Direct Download Real time implementation of artificial neural networks-based controller for battery storage supported wind electric generation - {Dubstowel} torrent

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Abstract:
Energy storage systems have established their capability to overcome the problems caused by intermittent nature of renewable sources when integrated to existing grid. Voltage and frequency control, as well as load shifting can be done using grid level storage systems incorporated with renewable sources. They can effectively serve the system as an energy sink and source. Operational use of energy storage for grid level support of a wind electric generator (WEG) is demonstrated in this study. The battery storage supported WEG along with controllers is modelled. Artificial neural network controller, which is having inherent learning capability, is developed to regulate the power flow between wind generator and utility grid. The proposed algorithm and the corresponding controller are simulated in MATLAB/Simulink and implemented in the DSP processor. The real time data exchange between Simulink and the floating point DSP processor TMSF32028335 is realised using on-board JTAG emulator. The hardware implementation using DSP processor presented in this work establishes the efficacy of the proposed control strategy for real time applications. [ABSTRACT FROM AUTHOR]
How to Cite:
APA:
Kurian, S., Krishnan, S. T., & Cheriyan, E. P. (2015). Real time implementation of artificial neural networks-based controller for battery storage supported wind electric generation. IET Generation, Transmission & Distribution, 9(10), 937-946. doi:10.1049/iet-gtd.2014.0544
AMA:
Kurian S, Krishnan S, Cheriyan E. Real time implementation of artificial neural networks-based controller for battery storage supported wind electric generation. IET Generation, Transmission & Distribution [serial online]. October 2015;9(10):937-946. Available from: Academic Search Complete, Ipswich, MA. Accessed November 15, 2015.
Harvard:
Kurian, S, Krishnan, S, & Cheriyan, E 2015, 'Real time implementation of artificial neural networks-based controller for battery storage supported wind electric generation', IET Generation, Transmission & Distribution, 9, 10, pp. 937-946, Academic Search Complete, EBSCOhost, viewed 15 November 2015.
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