Adaptive and predictive controllers applied to onshore wind energy conversion system

1.
ICT, Universidade de Évora, Évora, Portugal
2.
Departamento de Física, Escola de Ciências e Tecnologia, Universidade de Évora, Portugal
3.
IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
4.
Instituto Superior de Engenharia de Lisboa, Lisboa, Portugal
5.
CISE, Electromechatronic Systems Research Centre, Universidade da Beira Interior, Portugal
6.
INESC-ID, Lisboa, Portugal

Received: 31 May 2018 Accepted: 13 August 2018 Published: 28 August 2018

Abstract
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This paper presents a simulation of onshore energy conversion system connected to the electric grid and under an event-based supervisor control based on deterministic version of a finite state machine. The onshore energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two-mass drive train, a gearbox, a doubly fed induction generator rotor and by a two-level converter. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as adaptive controllers and predictive controllers. The study of an event-based supervisor based on finite state machines is also studied. The control and supervision strategy proposed for the onshore energy conversion system is based on a hierarchical structure with two levels, execution level where the adaptive and predictive controllers are included, and the supervision level where the event-based supervisor is included. The objective is to control the electric output power around the reference power and also to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the onshore energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. A comparison of the onshore energy conversion system performance without or with the supervisor is carried out to access the influence of the control and supervision strategy on the performance.
- adaptive control,
- model predictive control,
- wind energy,
- event-based supervisor,
- performance assessment,
- onshore,
- finite state machine
Citation: Carla Viveiros, Rui Melicio, Victor Mendes, Jose Igreja. Adaptive and predictive controllers applied to onshore wind energy conversion system[J]. AIMS Energy, 2018, 6(4): 615-631. doi: 10.3934/energy.2018.4.615

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Abstract

This paper presents a simulation of onshore energy conversion system connected to the electric grid and under an event-based supervisor control based on deterministic version of a finite state machine. The onshore energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two-mass drive train, a gearbox, a doubly fed induction generator rotor and by a two-level converter. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as adaptive controllers and predictive controllers. The study of an event-based supervisor based on finite state machines is also studied. The control and supervision strategy proposed for the onshore energy conversion system is based on a hierarchical structure with two levels, execution level where the adaptive and predictive controllers are included, and the supervision level where the event-based supervisor is included. The objective is to control the electric output power around the reference power and also to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the onshore energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. A comparison of the onshore energy conversion system performance without or with the supervisor is carried out to access the influence of the control and supervision strategy on the performance.

References

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