Effective supervisory controller to extend optimal energy management in hybrid wind turbine under energy and reliability constraints View Full Text


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Article Info

DATE

2018-03

AUTHORS

Billel Meghni, Djalel Dib, Ahmad Taher Azar, Abdallah Saadoun

ABSTRACT

One of the major factors that can increase the efficiency of wind turbines (WTs) is the simultaneous control of the different parts in several operating area. The main problem associated with control design in wind generator is the presence of asymmetric in the dynamic model of the system, which makes a generic supervisory control scheme for the power management of WT complicated. Consequently, supervisory controller can be utilized as the main building block of a wind farm controller (offshore), which meets the grid code requirements and can increased the efficiency and protection of WTs in (region II and III) at the same time. This paper proposes a new effective adaptive supervisory controller for the optimal management and protection simultaneously of a hybrid WT, in both regions (II and III). To this end, the second order sliding mode with the adaptive gain super-twisting control law and fuzzy logic control are used in the machine side, batteries side and grid side converters, to achieve four control objectives: (1) control of the rotor speed to track the optimal value; (2) adaptive control (commutative mode) in order to maximum power point tracking (MPPT) or power limit in various regions; (3)regulate the average DC link voltage near to its nominal value;(4) ensure: a smooth regulation with high quality of power supply injected into the grid, a satisfactory power factor correction and a high harmonic performance in relation to the AC source and eliminating the chattering effect. Results of extensive simulation studies prove that the proposed supervisory control system guarantees to track reference signals with a high harmonic performance despite external disturbance uncertainties. More... »

PAGES

369-383

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s40435-016-0296-0

    DOI

    http://dx.doi.org/10.1007/s40435-016-0296-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1007660895


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