A 10 year installation program for wave energy in Ireland: A case study sensitivity analysis on financial returns

This paper is a case study which examines the finances of a proposed installation schedule of 500 MW of a wave energy device type in Ireland. The novel aspects of the analysis were the modelling of the combined influence of learning curves, supply and demand rates as well as future cost of cash on the phased deployment over the 10 years. There are many studies which have examined the economics of renewable energy project installations, including wave energy. However, there is lack of research in the impact and implications of phased installations over time, especially when using a feed-in tariff (FIT) revenue mechanism. The goal of the study was twofold. The first goal was to assess the viability of the current Irish feed-in tariff within the context of a phased installation program for the wave energy device chosen for the study, and measures required to produce a positive rate of return. The second aim was to assess the impact of learning curve, supply/demand curves and future cost of cash on phased project installations. The wave energy device chosen for the study was the Pelamis P1 and the economic model used was NAVITAS, created by HMRC. The assessment was based on net present value and internal rate of return. The wave energy data for the study was 2007 from M4 of the west coast of Ireland, obtained from Marine Institute, Ireland. Results from the case study indicated that the high initial costs for the case study wave energy device had a significant impact on financial returns. Results of the case study indicate that higher tariffs may be required than the current Irish, static, nonindex linked. FIT to foster positive returns for future wave energy projects, especially if phased installations are considered, which are susceptible to future cash and supply/demand factors. The large range of sensitivity factors assessed in the case study demonstrates the vulnerable nature of these large scale projects when estimating financial returns. Further studies will be required to assess multiple device types, update initial costs for wave energy devices, provide reliable power matrices, as well as appropriate learning curve and supply demand rates. (C) 2011 Elsevier Ltd. All rights reserved.