In the last two decades, renewable energy industry has growth incredibly and nowadays they represent a good integration to reduce the impact of fossil sources. Due to the characteristics of the renewable re-sources, technologies for the production of energy are very different and require specific environmental conditions. For this reason, an important activity involving the study of the environmental conditions is al-ways required in order to provide a liable estimation of productivity and verify the potential profitability of a renewable power plant that can justify or discourage a possible investment. Traditionally, the energy production estimation is carried out using mathematical models which take into account plant configuration and averaged statistics of the hosting site. These mathematical models rarely take into account the concept of plant availability in the process of energy estimation. Therefore, the inte-gration of dynamic reliability in such models, combining traditional productivity assessment with an availa-bility assessment model could offer some extent of innovation as novel paradigm. In this paper, we provide a theoretical framework for modelling PV power plants as a Stochastic Hybrid Fault Tree Automaton, a novel promising technique for dynamic reliability. Afterwards, a case study of a photovoltaic power plant is solved and discussed. Results demonstrate that the Stochastic Hybrid Fault Tree Automaton lead to a more precise estimation and offer further benefits for the maintenance and the operation of the plant.
|Titolo:||Stochastic hybrid fault tree automaton for the production forecast of PV power plant|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|