In this dissertation, system identification methods are applied to characterize the
dynamic components behavior of a renewable plant (Hydro – Solar – Wind-Geothermal). First, the relevant factors that are explicative of our models are extracted, to after use Markov Chain and Monte-Carlo simulations to get the more suitable algorithm-based models to optimize the operation cost (or other operative parameters) along the life span of the plant (even under the life time extension mode) we set up the Lost Production Factor (LPF) as an output,. This model will help to better operate the plants by using diagnostics-prognostics, condition monitoring, forecast and predictions, and control design (design to cost). It will help choose the best technologies for the plants and operate the already existing ones in the most profitable way. The application examples are motivated by real-world engineering challenges with renewable Plants under one of the large utilities in the world. The ISO 55000 series Standards are used as a guide, in order to be able to get the proper certification if needed in the future
