Extremum Seeking for Plants with a Time-Varying Disturbance: Application to Photovoltaic Maximum Power Point Tracking

Michelle A. Kehs, Hosam K. Fathy

Research output: Contribution to journalArticle

Abstract

This paper presents an extremum seeking controller for photovoltaic maximum power point tracking (MPPT). The controller belongs to the broad family of "perturb and observe" algorithms, where the terminal voltage of a photovoltaic system is adjusted to maximize its output power. One critical challenge with these algorithms is that it can be difficult to distinguish between changes in photovoltaic power resulting from changes in irradiation versus the control input. With regard to this challenge, we develop an extremum seeking algorithm that uses least-squares estimation to explicitly separate the effect of the control input from the effect of time-varying disturbances. While the use of least-squares estimation in the context of extremum seeking is not new, our separation of time-varying effects is. In addition, our formulation retains much of the structure of traditional extremum seeking, thereby allowing us to perform a stability analysis comparable to the existing literature. This stability analysis assumes the time-varying disturbance to be slow, but we test the controller beyond this limit in simulation for photovoltaic MPPT. We compare our controller to two benchmarks (a similar controller that does not separate time-varying effects and a traditional extremum seeking controller), and our controller outperforms both.

LanguageEnglish (US)
Article number011011
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume141
Issue number1
DOIs
StatePublished - Jan 1 2019

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range (extremes)
controllers
disturbances
Controllers
Irradiation
formulations
irradiation
output
Electric potential
electric potential
simulation

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

Cite this

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title = "Extremum Seeking for Plants with a Time-Varying Disturbance: Application to Photovoltaic Maximum Power Point Tracking",
abstract = "This paper presents an extremum seeking controller for photovoltaic maximum power point tracking (MPPT). The controller belongs to the broad family of {"}perturb and observe{"} algorithms, where the terminal voltage of a photovoltaic system is adjusted to maximize its output power. One critical challenge with these algorithms is that it can be difficult to distinguish between changes in photovoltaic power resulting from changes in irradiation versus the control input. With regard to this challenge, we develop an extremum seeking algorithm that uses least-squares estimation to explicitly separate the effect of the control input from the effect of time-varying disturbances. While the use of least-squares estimation in the context of extremum seeking is not new, our separation of time-varying effects is. In addition, our formulation retains much of the structure of traditional extremum seeking, thereby allowing us to perform a stability analysis comparable to the existing literature. This stability analysis assumes the time-varying disturbance to be slow, but we test the controller beyond this limit in simulation for photovoltaic MPPT. We compare our controller to two benchmarks (a similar controller that does not separate time-varying effects and a traditional extremum seeking controller), and our controller outperforms both.",
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