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Titlebook: Intelligent Paradigms for Smart Grid and Renewable Energy Systems; B. Vinoth Kumar,P. Sivakumar,K. Vijayakumar Book 2021 The Editor(s) (if

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樓主: 劉興旺
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發(fā)表于 2025-3-23 12:50:56 | 只看該作者
Learning Automata and Soft Computing Techniques Based Maximum Power Point Tracking for Solar PV Sysnlinear, and maximum power point (MPP) is dependent on the input conditions. To extract maximum power from SPV module, MPP tracking controller is incorporated in SPV system. The main aim of this chapter is to introduce learning automata concept and its adaptability for the development of MPPT algori
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發(fā)表于 2025-3-23 16:42:41 | 只看該作者
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發(fā)表于 2025-3-23 20:05:05 | 只看該作者
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發(fā)表于 2025-3-24 02:13:39 | 只看該作者
Soft Computing Techniques-Based Low Voltage Ride Through Control of Doubly Fed Induction Wind Genere coupled to grid throughout as well as post fault conditions and must source reactive power to the grid with an objective of maintaining grid voltage. This chapter focuses on the Low Voltage Ride Through (LVRT) enhancement of Doubly fed induction generator (DFIG) wind turbine especially on the cont
15#
發(fā)表于 2025-3-24 04:52:31 | 只看該作者
Harmonic Current Estimation of a Non-linear Load Using Artificial Neural Network,e loads drawn on-sinusoidal current waveform. The active harmonic power filters are employed to mitigate these harmonics. The accuracy of Harmonic Current Estimation (HCE) assumes importance for the good performance of active harmonics power filter. The conventional method namely Fourier series meth
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發(fā)表于 2025-3-24 10:29:00 | 只看該作者
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發(fā)表于 2025-3-24 12:15:22 | 只看該作者
2524-7565 smart technologies.Serves as a reference for researchers andThis book addresses and disseminates state-of-the-art research and development in the applications of intelligent techniques for smart grids and renewable energy systems. This helps the readers to grasp the extensive point of view and the e
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發(fā)表于 2025-3-24 14:54:02 | 只看該作者
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發(fā)表于 2025-3-24 20:15:04 | 只看該作者
20#
發(fā)表于 2025-3-24 23:20:12 | 只看該作者
2524-7565 t paradigms pertaining to the smart grid and renewable energy systems. The prospective audience would be researchers, professionals, practitioners and students from academia and industry who work in this field.978-981-15-9970-5978-981-15-9968-2Series ISSN 2524-7565 Series E-ISSN 2524-7573
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