Information-based reliability weighting for failure mode prioritization in photovoltaic (PV) module design

Electric utilities and grid operators face major challenges from an accelerated evolution of grids towards an extensive integration of variable renewable energy sources, such as solar photovoltaic (PV). An opportunity exists to incorporate probabilistic risk analysis into the design and operation of photovoltaic systems to deal with rapidly evolving design and configuration techniques. This could potentially achieve greater design reliability through prediction and remediation of failure modes during design and testing project phases, before project implementation or construction. However, because these systems are novel, detailed component level reliability models are difficult to characterize. In this paper, an approach to the prioritization of PV failure modes extending Colli (1), (2) using a Shannon information-weighted reliability approach is demonstrated. We call this information-weight the "surprise index." The surprise index approach facilitates the prioritization of failure modes by weighting the consequence of their failures by the information in the failure generation model. The surprise index may potentially aid in systematic evaluation of deep uncertainties in PV module design, as failure modes that might be overlooked using traditional PRA may be addressed using the information-based approach.