CASE STUDIES IN ESTIMATING WIND POWER POTENTIAL: USING MAXIMUM LIKELIHOOD AND MODIFIED MAXIMUM LIKELIHOOD METHODS

Abstract

Wind power is an important renewable energy source, and estimating its potential is necessary for
efficient utilization. In this paper, we discuss various methods for estimating wind power potential, with a
focus on the use of the Weibull distribution. We present five approaches for estimating the parameters of the
Weibull distribution, including the Maximum likelihood method, the Modified maximum likelihood method,
Error of approximation, Method of Moment, and the Energy pattern factor method. A sample wind speed
dataset is used to compare the accuracy of each method. We also highlight the importance of wind power
forecasting in grid-connected wind generating plants and discuss various modern methodologies for weather
forecasting. Lastly, we present a case study for the Energy pattern factor method, demonstrating its
applicability in wind energy production.