Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model

Ferdinando Chiacchio, Fabio Famoso, Diego D’Urso, Sebastian Brusca, Jose Ignacio Aizpurua and Luca Cedola
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Ferdinando Chiacchio: Department of Electrical, Electronical and Computer Engineering, University of Catania, Viale Andrea Doria 6, 95025 Catania, Italy
Fabio Famoso: Department of Civil Engineering and Architecture, University of Catania, Viale Andrea Doria 6, 95025 Catania, Italy
Diego D’Urso: Department of Electrical, Electronical and Computer Engineering, University of Catania, Viale Andrea Doria 6, 95025 Catania, Italy
Sebastian Brusca: Department of Engineering, University of Messina, Contrada Di Dio, 98166 Messina, Italy
Jose Ignacio Aizpurua: Institute for Energy and Environment—Electronic and Electrical Engineering Department, University of Strathclyde, Technology and Innovation Centre, Level 4, 99 George Street, Glasgow G11RD, UK
Luca Cedola: Department of Mechanical and Aerospace Engineering, University of Rome, Via Eudossiana 18, 00184 Roma, Italy

Energies, 2018, vol. 11, issue 2, 1-22

Abstract: The contribution of renewable energies to the reduction of the impact of fossil fuels sources and especially energy supply in remote areas has occupied a role more and more important during last decades. The estimation of renewable power plants performances by means of deterministic models is usually limited by the innate variability of the energy resources. The accuracy of energy production forecasting results may be inadequate. An accurate feasibility analysis requires taking into account the randomness of the primary resource operations and the effect of component failures in the energy production process. This paper treats a novel approach to the estimation of energy production in a real photovoltaic power plant by means of dynamic reliability analysis based on Stochastic Hybrid Fault Tree Automaton (SHyFTA). The comparison between real data, deterministic model and SHyFTA model confirm how the latter better estimate energy production than deterministic model.

Keywords: renewable energy; stochastic hybrid automaton; aging; photovoltaic power plant; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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