Abstract
In solar photovoltaic (PV) power generation systems, availability impacts directly on annual energy production capacity. In order to reveal availability levels, the system is usually constructed and monitored. Besides to be expensive and time consuming, this approach fails to provide in-advance estimations that could benefit planning, dimensioning, and predictive maintenance. This paper proposes a Petri Net-based model that can anticipate, within a short period of time and acceptable level of accuracy, availability levels for PV systems with different sizes, architectures, generation profiles, and stages of construction. By receiving a set of offline input parameters, the model can be exploited in advance, before actually constructing the real infrastructure to be measured. Simulations show that the system behavior under variability can be anticipated with reasonable accuracy, which tends to be valuable for predictive engineering. A real PV system model illustrates our approach.
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