Sakshi Chavan

Ms. Sakshi Chavan

K.J.Somaiya College of Engineering, Mumbai, Mahārāshtra, International

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
31 October 2022 in Energies
Verified
Journal Article
Open access
PDF file
MPManisha Parlewar
Manisha Parlewar
RPRupali Patil
Rupali Patil
TSTanmay Shikhare
Tanmay Shikhare
SNShreyas Nagle
Shreyas Nagle
SCSakshi Chavan
Sakshi Chavan
Neeraj Dhanraj BokdeNeeraj Dhanraj Bokde
Neeraj Dhanraj Bokde
With large penetration of wind power into power grids, the accurate prediction of wind power generation is becoming extremely important. Planning, scheduling, maintenance, trading and smooth operations all depend on the accuracy of the prediction. However due to the highly non-stationary and chaotic behaviour of wind, accurate forecasting of wind power for different intervals of time becomes more challenging. Forecasting of wind power generation over different time spans is essential for different applications of wind energy. Recent development in this research field displays a wide spectrum of wind power prediction methods covering different prediction horizons. A detailed review of recent research achievements, performance, and information about possible future scope is presented in this article. This paper systematically reviews long term, short term and ultra short term wind power prediction methods. Each category of forecasting methods is further classified into four subclasses and a comparative analysis is presented. This study also provides discussions of recent development trends, performance analysis and future recommendations.