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Title: Optimal condition monitoring of wind turbines using intelligent image processing and internet of things

Authors: K. Sujatha; B. Deepalakshmi; Su-Qun Cao

Addresses: Department of Electrical and Electronics Engineering Center for Electronics Automation and Industrial Research (CEAIR), Dr. M.G.R. Educational and Research Institute/Southeast University, Maduravoyal, Chennai, Tamil Nadu, India ' Department of Electrical and Electronics Engineering Center for Electronics Automation and Industrial Research (CEAIR), Dr. M.G.R. Educational and Research Institute/Southeast University, Maduravoyal, Chennai, Tamil Nadu, India ' Department of Electrical and Electronics Engineering Center for Electronics Automation and Industrial Research (CEAIR), Dr. M.G.R. Educational and Research Institute/Southeast University, Maduravoyal, Chennai, Tamil Nadu, India

Abstract: The aim is to suggest a control scheme for the wind mills which convert wind energy to electrical energy. The functioning of the governing scheme is characterised by incorporating it to a doubly fed induction generator (DFIG). The stationary part of the DFIG is unswervingly linked to the electric network. The rotating part is allied to this electric network all the way through a back-to-back AC-DC-AC PWM converter. Fuzzy logic is used to acquire features using decision making logic which as human-like flexibility. The FLC provides a crisp and smooth control action. The governing process of the converter on rotating part is comprehended by stationary magnetic flux to adjust the performance of the fuzzy logic controller (FLC). The FLC is opted to have an intelligent speed control. To enable a level direct current voltage and to guarantee a pure sine wave for the current in the grid side a Grid Side Converter (GSC) is used which is controlled using FLC. The accuracy of the FLC used for the control of DFIG has a quick vibrant retort with almost unsteady error value once evaluated with the scheme using conformist proportional integral (PI) controller. Image processing algorithms are used to track the blade sweep and angular velocity. The entire monitoring is implemented using ATmega processor and incorporated in cloud service for online monitoring.

Keywords: doubly fed induction generator; DFIG; fuzzy logic controller; FLC; power converters; image processing and internet of things; IoT.

DOI: 10.1504/IJRET.2018.090112

International Journal of Renewable Energy Technology, 2018 Vol.9 No.1/2, pp.158 - 180

Available online: 13 Feb 2018 *

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