Cost Modelling Analysis of Floating Wind Technologies: Assessing the Potential of TLPWIND

Transcription

1 Cost Modelling Analysis of Floating Wind Technologies: Assessing the Potential of TLPWIND Angeliki Spyroudi October 2016 TLI-SP This document explores the commercial viability of floating wind technology by carrying out a cost modelling analysis of TLPWIND, a tension leg platform solution. This is driven by the need to unlock the potential of deeper water sites around the UK which have high wind resources, but which are not suitable for fixed-bottom platforms. For developers and policy makers, key to accelerating floating wind development is a significant reduction in the levelised cost of energy (LCOE). ORE Catapult, in partnership with Iberdrola Engineering and Construction (IEC), has developed a bespoke LCOE model using the TLPWIND design to analyse the viability of floating wind technology, from prototype to commercial arrays, taking into account market and environmental drivers that impact on deployment. Summary of findings Early-stage concepts in floating wind technologies face difficulties in proving their economic viability and potential to reduce offshore wind energy costs. The LCOE modelling exercise for TLPWIND at the candidate Aberdeen site showed a decrease from 184/MWh for a prototype device, to 159/MWh for a pre-commercial array, and 95/MWh for a fullscale commercial wind farm a 70% reduction from prototype to commercial scale. Different environmental conditions such as wind speed, distance to shore and wave height cause major variations in costs and energy production. Using a "medium" market and environmental conditions scenario, the LCOE for a commercialscale wind farm in a generic UK site was modelled at 102/MWh, slightly higher than the more environmentally favourable Aberdeen site. Of all the market drivers, operation and maintenance (O&M) cost is shown to have the greatest impact on LCOE. External drivers such as exchange rate risk also have a major impact. After 2025, a combination of increased market size, experience and investor confidence, coupled with higher turbine capacity, has the potential to reduce the cost of floating wind technologies by almost 40% (under the "medium" site and market conditions scenario). Recommendations A detailed LCOE modelling analysis is necessary to assess the benefits of floating offshore wind farms. A multiple-factor sensitivity analysis must be conducted to understand the cost deviations in site conditions, market prices and market uncertainty. Floating wind developers must exploit the availability of transferable knowledge from onshore wind, fixedbottom wind and the oil and gas industry, where floating platforms are routinely used in deep waters. Policymakers should take steps to increase the proportion of offshore wind in the UK energy mix, promote bespoke contract for difference (CfD) auction rounds for floating wind projects, support the development of energy storage solutions, and improve the grid network. There is a need for further detailed analysis of site suitability, while collaborative research and knowledge sharing between developers and supply chain which would facilitate more optimised designs and more accurate cost estimation should be encouraged.

2 Background The UK has become a leader in global offshore wind deployment over the last few years, thanks to an abundance of shallow waters and plentiful wind resource. More than 5GW is currently generated in shallow waters (<50m) by wind farms using fixed-bottom foundations, with plans in place to increase this to 10GW by The availability of feasible shallow water sites around the UK will eventually become exhausted, meaning there is a requirement for a viable technical solution which offers a competitive alternative. This means exploring deeper sea areas, with high practical wind resource. In Scotland in particular, more than 70% of potential practical resource is located in waters greater than 60 metres deep. 1 Floating wind substructures have the potential to exploit high wind resources further from shore in deep water sites (>50m). Currently, there are three common support structures used across the oil and gas industry which have been adapted to offshore wind. These include the spar-type support structure, semisubmersibles and the tension leg platform (TLP). These floating wind typologies are still in their initial phases of development; they require further deployment on a commercial scale to determine their costcompetitiveness, iron out technical issues, and understand their risks. Only then will they be able to attract investment. Floating wind substructures offer a viable alternative to conventional fixed-bottom foundations, which are not a practical option for deeper sea sites. They also deliver a series of benefits, ranging from lower fabrication, installation and O&M costs, to the opportunity to harness higher wind resources. However, the lack of an optimised design and accurate validation of results remains a barrier to the acceleration of these technologies. There is a requirement to address key technical issues related to the wind turbine, support structure, moorings, anchors, electrical infrastructure, installation, maintenance and simulation tools. 2 Early-stage concepts have the potential to deliver cost-effective solutions in the longer term. However, they face a race against time to reach the high technology readiness of the leading concepts. Prior to commercial wind farm-scale development, the construction of a prototype followed by a small-scale pilot park is a strategy which encourages the wider scale adoption of the technology. In the early stages, the high technology risk and the lack of standardisation requires funding support to move the concept towards a full-scale demonstration project. The level of risk discourages investment and increases the cost of finance. A detailed and robust LCOE model, based on a representative site, can provide insight into the economic viability of the solution while mitigating the concerns of developers. 1 Johanna Yates, Floating Offshore Wind Scotland s Opportunity, Scottish Enterprise, Presentation made at All Energy Exhibition and Conference 2015, Glasgow, (07/05/2015) available online at novadocuments/86793?v= , accessed September Floating wind: technology assessment: Interim findings, ORE Catapult, June 2015, available online at accessed September 2016

3 Modelling the LCOE of the TLPWIND model: project aims ORE Catapult, working in partnership with IEC, have developed a bespoke LCOE model for an innovative TLP design called TLPWIND (Figure 1). Figure 1: TLPWIND technology Because of the level of detail required to comprehensively assess the viability of any wind energy concept, it is critical to prove there is clear capability of reducing the cost of offshore wind generation when reaches commercialisation. In considering the development of TLPWIND, there are four key areas the IEC/ORE Catapult model addresses: What kind of information is needed in order to assess the cost-effectiveness of TLPWIND in the future? What are the costs of developing different sizes of demonstrations? How sensitive is this cost to changes? What is the future view of the market? The IEC/ORE Catapult model is designed to assess the cost of the design from prototype to commercial windfarm using a baseline site, and evaluating the sensitivities that impact on the cost. The LCOE metric is defined as "the total lifetime cost of generating one unit of energy". This same metric is used extensively in energy technologies to evaluate financial viability and compare generating costs. The cost categories which constitute the TLPWIND analysis are divided by capital expenditure (CAPEX), operational expenditure (OPEX) and decommissioning expenditure (DECEX). The high-level cost breakdown used in this LCOE analysis is given in Table 1.

4 CAPEX OPEX DECEX Development and consenting O&M of generating assets Offshore dismantling Fabrication and procurement TNUoS charge Port facilities cost Transportation and installation BSUoS Onshore dismantling Interarray cables Transmission Royalty fee OAR insurance Bottom lease Transmission fee Table 1: Cost categories of TLPWIND LCOE analysis The discount rate used in the analysis is 10% (pre-tax real). This is higher than current estimates for commercial offshore wind, reflecting the higher returns required by the developers for accepting this level of risk associated with any emerging technology.

5 The key components of the TLPWIND model 1. LCOE estimation The fi rst part of the LCOE analysis assumes a baseline set of site conditions. From these, an initial estimate of LCOE for three sizes of concept development can be derived: prototype (1 unit), precommercial (10 units) and commercial scale array (100 units). A 5MW turbine is used for this analysis, which is representative of the likely technology for a typical project. The cost estimations are based on a potential installation of a commercial-scale array for a UK site situated off the coast of Aberdeen in North East Scotland. The commercial-scale array estimates have been evaluated in detail, whereas those for the prototype and pre-commercial are indicative only. Based on the parameters outlined above, the results indicate LCOE values of 184/MWh for a prototype device, 159/MWh for a pre-commercial array and 95/MWh for a full-scale commercial wind farm (Figure 2). The resulting LCOE is a good indication that signifi cant cost reductions can be achieved when progressing from a single prototype to a full-scale commercial array. Figure 2: LCOE progression from prototype to commercial scale for TLPWIND The CAPEX per MW for the commercial array is cut by almost half compared with the pre-commercial projects. This is mainly due to economies of scale particularly in development and consenting costs, and in the mobilisation costs associated with fabrication, procurement and installation. The fixed annual OPEX per MW for a small-scale wind farm appears disproportionate for just a single unit due to the cost of network transmission, which is not included in the prototype cost.

6 2. Sensitivity analysis The developers of this cost model identified Aberdeen as the most suitable location at which the first 500MW array of the TLP concept could be deployed in the UK. In order to understand the impact of different locations on the LCOE, a medium site with average conditions has also been defined within the model. In order to demonstrate the uncertainty in costs and performance of a typical commercial array, it was decided that a sensitivity analysis of market and environmental conditions should be applied to the baseline LCOE of the medium site. This is because the Aberdeen site is known to have favourable environmental conditions, so the medium site is considered to be a more representative base case for the sensitivity analysis. The market and environmental drivers take into account the market rates of commodity prices and the exchange rate, construction and operational uncertainties and site characteristics. The sensitivities are examined individually and then in aggregated scenarios to illustrate, as realistically as possible, the variations on LCOE. a. Market sensitivity An individual sensitivity analysis isolates the effect of each LCOE driver, while all the other variables remain fixed at the medium values. The sensitivity to a 10% change in each of the individual cost drivers shows that, on a like-for-like basis, exchange rate and then turbine CAPEX have the most significant effects in LCOE of the TLPWIND (Figure 3). Figure 3: Single parameter market sensitivities tornado chart (percentage change)

7 It is important to understand that showing the sensitivity to a 10% change in each individual cost driver does not reflect the level of uncertainty characterised by each individual driver. Figure 4 indicates that O&M cost is viewed as having the greatest degree of uncertainty the O&M-driven LCOE variation is highest due to the sensitivity percentage ascribed to the inputs by the concept developers and LCOE modelling team. Figure 4: Single parameter market sensitivities tornado chart (uncertainty level) The interdependencies of these parameters enables different market scenarios to be modelled. Three basic scenarios of low, medium and high market conditions are examined for the medium site. The central estimate of LCOE under mid market conditions is 102/MWh (higher than the central estimate for the Aberdeen site, due to slightly more challenging environmental conditions). Market price variations result in a LCOE variation of approximately ± 10%. b. Environmental sensitivities Site-specific parameters such as wind speed, water depth, seabed type, etc. also impact on LCOE. All locations are different and the variations will become more obvious as the floating wind market grows. The resulting LCOE variations for the medium site are illustrated in Figure 5.

8 Figure 5: Single parameter environmental sensitivities tornado chart All environmental variables, except for wind speed and distance to the O&M port, prove that changes to low and high values, for "easier" and "more difficult" sites respectively, will have the same range of positive and negative effect on LCOE. Although the medium wind speed scenario sits in an approximately central position within the range, the assumed distribution of wind speeds around the mean measurement, and the fact that the 5MW turbine used for this analysis 3 reaches a rated capacity at 12m/s, means that the lower speed has a larger impact on the LCOE (+ 13/MWh) than the higher wind speed (- 9/MWh). In terms of taking account of the distance to the O&M port (routine), the base case assumes a distance of 60km, with the high and low distances being 90km and 30km respectively. The factor under sensitivity in this analysis is distance only (i.e. not combined with more or less difficult sea states). Modelling estimates that O&M (routine) cost for distances between 30km and 60km are to a large extent unchanged, unless accompanied with a change in sea state (e.g. significant wave height). However, as distance increases from 60km towards 90km, more expensive O&M strategies, such as use of helicopters, will be required and so distance does drive higher O&M (routine) costs. These factors result in the extremely asymmetrical LCOE variance. There are also some interdependencies between environmental factors which should be taken into account (e.g. changes in wind speed are likely to be correlated with changes in significant wave height). To model the effect of environmental variations as realistically as possible, a set of scenarios (see Table 2) with lower and upper bounds has been developed and analysed for presenting the combined effect on LCOE. Net equivalent hours (NEH) are modelled alongside cost, in place of a net capacity factor, for ease of illustration. 3 Definition of a 5-MW reference wind turbine for offshore system development, National Renewable Energy Laboratory, February 2009, available online at accessed September 2016

9 Scenario Description 1 Low depth, medium wind, low waves 2 High wind speed and high wave height 3 Best case site conditions but with low wind speed 4 High wind, high waves and far to the coast 5 Closest case possible to Pelastar baseline site conditions 6 Low wave, average wind, drilled 7 Deep and rocky sea bottom 8 Longest distance to the grid connection point and high power losses 9 Medium wind, high waves (swell) 10 Worst site conditions with high wind speed 11 High distance to the O&M permanent base and high distance of offshore export cable 12 Low wind and low wave height 13 Low depth, low wind, close to shore and with rocky seabed 14 Low wind, average waves and long distance to coast Table 2: Scenario definitions for combined environmental sensitivity analysis The Figure 6 displays an LCOE range from 91/MWh to 120/MWh. The potential rise in LCOE due to environmental factors is slightly higher than the corresponding rate of reduction. In particular, LCOE variations are estimated to be in a range between -9% and +19%. As might be expected, these challenging conditions leading to +19% increase in LCOE would not be favourable for the deployment of a wind farm or, at least, the most economically attractive.

10 Figure 6: LCOE comparison with CAPEX, OPEX and production inputs environmental sensitivities c. Combined market and environmental sensitivities The cumulative effect of market sensitivities and environmental sensitivities on LCOE has been modelled via nine scenarios as shown in Figure 7, pairing each market type (low, mid and high) with each site type (low, medium and high). The low site illustrates relatively easy site conditions (lower water depth, closer to shore) but also lower wind speeds, resulting in lower CAPEX and NEH of energy production. Likewise, the high site illustrates more difficult site conditions (deeper water depth, farther from shore) but higher wind speeds, resulting in higher CAPEX and NEH. This means that there are offsets influenced by different environmental characteristics within the three examined scenarios. Figure 7: LCOE comparison with CAPEX, OPEX and production inputs combined environmental and market sensitivities

11 Consequently, the pattern of LCOE for each site type, and the LCOE values estimated within each site type, are very similar. All the combined scenarios show the same range of sensitivity in changes to market conditions (±10%) for all the site options. This modelling demonstrates that market variations have a greater impact on LCOE than changes in environmental characteristics. 3. Future outlook The estimation of LCOE for a commercial-scale array can support decision makers in identifying the expected costs of installing the first-of-a-kind floating wind farm. However, after the first installation, costs are likely to decrease for future wind farms. This will be as a result of factors such as market growth, deployment of floating wind technologies, increase in turbine capacity, learning-by-doing and improved investor confidence. Every anticipated doubling of installed capacity reduces cost. In order to forecast the future cost reduction of TLPWIND, ORE Catapult has developed three deployment scenarios that might be in place by 2050 (low, central and high) for predicted offshore wind installed capacity, and applied the learning rate method. By assessing the degree of novelty for each component of the floating substructure, the cost breakdown categories are classified as mature, emerging or nascent. The three deployment scenarios indicate the timescale in which the benefits of learning will result in reductions mainly to CAPEX and hence to LCOE. Based on the central estimates of cost and future market scenarios described previously, the first commercial array will be installed by The cost in the central case is likely to fall by approximately 18% from 2025, and then level out in the longer term. CAPEX is likely to see a reduction of 21%. However, the 5MW turbine used so far for the TLPWIND analysis is likely to be superseded as larger turbines of 8MW or even 10MW are introduced in the market. Progression to larger turbines is likely to coincide with deployment of commercial-scale floating wind technologies. Fewer large turbines will be needed to meet the installed capacity of the market deployment scenarios. This implies that the learning will be slower and it will take longer for each doubling of installed units. However, fewer turbines mean fewer platforms and subsequently less cost. In addition, we have assumed a learning benefit of 70% is transferable from the existing turbines, as many procedures will be common across turbine sizes. As a result, we have assumed that a cost reduction will follow when the larger turbines start to be deployed in 2030 and Additionally, experience can improve the sector s perception of risk and encourage developers and financiers to enter the market. As they become more familiar with floating wind technologies, this will help reduce the level of return required and hence the discount rate. A lowering of the discount rate by 0.05% for every doubling of capacity from 10% to a lower limit of 8%, could reduce LCOE by a further 11%-12% by A combination of all the above scenarios is illustrated in Figure 8.

12 Figure 8: Effect of market growth on LCOE, The turbine evolution from 5MW in 2025, to 8MW in 2030 and then 10MW in 2035 is the central scenario which illustrates an expected decrease in LCOE of 13% by 2030 and 25% by The upper bound on LCOE is associated with the same evolution in turbine size, but is mapped against low market deployment assumptions. The lower bound on LCOE assumes the same turbine size impact, but is associated with high market deployment assumptions, combined with decreasing cost of finance for each doubling of capacity. This gives a range of between 84/MWh and 93/MWh by 2030 and of between 64/MWh and 84/MWh by 2050, with asymmetric variation around central value. Overall, the results outline that the potential for future LCOE reduction from floating TLPWIND is substantial. In the best case scenario of TLPWIND, under favourable market deployment and financing conditions, a reduction of almost 40% on the baseline estimate of 102/MWh for 2025 could be achieved. The Cost Reduction Monitoring Framework (CRMF) has stated that the cost of electricity from fixed-bottom offshore wind is on track (for some projects at least) to reach 100/MWh (in 2011 prices) by This means that if the uncertainties around market, site availability and policy substrate are mitigated, floating wind technologies could be in line with the costs of fixed-bottom wind farms by as early as 2025, with potential to fall even further in long term. The study shows there is a strong potential to reduce the cost of offshore wind in deeper waters and that floating wind technologies can be competitive with other energy sources such as CCGT, coal, onshore wind and solar 5. 4 Cost Reduction Monitoring Framework 2015: Summary Report to the Offshore Wind Programme Board, ORE Catapult, March 2016, available online at: Framework Summary-report-to-the-OWPB.pdf, accessed September Electricity Generation Costs 2013, Department of Energy & Climate Change, July 2013, available online at: Costs_for_publication_-_24_07_13.pdf, accessed September 2016

13 Conclusions The UK's waters have great wind potential in deeper areas, where fixed-bottom foundations cannot provide a feasible solution. Floating wind substructures are expected to be able to harness offshore wind energy in these challenging sites and drive down the cost of energy from offshore renewable energy sources. The cost modelling analysis undertaken shows that the LCOE of TLPWIND for the selected Aberdeen site is estimated to decrease from 184/MWh for a prototype device, to 159/MWh for a pre-commercial array, and finally to 95/MWh for a full-scale commercial wind farm. In a less favourable site, a medium scenario estimates an LCOE for a commercial array at around 102/MWh. In addition, the market sensitivity analysis identifies exchange rate and turbine cost as key market sensitivities. However, if the uncertainty surrounding each of the variables is taken into account, O&M cost is the greatest source of uncertainty in the LCOE of the TLPWIND. Based on a single factor environmental sensitivity analysis, wind speed is ranked as the main environmental driver, followed by annual wave height and distance to shore. The future market outlook of TLPWIND technology seems to be directly related to wider market growth, learning benefits, economies of scale, increase in turbine size and reduction in discount rate. Considering a number of scenarios for these parameters and incorporating the learning rate methodology, it can be forecast that the cost in a central case scenario is likely to decrease 13% by 2030 and 25% by 2050 compared to the 2025 value of 102/MWh where the first commercial array is expected. These results show that under favourable market conditions, energy from floating offshore wind installations can become cost-competitive with energy from fixed-bottom offshore wind installations and potentially other renewable energy technologies. The TLPWIND concept could contribute substantially to this cost reduction pathway. However, there are some actions which should be taken now that will help the acceleration of floating wind deployment in the next years. These include: The mapping of sites suitable for floating wind technologies. Encouraging collaborative research and knowledge sharing between developers and the supply chain to facilitate design optimisation. Identifying development costs which can be shared. Ensuring greater accuracy in estimating costs. Developers should also exploit the availability of transferable knowledge from fixed-bottom wind installations and other energy sectors, such as oil and gas, where floating substructures are already well used. Policymakers must take a greater interest in the development of floating wind technologies as part of the UK energy mix, linking floating wind with strategies in the areas of CfD auction rounds, energy storage solutions and grid interconnections.

14 Recommended reading Floating wind: technology assessment: Interim findings, ORE Catapult, June pdf accessed September 2016 ORE Catapult (2016), Cost Reduction Monitoring Framework 2015, Summary Report to the Offshore Wind Programme Board Summary-report-to-the-OWPB.pdf accessed September 2016 Author profile Angeliki Spyroudi is a Strategy Analyst at ORE Catapult. She is an experienced researcher, responsible for providing strategic insights to the offshore renewables market combined with in-depth understanding of the industry s cost drivers. She has contributed to financial modelling analysis in a number of floating wind projects and for internal business cases. Her background covers multiple renewable energy sectors. Disclaimer While the information contained in this report has been prepared and collated in good faith, ORE Catapult makes no representation or warranty (express or implied) as to the accuracy or completeness of the information contained herein nor shall be liable for any loss or damage resultant from reliance on same. ORE Catapult Inovo 121 George Street Glasgow G1 1RD +44 (0) National Renewable Energy Centre Offshore House Albert Street Blyth Northumberland NE24 1LZ T +44 (0) Fife Renewables Innovation Centre (FRIC) Ajax Way Leven KY8 3RS T +44 (0) info@ore.catapult.org.uk Web: