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Lifetime assessment of a photovoltaic system using stochastic Petri nets

AbstractThe lifetime estimation of photovoltaic (PV) systems is an important consideration in their life cycle. This paper presents a multi-level methodology to estimate the availability and the lifetime of a PV system using stochastic Petri networks and taking into account the time distribution to failure and to repair. The following components – module, wires, and inverter – are modeled with a Petri network. The evolution of the MTBF, availability, and outages over a 30-year period is simulated for different series/parallel configurations of connected PV modules. Findings are in agreement with reported experimental results, namely the evolution of the availability which tends to be near 96% for long times. Numerical results show that the highest MTBF is 3.2 years and the lowest outage is of 11.84 days/year, which are both obtained for the string configuration. The approach is interesting for the dimensioning of a PV plant or an installation.
- University of Angers France
- Paris-East Créteil University France
- University of Paris France
- École Normale Supérieure France
- Paris-Est Sup France
lifetime, [STAT.AP]Statistics [stat]/Applications [stat.AP], availability, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Petri nets, [SPI.AUTO]Engineering Sciences [physics]/Automatic, failure probability, photovoltaic system, [SPI.AUTO] Engineering Sciences [physics]/Automatic, [SPI.NRJ] Engineering Sciences [physics]/Electric power
lifetime, [STAT.AP]Statistics [stat]/Applications [stat.AP], availability, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Petri nets, [SPI.AUTO]Engineering Sciences [physics]/Automatic, failure probability, photovoltaic system, [SPI.AUTO] Engineering Sciences [physics]/Automatic, [SPI.NRJ] Engineering Sciences [physics]/Electric power
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).8 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
