Online Identification of Power System Dynamic Signature Using PMU Measurements and Data Mining


This paper proposes a 2-stage methodology for online identification of Power System dynamic signature using phasor measurement unit (PMU) measurements and Data Mining . Only transient stability standing is usually predicted within the literature to assist with corrective control, without the dynamic behavior of generators within the event of instability. This paper uses ancient binary classification to spot transient stability in the first stage, and then develops a unique methodology to predict the character of unstable dynamic behavior in the second stage. The method firstly applies hierarchical clustering to define patterns of unstable dynamic behavior of generators, and then applies different multiclass classification techniques, as well as call tree, ensemble call tree and multiclass support vector machine to identify characterized unstable responses. The proposed methodology is demonstrated on a multi-area transmission check system. High prediction accuracy at both stages of identification is demonstrated.

Did you like this research project?

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

PROJECT TITLE : Classification of Online Toxic Comments Using Machine Learning Algorithms ABSTRACT: Toxic comments are online remarks that are insulting, abusive, or inappropriate, and frequently cause other users to quit a
PROJECT TITLE : Reviewer Credibility and Sentiment Analysis Based User Profile Modelling for Online Product Recommendation ABSTRACT: Even for humans, deciphering user buying preferences, likes and dislikes is a difficult undertaking,
PROJECT TITLE : Active Learning From Imbalanced Data A Solution of Online Weighted Extreme Learning Machine ABSTRACT: Active learning is well known for its ability to improve the quality of a classification model while also reducing
PROJECT TITLE : Online ADMM-based Extreme Learning Machine for Sparse Supervised Learning ABSTRACT: In the field of machine learning, sparse learning is a useful strategy for selecting features and avoiding overfitting. An online
PROJECT TITLE : Online Subspace Learning from Gradient Orientations for Robust Image Alignment ABSTRACT: Robust and effective picture alignment remains a difficult task due to the size and complexity of images as well as fluctuations

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry