Probabilistic wind speed forecast for wind power prediction using pseudo ensemble approach Sultan Al-Yahyai 1 , Yassine Charabi 2 , Adel Gastli 1 s.alyahyai@gmail.com yassine@squ.edu.om gastli@squ.edu.om 1 Department of Electrical & Computer Engineering 2 Department of Geography College of Engineering College of Arts & Social Sciences Sultan Qaboos University, Muscat, Oman Abstract Accurate wind and power forecast is essential process in wind energy marketing. Due to the intermittent nature of the wind, it is necessarily to provide information about predictability of different wind speeds. Numerical Weather Prediction (NWP) provides wind forecast as a single value for a given time horizon. Therefore, forecasting wind speed as deterministic value doesn’t represent the uncertainty of the wind speed forecast. Ensemble NWP forecast is used to calculate the probability of occurrence of different wind speeds classes. The main disadvantage of this approach is the extensive computational resources required to run multiple copies of the model. Poor man ensemble method is used to overcome extensive computational resources requirement of the approach through utilizing the overlapping runs of the NWP model from different starting times for given point in time. This paper, explores the possibility of using pseudo ensemble method for generating probabilistic wind forecast for wind power applications. This method utilizes the spatial and temporal neighborhoods of the forecast point to generate forecast dataset and then calculate the required probabilities. A case study using the proposed method is tested using wind data from NWP model and measurements from three weather stations in Oman. Key words: Probabilistic power forecast, pseudo ensemble, Oman 1. Introduction Due to the cubic relation between wind speed and theoretical power contents of the wind, it is necessary to accurately estimate the future wind speed at wind farm site. Accurate wind and power forecast is needed by wind farm developers and operators. It is used to ensure high security of supply [1] in term of optimizing the scheduling of conventional power plants, optimizing the value of produced electricity in the market and scheduling the maintenance planning [2].