Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model
by
Ferdinando Chiacchio 1,*
, Fabio Famoso 2, Diego D’Urso 1, Sebastian Brusca 3, Jose Ignacio Aizpurua 4 and Luca Cedola 5
Ferdinando Chiacchio 1,*, Fabio Famoso 2, Diego D’Urso 1, Sebastian Brusca 3, Jose Ignacio Aizpurua 4 and Luca Cedola 5
1
Department of Electrical, Electronical and Computer Engineering, University of Catania, Viale Andrea Doria 6, 95025 Catania, Italy
2
Department of Civil Engineering and Architecture, University of Catania, Viale Andrea Doria 6, 95025 Catania, Italy
3
Department of Engineering, University of Messina, Contrada Di Dio, 98166 Messina, Italy
4
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
5
Department of Mechanical and Aerospace Engineering, University of Rome, Via Eudossiana 18, 00184 Roma, Italy
*
Author to whom correspondence should be addressed.
Energies 2018, 11(2), 306; https://doi.org/10.3390/en11020306
Received: 16 December 2017 / Revised: 24 January 2018 / Accepted: 25 January 2018 / Published: 31 January 2018
(This article belongs to the Section Electrical Power and Energy System)
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.
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Keywords:
renewable energy; stochastic hybrid automaton; aging; photovoltaic power plant; Monte Carlo simulation
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MDPI and ACS Style
Chiacchio, F.; Famoso, F.; D’Urso, D.; Brusca, S.; Aizpurua, J.I.; Cedola, L. Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model. Energies 2018, 11, 306.
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