) controller that utilizes the natural inverter ripple is designed and tested on a simulated solar array with a grid-tied inverter. The new algorithm is benchmarked against the perturb and observe (PO) method using high-variance irradiance data gathered on a rooftop array experiment in Princeton, NJ. The ES controller achieves efficiencies exceeding 99% with transient rise-time to the maximum power point of less than 0.1 s. It is shown that voltage control is more stable than current control and allows for accurate tracking of faster irradiance transients. The limitations of current control are demonstrated in an example. Finally, the effect of capacitor size on the performance of ripple-based ES control is investigated.

Original language	English (US)
Article number	5460938
Pages (from-to)	2531-2540
Number of pages	10
Journal	IEEE Transactions on Power Electronics
Volume	25
Issue number	10
DOIs	https://doi.org/10.1109/TPEL.2010.2049747
State	Published - 2010

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Keywords

Current control
DC - AC power conversion
control systems
extremum seeking control
inverters
optimization methods
photovoltaic power systems

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10.1109/TPEL.2010.2049747

Cite this

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title = "Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control",

abstract = "This study develops a maximum power point tracking algorithm that optimizes solar array performance and adapts to rapidly varying irradiance conditions. In particular, a novel extremum seeking (ES) controller that utilizes the natural inverter ripple is designed and tested on a simulated solar array with a grid-tied inverter. The new algorithm is benchmarked against the perturb and observe (PO) method using high-variance irradiance data gathered on a rooftop array experiment in Princeton, NJ. The ES controller achieves efficiencies exceeding 99% with transient rise-time to the maximum power point of less than 0.1 s. It is shown that voltage control is more stable than current control and allows for accurate tracking of faster irradiance transients. The limitations of current control are demonstrated in an example. Finally, the effect of capacitor size on the performance of ripple-based ES control is investigated.",

keywords = "Current control, DC - AC power conversion, control systems, extremum seeking control, inverters, optimization methods, photovoltaic power systems",

author = "Brunton, {Steven L.} and Rowley, {Clarence W.} and Kulkarni, {Sanjeev R.} and Charles Clarkson",

note = "Funding Information: Mr. Brunton is the recipient of a Gordon Wu Fellowship Award. Funding Information: Manuscript received December 14, 2009; revised February 22, 2010, March 8, 2010, March 22, 2010, and April 13, 2010; accepted April 25, 2010. Date of current version September 17, 2010. This work was supported by the New Jersey Commission on Science and Technology. Recommended for publication by Associate Editor K. Ngo.",

year = "2010",

doi = "10.1109/TPEL.2010.2049747",

language = "English (US)",

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AU - Clarkson, Charles

N1 - Funding Information: Mr. Brunton is the recipient of a Gordon Wu Fellowship Award. Funding Information: Manuscript received December 14, 2009; revised February 22, 2010, March 8, 2010, March 22, 2010, and April 13, 2010; accepted April 25, 2010. Date of current version September 17, 2010. This work was supported by the New Jersey Commission on Science and Technology. Recommended for publication by Associate Editor K. Ngo.

PY - 2010

Y1 - 2010

N2 - This study develops a maximum power point tracking algorithm that optimizes solar array performance and adapts to rapidly varying irradiance conditions. In particular, a novel extremum seeking (ES) controller that utilizes the natural inverter ripple is designed and tested on a simulated solar array with a grid-tied inverter. The new algorithm is benchmarked against the perturb and observe (PO) method using high-variance irradiance data gathered on a rooftop array experiment in Princeton, NJ. The ES controller achieves efficiencies exceeding 99% with transient rise-time to the maximum power point of less than 0.1 s. It is shown that voltage control is more stable than current control and allows for accurate tracking of faster irradiance transients. The limitations of current control are demonstrated in an example. Finally, the effect of capacitor size on the performance of ripple-based ES control is investigated.

AB - This study develops a maximum power point tracking algorithm that optimizes solar array performance and adapts to rapidly varying irradiance conditions. In particular, a novel extremum seeking (ES) controller that utilizes the natural inverter ripple is designed and tested on a simulated solar array with a grid-tied inverter. The new algorithm is benchmarked against the perturb and observe (PO) method using high-variance irradiance data gathered on a rooftop array experiment in Princeton, NJ. The ES controller achieves efficiencies exceeding 99% with transient rise-time to the maximum power point of less than 0.1 s. It is shown that voltage control is more stable than current control and allows for accurate tracking of faster irradiance transients. The limitations of current control are demonstrated in an example. Finally, the effect of capacitor size on the performance of ripple-based ES control is investigated.

KW - Current control

KW - DC - AC power conversion

KW - control systems

KW - extremum seeking control

KW - inverters

KW - optimization methods

KW - photovoltaic power systems

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Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control

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Keywords

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