Sell Your Projects | My Account | Careers | This email address is being protected from spambots. You need JavaScript enabled to view it. | Call: +91 9573777164

Support-Vector-Machine-Based Proactive Cascade Prediction in Smart Grid Using Probabilistic Framework

1 1 1 1 1 Rating 4.59 (54 Votes)

PROJECT TITLE :

Support-Vector-Machine-Based Proactive Cascade Prediction in Smart Grid Using Probabilistic Framework

ABSTRACT:

The worldwide major blackout events of power network are highlighting the necessity for technology upgradation in traditional grid. One among the foremost upgradations needed is in the world of early warning generation in case of any grid disturbances such as line contingency leading to cascade failure. This paper proposes a proactive blackout prediction model for a smart grid early warning system. The proposed model evaluates system performance probabilistically, in steady state and under dynamical (line contingency) state, and prepares a historical database for traditional and cascade failure states. A support vector machine (SVM) has been trained with this historical database and is used to predict blackout events in advance. The key contribution of this paper is to capture the essence of the cascading failure using probabilistic framework and integration of SVM machine learning tool to make a prediction rule, which would be in a position to predict the scenarios of the blackout as early as potential. The proposed model is validated using the IEEE 30-bus take a look at-bed system. Proactive prediction of cascade failure using the proposed model might facilitate in realizing the grid resilience feature of good grid.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


Support-Vector-Machine-Based Proactive Cascade Prediction in Smart Grid Using Probabilistic Framework - 4.6 out of 5 based on 54 votes

Project EnquiryLatest Ready Available Academic Live Projects in affordable prices

Included complete project review wise documentation with project explanation videos and Much More...