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Chandrashekhar N. Bhende
Researcher at Indian Institute of Technology Bhubaneswar
Publications - 42
Citations - 1854
Chandrashekhar N. Bhende is an academic researcher from Indian Institute of Technology Bhubaneswar. The author has contributed to research in topics: Photovoltaic system & Electric power system. The author has an hindex of 12, co-authored 37 publications receiving 1523 citations. Previous affiliations of Chandrashekhar N. Bhende include Indian Institutes of Technology & Indian Institute of Technology Delhi.
Papers
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Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network
TL;DR: The simulation results reveal that the combination of S-Transform and PNN can effectively detect and classify different PQ events and it is found that the classification performance of PNN is better than both FFML and LVQ.
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Permanent Magnet Synchronous Generator-Based Standalone Wind Energy Supply System
TL;DR: In this paper, an algorithm based on dc link voltage is proposed for effective energy management of a standalone permanent magnet synchronous generator (PMSG)-based variable speed wind energy conversion system consisting of battery, fuel cell, and dump load (i.e., electrolyzer).
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Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation
TL;DR: In this article, a new algorithm based on the foraging behavior of Ecoli Bacteria in the human intestine, to optimize the coefficients of the proportional plus integral (PI) controller was presented.
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TS-fuzzy-controlled active power filter for load compensation
TL;DR: Computer simulation results show that the dynamic behavior of TS fuzzy controller is better than the conventional Pl controller and is found to be more robust to changes in load and other system parameters when implemented for PWM switching signal generation.
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Detection and classification of power quality disturbances using S-transform and modular neural network
TL;DR: In this article, an S-transform based modular neural network (NN) classifier was proposed for recognition of power quality disturbances in noisy condition and the performance of wavelet transform (WT) degrades while detecting and localizing the disturbances in the presence of noise.