Uncertainty analysis of wave energy farms financial indicators

• Published in: Renewable energy 2014-08, Vol.68, p.570-580
• Main Authors: Guanche, R., de Andrés, A.D., Simal, P.D., Vidal, C., Losada, I.J.
• Format: Article
• Language: English
• Subjects: Applied sciences; Climate; Energy; Exact sciences and technology; Farms; Indicators; Internal rate of return; Interpolation; Methodology; Natural energy; Net present value; Sensitivity analysis; Tariffs; Uncertainty; Wave energy converter; Wave interaction
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2014.02.046

In this work, an analysis of the uncertainty that influences wave energy farm financial returns is carried out. Firstly, a methodology to analyze the financial uncertainty through cash flow analysis is developed. A reconstruction of a set of power production life-cycles is made based on the methodology proposed in Ref. [1] using a selection and an interpolation technique. This set of lifecycles allowed to obtain the statistical distributions of the main financial indicators (IRR, NPV and PBP). The high variability of these parameters is explained by the climate variability. Therefore, for the economic study of a wave energy project the influence of the climate conditions is demonstrated and for this purpose a long climate data series is needed. Finally, a second uncertainty source related with the political and legislation environment is studied, focusing on the effect of feed in tariff. This sensitivity analysis of the feed in tariffs is made based on cash-flow algorithm. Current feed in tariffs seemed insufficient in order to get profitable wave energy projects and also an increase in feed in tariff resulted in an increase of variability of financial indicators. Therefore an increase in feed in tariff is not recommended for early stage technologies. Finally, learning curve was also included in this investigation and it appeared as a key parameter in order to get cost effective financial returns. •An analysis of the uncertainties that affect wave energy projects is performed.•Climate variability is shown to have a huge influence on financial parameters.•Feed in tariff maximizes the financial parameters uncertainty.•Feed in tariff is not recommended for early stage technologies.