2015/02/11 by G. D'Amico, Guglielmo D’Amico, D'Amico, G. +4
Engineering · Physics and Astronomy · #Data Analysis #Electric Power System Optimization #Energy Load and Power Forecasting #FOS: Physical sciences #Statistics and Probability (physics.data-an) #Wind Energy Research and Development #physics.data-an
paper · pdf · doi:10.48550/arxiv.1502.03205
arXiv admin note: substantial text overlap with arXiv:1312.3895
arxiv created 2015/02/11 · openalex publication_date 2015/02/11 · arxiv updated 2015/02/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Modeling wind speed is one of the key element when dealing with the production of energy through wind turbines. A good model can be used for forecasting, site evaluation, turbines design and many other purposes. In this work we are interested in the analysis of the future financial cash flows generated by selling the electrical energy produced. We apply an indexed semi-Markov model of wind speed that has been shown, in previous investigation, to reproduce accurately the statistical behavior of wind speed. The model is applied to the evaluation of financial indicators like the Internal Rate of Return, semi-Elasticity and relative Convexity that are widely used for the assessment of the profitability of an investment and for the measurement and analysis of interest rate risk. We compare the computation of these indicators for real and synthetic data. Moreover, we propose a new indicator that can be used to compare the degree of utilization of different power plants.