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WORLD ENERGY [R]EVOLUTION A SUSTAINABLE WORLD ENERGY OUTLOOK Pipeline networks will also need to be constructed to move CO2 to storage sites. This is likely to require a considerable outlay of capital.60 Costs will vary depending on a number of factors, including pipeline length, diameter and manufacture from corrosion-resistant steel, as well as the volume of CO2 to be 4 transported. Pipelines built near population centres or on difficult terrain, such as marshy or rocky ground, are more expensive.61 The Intergovernmental Panel on Climate Change (IPCC) estimates a cost range for pipelines of $1-8/tonne of CO2 transported. A United States Congressional Research Services report calculated capital costs for an 11 mile pipeline in the Midwestern region of the US at approximately $6 million.The same report estimates that a dedicated interstate pipeline network in North Carolina would cost upwards of $5 billion due to the limited geological sequestration potential in that part of the country.62 Storage and subsequent monitoring and verification costs are estimated by the IPCC to range from $0.5-8/tCO2 (for storage) and $0.1-0.3/tCO2 (for monitoring).The overall cost of CCS could therefore be a major barrier to its deployment.63 For the above reasons, CCS power plants are not included in our economic analysis. Table 4.6 summarises our assumptions on the technical and economic parameters of future fossil-fuelled power plant technologies. Based on estimates from WEO 2010, we assume that further technical innovation will not prevent an increase of future investment costs because raw material costs and technical complexity will continue to increase. Also, improvements in power plant efficiency are outweighed by the expected increase in fossil fuel prices, which would increase electricity generation costs significantly. 4.8 cost projections for renewable energy technologies The different renewable energy technologies available today all have different technical maturity, costs and development potential. Whereas hydro power has been widely used for decades, other technologies, such as the gasification of biomass or ocean energy, have yet to find their way to market maturity. Some renewable sources by their very nature, including wind and solar power, provide a variable supply, requiring a revised coordination with the grid network. But although in many cases renewable energy technologies are ‘distributed’ - their output being generated and delivered locally to the consumer – in the future we can also have large-scale applications like offshore wind parks, photovoltaic power plants or concentrating solar power stations. It is possible to develop a wide spectrum of options to market maturity, using the individual advantages of the different technologies, and linking them with each other, and integrating them step by step into the existing supply structures.This approach will provide a complementary portfolio of environmentally friendly technologies for heat and power supply and the provision of transport fuels. Many of the renewable technologies employed today are at a relatively early stage of market development. As a result, the costs of electricity, heat and fuel production are generally higher than those of competing conventional systems - a reminder that the environmental and social costs of conventional power production are not reflected in market prices. It is expected, however that large cost reductions can come from technical advances, manufacturing improvements and large-scale production, unlike conventional technologies. The dynamic trend of cost developments over time plays a crucial role in identifying economically sensible expansion strategies for scenarios spanning several decades. To identify long-term cost developments, learning curves have been applied to the model calculations to reflect how cost of a particular technology change in relation to the cumulative production volumes. For many technologies, the learning factor (or progress ratio) is between 0.75 for less mature systems to 0.95 and higher for well-established technologies. A learning factor of 0.9 means that costs are expected to fall by 10% every time the cumulative output from the technology doubles. Empirical data shows, for example, that the learning factor for PV solar modules has been fairly constant at 0.8 over 30 years whilst that for wind energy varies from 0.75 in the UK to 0.94 in the more advanced German market. Assumptions on future costs for renewable electricity technologies in the Energy [R]evolution scenario are derived from a review of learning curve studies, for example by Lena Neij and others64, from the analysis of recent technology foresight and road mapping studies, including the European Commission funded NEEDS project (New Energy Externalities Developments for Sustainability)65 or the IEA Energy Technology Perspectives 2008, projections by the European Renewable Energy Council published in April 2010 (“Re-Thinking 2050”) and discussions with experts from different sectors of the renewable energy industry. references 60 RAGDEN, P ET AL., 2006, PG 18. 61 HEDDLE, G ET AL., 2003, PG 17. 62 PARFOMAK, P & FOLGER, P, 2008, PG 5 AND 12. 63 RUBIN ET AL., 2005B, PG 4444. 64 NEIJ, L, ‘COST DEVELOPMENT OF FUTURE TECHNOLOGIES FOR POWER GENERATION - A STUDY BASED ON EXPERIENCE CURVES AND COMPLEMENTARY BOTTOM-UP ASSESSMENTS’, ENERGY POLICY 36 (2008), 2200-2211. 65 WWW.NEEDS-PROJECT.ORG. 62 scenarios for a future energy supply | COST PROJECTIONS FOR RENEWABLE ENERGY TECHNOLOGIESPDF Image | SUSTAINABLE WORLD ENERGY OUTLOOK
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