Probabilistic evaluation of wind power generation

• Main Authors: Razali N.M.M., Misbah M.
• Other Authors: 36440450000
• Format: Conference paper
• Published: Institute of Physics Publishing 2023
• Subjects: Electric power generation; Monte Carlo methods; Probability density function; Site selection; Wind turbines; Number of samples; Output power; Power curves; Probabilistic evaluation; Random winds; Stochastic nature; algorithm; conference proceeding; decision making; Monte Carlo analysis; power generation; probability density function; renewable resource; Weibull theory; wind power; wind turbine; wind velocity; Weibull distribution

The power supplied by wind turbine generators (WTG) is widely random following the stochastic nature of weather conditions. For planning and decision making purposes, understanding and evaluation of the behaviour and distribution of WTG's output power are crucial. Monte Carlo simulation enables the realization of artificial futures by generating a huge number of sample paths of outcomes to perform this analysis. The paper presents an algorithm developed for a random wind speed generator governed by the probability density function of Weibull distribution and evaluates the WTG's output by using the power curve of wind turbines. The method may facilitate assessment of suitable turbine site as well as generator selection and sizing. � Published under licence by IOP Publishing Ltd.