Title: Long-haul Wind Speed Prediction utilizing Multivariate Linear Regression


Volume 10 Issue 2 Year 2020

Authors:

Prateek Tiwari

prateekt299@gmail.com
Department of Electrical Engineering, Swami Keshvanand Institute of Technology, Management and Gramothan, Jaipur-302017 (INDIA),

Deepak Saini

deepak.92@outlook.com
Department of Electrical Engineering, Swami Keshvanand Institute of Technology, Management and Gramothan, Jaipur-302017 (INDIA)

Pages: 71-77


Abstract:

The appointment of power frameworks dependent on wind vitality is creating at a speedy pace wherever all through the world in perspective on the extended tendency of using reasonable power source resources and environmental worries regarding power generation. In wind vitality, the forecast of wind speed is over basic. The creating development in wind vitality enables for progressively exact models for wind speed expectation. To avoid both expensive overabundance age and degeneration, this paper acquaints a system with predict the breeze speed, on which the breeze vitality made, relies upon all the more gainfully. This can be cultivated by quantifiable systems wherein information in tremendous numbers are assembled, penniless down for the employable relationship using Multivariate Linear Regression (MLR) models. The parameters are utilized in the expectation of wind speed hourly verifiable information of temperature, pressure, relative humidity, past wind speed, and wind direction for the term of a half year and these parameters are gathered utilizing seven areas of Rajasthan. The results, which are gathered by utilizing MLR, at that point separated with constant information for validation.

 

Keywords:
Mean Absolute Percentage Error (MAPE), Root Mean Sqaure Error (RMSE), Thell's Inequality Coefficicent (TIC), Wind Speed Prediction, Regression, Multivariate Linera Regression (MLR), Welbull Distribution Factor (WDF), Total Suspended Particle (TSP), Sum of Squared Error (SSE), Wind Direction (WD), Relative humadity (RH), Temperature, Pressure