Name
Title | ||
|---|---|---|
A Stochastic Approach for the State-Wise Forecast of Wind Speed Using Discrete-Time Markov Chain |
Abstract | ||
|---|---|---|
With the increase in demand for wind generation, the challenge is very clear - How can the enemy industries effectively utilize this intermittent energy source whilst making wind power forecasts in order to reduce the occurrence, length of curtailment and improvise the working conditions on the wind power systems. In this paper discrete-time Markov chains are studied and well investigated for its application. An approximate estimation of state-wise forecasts of wind speed on short term basis is implemented. The proposed model builds up through rudimentary stages all-encompassing the very basic concepts, Chapman-Kolmogorov equations and culminating with the application of second order Markov chain. The geographical region under study is a wind farm in Chitradurga, Karnataka where wind speed values are sampled at an interval of 10 minutes for the duration of 3 years, starting from 1st January 2010 to 31st December 2012. Various forecasting errors are enumerated to audit the credibility of the method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TENCON.2019.8929529 | TENCON IEEE Region 10 Conference Proceedings |
Keywords | Field | DocType |
Markov Chain,Chapman Kolmogorov equations,Steady state Markov chain,State-wise forecast,Eigen value,Eigenvector,Equilibrium-vector,Short term prediction,ANOVA,Fisher-snedecor distribution,Probability value | Wind speed,Credibility,Industrial engineering,Computer science,Markov chain,Control engineering,Discrete time and continuous time,Intermittent energy source,Wind power | Conference |
ISSN | Citations | PageRank |
2159-3442 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mounika Yakasiri | 1 | 0 | 0.34 |
| Joyce Avrel | 2 | 0 | 0.34 |
| Swathi Sharma | 3 | 0 | 0.34 |
| M. Anuradha | 4 | 0 | 0.34 |
| B. K. Keshavan | 5 | 0 | 0.34 |