Volume 25, Issue 7 pp. 592-604
EU PVSEC PAPER

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

David Moser

Corresponding Author

David Moser

Institute for Renewable Energy, EURAC Research, Bolzano, Italy

Correspondence

David Moser, Institute for Renewable Energy, EURAC Research, Bolzano, Italy.

E-mail: [email protected]

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Matteo Del Buono

Matteo Del Buono

Institute for Renewable Energy, EURAC Research, Bolzano, Italy

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Ulrike Jahn

Ulrike Jahn

TÜV Rheinland Energy, Cologne, Germany

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Magnus Herz

Magnus Herz

TÜV Rheinland Energy, Cologne, Germany

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Mauricio Richter

Mauricio Richter

3E SA, Quai à la Chaux 6, 1000 Brussels, Belgium

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Karel De Brabandere

Karel De Brabandere

3E SA, Quai à la Chaux 6, 1000 Brussels, Belgium

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First published: 26 January 2017
Citations: 52

Abstract

In 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.

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