Models and algorithms for the efficient operation and planning of energy production systems

In particular, wind generation requires complex forecasting techniques which take into account wind speed, wind direction, hub height, geographical conditions, wind farm size, wind turbine technical and operational characteristics and so on. Since the use of wind energy sources and its integration into power generation systems is as- suming increasing importance, new generation models for synthetic wind data are needed, in order to properly generate forecasts of wind speed and power. This data is fundamental in simulations carried out to analyze and improve the performances of wind generating units, individuating the technical parameters of wind turbines that directly a ect power production. Part of our research activities focused also on developing a new model in order to generate real- istic synthetic wind data. In this model, wind speed is assumed to behave as aWeibull distribution, while wind speed forecast error is simulated using First-Order Auto-Regressive Moving Average - ARMA time-series models. Mathematical Operations Research formulations of the Assignment Problem are used to model wind speed persistence features, which, as shown by simulation results, are essential to properly obtain wind speed and power output forecasts. Furthermore, wind synthetic data, generated with the new generation model proposed, has been used to carry out simulations studies to individuate wind turbines operational parameters that mainly a ect wind generators performances. In particular, an experimental function which expresses the average energy produced by a wind