Availability analysis of photovoltaic inverters in presence of uncertain data via Bayesian approach

The paper presents an advanced Bayesian technique to carry out availability analyses of photovoltaic inverters in presence of uncertain reliability data. In order to proper take into account the above uncertainty, photovoltaic inverter hazard rate and repair rate are considered as random variables characterized by proper Log-normal and/or Gamma distributions. These assumptions are adequately motivated by well known and established physical and mathematical considerations. In this manner the photovoltaic availability uncertainty can be expressed as a function of the component uncertain data. Afterwards, thanks to the tailored Bayesian technique we demonstrate how, even in presence of scarce data, an efficient updating of the system performance can be accomplished during the photovoltaic inverter operating life. The methodology is really useful in view of an optimal allocation of the components’ reliabilities at the design stage and in order to establish the actual expected payback of the whole photovoltaic system. Extensive numerical simulations confirm the effectiveness and the validity of the developed Bayesian technique by also verifying its inherent robustness and efficiency through a rigorous analysis.