Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Dwivedi, Divyanshi"'
Autor:
Babu, K. Victor Sam Moses, Dwivedi, Divyanshi, Valdes, Marcelo Esteban, Chakraborty, Pratyush, Panigrahi, Prasanta Kumar, Pal, Mayukha
Arcing faults in low voltage (LV) distribution systems associated with arc-flash risk and potentially significant equipment damage are notoriously difficult to detect under some conditions. Especially so when attempting to detect using sensing at the
Externí odkaz:
http://arxiv.org/abs/2410.10151
Autor:
K., Victor Sam Moses Babu, Nayak, Sidharthenee, Dwivedi, Divyanshi, Chakraborty, Pratyush, Bhende, Chandrashekhar Narayan, Yemula, Pradeep Kumar, Pal, Mayukha
Faults on electrical power lines could severely compromise both the reliability and safety of power systems, leading to unstable power delivery and increased outage risks. They pose significant safety hazards, necessitating swift detection and mitiga
Externí odkaz:
http://arxiv.org/abs/2403.05995
Autor:
K., Victor Sam Moses Babu, Nayak, Sidharthenee, Dwivedi, Divyanshi, Chakraborty, Pratyush, Bhende, Chandrashekhar Narayan, Yemula, Pradeep Kumar, Pal, Mayukha
Electrical fault classification is vital for ensuring the reliability and safety of power systems. Accurate and efficient fault classification methods are essential for timely and effective maintenance. In this paper, we propose a novel approach for
Externí odkaz:
http://arxiv.org/abs/2403.05991
Autor:
Krishna, G Hari, Babu, K. Victor Sam Moses, Dwivedi, Divyanshi, Chakraborty, Pratyush, Yemula, Pradeep Kumar, Pal, Mayukha
The rapid increase in Electric Vehicle (EV) adoption provides a promising solution for reducing carbon emissions and fossil fuel dependency in transportation systems. However, the increasing numbers of EVs pose significant challenges to the electrica
Externí odkaz:
http://arxiv.org/abs/2401.01597
Autor:
Mitikiri, Sagar Babu, Babu, K. Victor Sam Moses, Dwivedi, Divyanshi, Srinivas, Vedantham Lakshmi, Chakraborty, Pratyush, Yemula, Pradeep Kumar, Pal, Mayukha
The increasing number of electric vehicles (EVs) has led to the growing need to establish EV charging infrastructures (EVCIs) with fast charging capabilities to reduce congestion at the EV charging stations (EVCS) and also provide alternative solutio
Externí odkaz:
http://arxiv.org/abs/2311.08656
Autor:
Dwivedi, Divyanshi, Mitikiri, Sagar Babu, Babu, K. Victor Sam Moses, Yemula, Pradeep Kumar, Srininvas, Vedantham Lakshmi, Chakraborty, Pratyush, Pal, Mayukha
This comprehensive review paper explores power system resilience, emphasizing its evolution, comparison with reliability, and conducting a thorough analysis of the definition and characteristics of resilience. The paper presents the resilience framew
Externí odkaz:
http://arxiv.org/abs/2311.07050
Publikováno v:
IEEE Transactions on Instrumentation and Measurement-2023
The expansion in technology and attainability of a large number of sensors has led to a huge amount of real-time streaming data. The real-time data in the electrical distribution system is collected through distribution-level phasor measurement units
Externí odkaz:
http://arxiv.org/abs/2304.00092
Autor:
Babu, K. Victor Sam Moses, Dwivedi, Divyanshi, Chakraborty, Pratyush, Yemula, Pradeep Kumar, Pal, Mayukha
The adoption of distributed energy resources (DERs) such as solar panels and wind turbines is transforming the traditional energy grid into a more decentralized system, where microgrids are emerging as a key concept. Peer-to-Peer (P2P) energy sharing
Externí odkaz:
http://arxiv.org/abs/2303.09471
The energy transition towards photovoltaic solar energy has evolved to be a viable and sustainable source for the generation of electricity. It has effectively emerged as an alternative to the conventional mode of electricity generation for developin
Externí odkaz:
http://arxiv.org/abs/2212.14653
Autor:
Patwardhan, Siddharth, Majumder, Utso, Sarma, Aditya Das, Pal, Mayukha, Dwivedi, Divyanshi, Panigrahi, Prasanta K.
The percolation threshold is an important measure to determine the inherent rigidity of large networks. Predictors of the percolation threshold for large networks are computationally intense to run, hence it is a necessity to develop predictors of th
Externí odkaz:
http://arxiv.org/abs/2212.14694