SCRS Proceedings of International Conference of Undergraduate Students
Smart Load Shedding
Authors: Ravi Kumar Jain, Vindhya Srivastava, Akanksha Yadav and Sachin Verma
Publishing Date: 16-01-2023
ISBN: 978-81-95502-01-1
Abstract
Modern Power systems demand maintenance of essential security in the field of load shedding. We are still living in a society where a large number of houses go through long hours of power cuts in the locality. For many years, the increased effectiveness of the under-frequency load shedding (UFLS) schemes has proven to be a matter of research across the globe. Regrettably, the solution which was proposed mostly requires expensive technical resources and large amounts of real-time data monitoring. This paper presents a smart scheme for rapid and accurate load shedding using neural networks so that predicting the possible loss of load at the initial stage becomes feasible and neuro-fuzzy to determine how much load shed is to be done. The proposed techniques can provide tools for improving the reliability and continuity of the power supply. This was validated by the results obtained by various research papers reviewed in this paper. The authors aim to undermine an Underfrequency Load Shedding Scheme characterized by increased effectiveness where the case is of large disturbances and foreshortened power which was disconnected in the case of small disturbances compared to the old conventional load-shedding methods. The aim is to provide centralized and distributed load shedding strategies.
Keywords
Power System, Load shedding, Fuzzy logic, Power Supply, load demand.
Cite as
Ravi Kumar Jain, Vindhya Srivastava, Akanksha Yadav and Sachin Verma, "Smart Load Shedding", In: Prashant Singh Rana, Deepak Bhatia and Himanshu Arora (eds), SCRS Proceedings of International Conference of Undergraduate Students, SCRS, India, 2023, pp. 161-166. https://doi.org/10.52458/978-81-95502-01-1-18