Risk Assessment of River-Type Hydropower Plants by Using Fuzzy Logic Approach

S. Kucukali
Cankaya University, Department of Civil Engineering, Ankara, Turkey

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp110571432

Ingår i: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:8, s. 1432-1439

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Publicerad: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


In this paper; a fuzzy rating tool has been developed for river-type hydropower plant projects risk assessment and expert judgments have been used instead of probabilistic reasoning. The methodology is a multi-criteria decision analysis which provides a flexible and easily understood way to analyze project risks. The external risks; which are partly under the control of companies; have been considered in the model. The eleven classes of risk factors were determined based on the expert interviews; field studies and literature review as follows: site geology; land use; environmental issues; grid connection; social acceptance; financial; natural hazards; political/regulatory changes; terrorism; access to infrastructure and revenue. The relative importance (impact) of risk factors was determined from the survey results. The survey was conducted with the experts that have experience in river-type hydropower projects. The survey results revealed that the site geology and environmental issues were considered as the most important risks. The new risk assessment method enabled a Risk Index (R) value to be calculated; establishing a 4-grade evaluation system: low risk having R values between 1.2 and 1.6; medium risk; between 1.6 and 2; high risk; between 2 and 2.4; extreme risk; between 2.4 and 2.8. Applicability of the proposed methodology was tested on a real case hydropower project namely Kulp IV which was constructed on Dicle River in East Anatolia in Turkey. The proposed risk analysis will give investors a more rational basis on which to make decisions and it can prevent cost and schedule overruns.


Hydropower; Risk Analysis; Fuzzy Logic


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