Sliding-Window-Based Real-Time Model Order Reduction for Stability prediction in smart Grid


A new real-time model order reduction technique for smart grid stability prediction is proposed in this work. An online appropriate orthogonal decomposition algorithm is used in the suggested method. A randomised singular value decomposition is used to extract the major components of the system states using a snapshot matrix on a sliding sample window. For this snapshot matrix, a local linear model is estimated after the system's order is reduced. The system's state is then forecasted using a sliding prediction window. Finally, a suitable stability index is determined, and the system's stability is predicted within this prediction window. Transient stability, unstable/critical machines, and the stability limit may all be predicted using the suggested method. It can also be used to detect first-swing and multiple-swing instability. The suggested technique can forecast system stability with high precision in real time, according to simulations on three test systems. The computational cost and forecast horizon length are appropriate for realistic applications, and the proposed approach offers significant benefits in the case of large-scale Power Systems.

Did you like this research project?

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

PROJECT TITLE : Scheduling Real-Time Parallel Applications in Cloud to Minimize Energy Consumption ABSTRACT: The concept of cloud computing has emerged as an important paradigm in recent years. Cloud computing enables users to
PROJECT TITLE : Improving the Schedulability of Real-Time Tasks using Fog Computing ABSTRACT: The cloud is not the best option for carrying out real-time tasks that have to be completed by a certain time because there is a significant
PROJECT TITLE : Securing Real-Time Video Surveillance Data in Vehicular Cloud Computing: A Survey ABSTRACT: The concept of vehicular ad hoc networks, or VANETs, has attracted a lot of attention recently, particularly in the
PROJECT TITLE : Real-Time Tracking Algorithm for Aerial Vehicles Using Improved Convolutional Neural Network and Transfer Learning ABSTRACT: A real-time tracking algorithm that makes use of an improved convolutional neural network
PROJECT TITLE : Real-Time Learning from an Expert in Deep Recommendation Systems with Application to mHealth for Physical Exercises ABSTRACT: In today's increasingly digital world, recommendation systems are playing an increasingly

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

Project Enquiry