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200 results on '"Chakraborty, Ajoy Kumar"'

13. Image Encryption Using Pseudorandom Permutation

Author

Hazra, Tapan Kumar, Raj, Kishlay, Sumanth Kumar, M., Chattopadhyay, Soummyo Priyo, Chakraborty, Ajoy Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Chakraborty, Mohuya, editor, Chakrabarti, Satyajit, editor, Balas, Valentina Emilia, editor, and Mandal, J. K., editor

Published
2019
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16. Optimal Operation of Standalone DC Microgrids Considering Renewable and Load Uncertainties.

Author

Reddy, O. Yugeswar, Jithendranath, J., and Chakraborty, Ajoy Kumar

Subjects
MICROGRIDS, BATTERY storage plants, OPTIMIZATION algorithms
Abstract

The rapid growth and development in DC microgrids (DCmGs), led system-level operation and control to be reformed continuously imbibing constraints and concerns that improve system operational performance. Focusing only on islanded DCmGs, quite a literature/work has been attempted in various perspectives to solve energy management problems. In light of this aspect, an optimal operation/control of standalone DCmGs, composed of the droop-regulated dispatchable type distributed generators (DGs) considering generation cost, voltage deviation, and current-sharing objectives has been proposed. The proposed work includes the uncertainties in network variables such as load demand, wind, and solar power generations. The scenario-based analytical method has been employed for modeling the uncertainties stated. For optimal operation, the droop parameters were solved by means of the heuristic-based multi-objective optimization technique, Dragonfly Algorithm (DA). The proposed methodology has been implemented on modified 6-bus and 33-bus test systems operated as DCmGs. Furthermore, the applicability of the proposed approach has been presented for the case study with battery energy storage system (BESS) scheduled DCmG network operation on a 24-hour time horizon. The obtained results have been compared with other optimization algorithms to validate the accuracy of the proposed approach. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Mathematical Vector Quantity Modulated Three Phase Four Leg Inverter

Author

Bhattacharya, Bhaskar, Chakraborty, Ajoy Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Satapathy, Suresh Chandra, editor, Mandal, Jyotsna Kumar, editor, Udgata, Siba K., editor, and Bhateja, Vikrant, editor

Published
2016
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33. Stability Constrained Optimal Operation of Standalone DC Microgrids Considering Load and Solar PV Uncertainties

Author

O, Yugeswar Reddy, J, Jithendranath, Chakraborty, Ajoy Kumar, and Guerrero, Josep M.

Abstract

Operation and control dynamics of islanded DC microgrids (DC mGs) have received enormous interest recently in distribution system management. In this regard, research concern on droop-controlled distributed generations (DGs) integrated within the standalone DC mG is becoming more profound. This paper proposes an optimal operation of droop-controlled standalone DC mG with combined small-signal stability and economic-environment-related objectives. The proposed approach optimizes the principal eigenvalue that affects the system stability and two other objectives. An eigen value-based stability analysis for network configurations, with the possibility of its buses solely connected to either dispatchable DG or constant power load (CPL), is proposed. Moreover, uncertainties involved in mG network variables that originate due to the integration of solar PV generation with load consumption were considered and modelled with relevant probability characterization. A recent swarm-based intelligent technique (dragonfly algorithm) for optimization of droop parameters is adopted in the proposed approach. A unique bi/tri – objective combinations are solved, and obtained results are discussed. To show the adaptability of the proposed approach for any given DC mG network, a standalone 6-bus mG was adopted to verify the applicability. Furthermore, the time-domain simulations were carried out on a sample 3-bus DC mG to validate the proposed strategy.

Published
2023
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42. Bilayered fault detection and classification scheme for low-voltage DC microgrid with weighted KNN and decision tree.

Author

Reddy, O. Yugeswar, Chatterjee, Soumesh, and Chakraborty, Ajoy Kumar

Subjects
DECISION trees, MICROGRIDS, K-nearest neighbor classification, MACHINE learning, BILEVEL programming, ELECTRIC potential measurement, CLASSIFICATION
Abstract

DC microgrids (DCMGs) are gaining popularity mainly in shipboards and isolated power systems for their modest control and higher efficiency. However, the newer conception and less literature are forcing the operators to take up tough challenges for smoother operation of the overall system. Protection areas of DCMGs are still immature because of the inexperience of handling DC faults and less availability of DC circuit breakers (DCCBs) in outsized range. In this work, the fault detection and classification issue in low-voltage-DC-microgrid (LVDCMG) has been solved with a bilayered machine learning scheme based on weighted K-nearest neighbor (WKNN) and decision tree (DT). WKNN accurately detects the fault in the line, and DT classifies the fault as PG or PP for further corrective measures. The developed technique has been implemented in an LVDCMG with PV and battery energy sources. Voltage and current measurements from the network have been used as training samples to the classifier models. It has been noticed that the proposed bilayered protection scheme is giving 100% detection accuracy. The outcome of the proposed structure seems to be promising and has been compared with some of the existing machine learning (ML)-based fault detection techniques for microgrids (MGs). [ABSTRACT FROM AUTHOR]

Published
2022
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