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|Title:||PRA-Type Study Adapted to the Multi-crystalline Silicon Photovoltaic Cells Manufacture Process|
|Authors:||COLLI ALESSANDRA; SERBANESCU DAN; ALE Ben|
|Citation:||Safety, Reliability and Risk Analysis. Theory, Methods and Applications (ISBN: 978-0-415-48513-5) vol. 4 (ISBN: 978-0-415-48792-4) p. 2715-2724|
|Publisher:||CRC Press Taylor & Francis Group|
|Type:||Articles in periodicals and books|
|Abstract:||The paper presents a Probabilistic Risk Assessment type (PRA-type) study developed by the Institute of Energy of the Joint Research Centre of the European Commission (JRC-IE) for non-nuclear energy applications and adapted to the manufacture process for multi-crystalline silicon solar cells production. The study is in the context of a project, which is part of a PhD study that aims to develop a methodology to compare risks across different energy systems. Risk assessment and risk data collection efforts are under way in most energy sectors (nuclear, fossil, hydropower), making possible comparisons easier. The photovoltaic (PV) sector, as a new rapidly growing energy technology, offers opportunities for assessing possible risks mainly based on the quantity of dangerous chemicals used, but there seems to be a lack of reported information on its risk events. This situation makes it difficult to analyze the impact of the PV technology, especially if the attention is on human health. Therefore, other well-known methods to assess the safety level of PV manufacturing facilities, such as PRA, can be used to assess corresponding risk levels. The PRA methodology allows to evaluate preliminary quantification figures for failure frequencies, and to demonstrate the possible advantages in identifying the failure scenarios of the process itself, so that countermeasures can be considered. This paper presents first a detailed analysis of the PV manufacture process, conducted at a methodological level (knowledge of the single processes at every step, with chemicals introduced, and resulting as reaction products) as well as at a technical level (machinery involved, auxiliary systems). Next, on this basis, an event tree and fault tree model are constructed and the corresponding analysis performed, using data available from generic chemical industry data-bases. The results of this analysis show that it is possible to quantify the frequency of failures of such processes leading to health challenges and also to identify the scenarios leading to those end states. Even if the figures resulting from the existing models based on the information available so far indicate that such probabilities are unlikely in comparison with other industries, nevertheless the results indicate the existence of weak links. Such weak points could lead to possible health threats. The benefits of using such approaches in conjunction with other design tools are clear when performing risk reviews before events happen. Such an application would be in line with the best practice on these issues from other industrial fields (aviation, aero-space, nuclear, some other chemical processes). The use of such models in the framework of risk comparison could complement the data collected to support the development of the knowledge database on risks for various energy sources.|
|JRC Institute:||Institute for Energy and Transport|
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