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K.R. Devabalaji

Researcher at Hindustan University

Publications -  26
Citations -  1269

K.R. Devabalaji is an academic researcher from Hindustan University. The author has contributed to research in topics: Computer science & Wind power. The author has an hindex of 11, co-authored 19 publications receiving 742 citations. Previous affiliations of K.R. Devabalaji include MVJ College of Engineering & VIT University.

Papers
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Optimal size and siting of multiple DG and DSTATCOM in radial distribution system using Bacterial Foraging Optimization Algorithm

TL;DR: In this paper, a novel approach to determine the optimal location and sizing of Distribution Generation (DG) and Distribution STATic COMpensator (DSTATCOM) is analyzed, and the objective function is formulated for minimizing power loss, operational costs and voltage profile enhancement of the system subjected to equality and in equality constraints.
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Optimal location and sizing of capacitor placement in radial distribution system using Bacterial Foraging Optimization Algorithm

TL;DR: In this article, a new long term scheduling for optimal allocation of capacitor bank in radial distribution system with the objective of minimizing power loss of the system subjected to equality and in equality constraints is introduced.
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DSTATCOM allocation in distribution networks considering load variations using bat algorithm

TL;DR: In this article, the authors proposed a new method of scheduling for optimal placement and sizing of Distribution STATic COMpensator in the radial distribution networks to minimize the power loss, the proposed method Voltage Stability Index is used to search the optimal placement for installation of DSTATCOM.
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Automated power management strategy for wind power generation system using pitch angle controller

TL;DR: The main objective of this research work is to develop a fuzzy logic–based pitch angle control and to developed a static transfer switch to make power balance between the wind power generation system and the loads.
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Improved fault ride through capability of DFIG-wind turbines using customized dynamic voltage restorer

TL;DR: A novel hybrid genetic algorithm optimized Elman neural network controller for proton exchange membrane fuel cell supported customized Dynamic Voltage Restorer (DVR) to improve the fault ride-through capability of Doubly Fed Induction Generator (DFIG) based wind power generation systems.