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Identification of technical risks in the photovoltaic value chain and quantification of the economic impact

doi: 10.1002/pip.2857
AbstractIn photovoltaic (PV) projects, it is important to establish a common practice for professional risk assessment, which serves to reduce the risks associated with related investments. The objective of this paper is to present a methodology on how to improve the current understanding of several key aspects of technical risk management during the PV project lifecycle, with the identification of technical risks and their economic impact. To achieve this, available statistical data of failures during a PV project have been collected with the aim to (i) suggest a guideline for the categorisation of failure and (ii) develop a methodology for the assessment of the economic impact of failures occurring during operation but which might have originated in previous phases. The risk analysis has the aim to assess the economic impact of technical risks and how this can influence various business models and the levelised cost of electricity. This paper presents the first attempt to implement cost‐based failure modes and effects analysis to the PV sector and to define a methodology for the estimation of economic losses because of planning failures, system downtime and substitution/repair of components. The methodology is based on statistical analysis and can be applied to a single PV plant or to a large portfolio of PV plants in the same market segment. The quality of the analysis depends on the amount of failure data available and on the assumptions taken for the calculation of a cost priority number. The overall results can be linked to the cost of periodic and corrective maintenance and form the basis to estimate the impact of various risk and mitigation scenarios in PV business models. Copyright © 2017 John Wiley & Sons, Ltd.
- Accademia Europea di Bolzano Italy
- Accademia Europea di Bolzano Italy
- TÜV Rheinland (Germany) Germany
- TÜV Rheinland (Germany) Germany
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).52 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).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
