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9.12 Forecast Supply of Geothermal Energy EnergySector Fundamentals: Economic Analysis, Projections, and Supply Curves Chapter 9 (913) “Getting a new idea adopted, even when it has obvious advantages, is difficult. Many innovations require a lengthy period of many years from the time when they become available to the time when they are widely adopted. Therefore, a common problem for many individuals and organizations is how to speed up the rate of diffusion of an innovation.” (Rogers, 2003) In this section, we describe the forecast of supply as a function of resource and market price in various scenarios and sensitivity ranges. The basis of all of the learning curve benefits described earlier is the actual installation of EGS power. Therefore, we must establish a marketpenetration plan that would allow for these benefits to be realized. Diffusion of an innovation follows a normal bell distribution (Rogers, 2003): This normal distribution gives the installation rate for EGS in our evaluation. Equation (913) is centered on time tmax, where the EGS installation rate would be at a maximum. According to the Rogers diffusion theory, the standard deviation, categorizes the adopters into: (i) innovators (tmax–3 ≤ t ≤ tmax–2 ), (ii) early adopters (tmax–2 ≤ t ≤ tmax– ), (iii) early majority (tmax– ≤ t ≤ tmax), (iv) late majority (tmax ≤ t ≤ tmax+ ), and (v) laggards (tmax+ ≤ t) 17. We must also normalize Eq. (913) by the total possible installed EGS capacity, MWtot,EGS to scale up to the desired installed capacity. When Eq. (913) is integrated with respect to time, we get the cumulative capacity of EGS. Both the total capacity and tmax are determined iteratively, depending on the baseload market and the EGS LEC. The parameters tmax and were determined iteratively considering the economics of the innovation. The categorical divisions, given by , were found to be 10 years, tmax = 40 years, and MWtot,EGS (t = 50yrs) = 100,000 MWe, per the scope of this project. Using these parameters, we plot the distribution of installation rate and the cumulative EGS capacity in Figure 9.16. This distribution is used throughout the remaining analysis and is verified with the market considerations in the sections to follow. Using this scenario, one can see that the innovators enter the market at year 10, the early adopters at year 20, and the early majority at year 30. As will be seen in the following sections, the innovators enter the market once parity with market baseload price is reached, while the late majority adopt the technology following the period of highest profitability. 935 ,PDF Image | Energy Sector Fundamentals
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