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a b a b Chapter 9 EnergySector Fundamentals: Economic Analysis, Projections, and Supply Curves Table 9.7 Debt capital structure for the variable rate of return (VRR) model, based on DOE (1997). Year % Debt Debt Annual Rate of Return Equity Annual Rate of Return 15 100 5.5 % 511 80 6.4375 % 1150 60 8.0 % n/a 17% 17% Not typical of competitive market conditions, but reflect primarily publicsector sponsored research with little commercial penetration into the energy market. Period of industrygovernment 5050 cost sharing. 0.5x100+0.5x60=80% debt rate of return calculated as hybrid between govt. share (5/8 @ 5.5%) and IPP share (3/8 @ 8.0%) = 3.4375% + 3% We have estimated the penetration of geothermal capacity into the overall North American market as a function of the variables cited in the model description above. This is shown later in this chapter with graphs that present such penetration both in terms of MWe of installed capacity as a function of price or delivered cost, as well as the relative value of subsidizing technology development and deployment at the early stage of the process. Figure 9.17 illustrates the expected change in aggregate supply of EGS technology available for base load energy as calculated by the MIT EGS VRR model. This model is built on variable rate of return (VRR) assumptions that, in turn, reflect the quartet well configuration (3 production, 1 injector) and perwell flow rates at 80 kg/s. The value of this curve lies in its ability to show the relationship of “startup” in the new industry profile18 to a heat resource that is currently technically and economically beyond reach. This zone of “deficit” in installed capacity lays the groundwork for learning new drilling techniques and locating higherdensity power delivery regions. It also demonstrates the “breakeven” price of delivered power to grid operations given forecast increases in technology performance, drilling techniques, and reservoir stimulation and management where the area utilization (fraction of utilized thermal resource within a given temperature and depth regime) is limited to 2%19 of capacity. Subsequent supply curves shown in this study were calculated using a breakeven price minimization algorithm that assumes that any resource at the lowest possible breakeven price would be exploited up to the area utilization fraction before developing thermal resources that would result in a higher breakeven price (i.e., deeper and/or cooler resources). This covers the available resource range as presented in Chapters 2 and 3 of this report and uses either the MIT EGS model or the GETEM model to calculate the breakeven price, according to the learning curves for the technologies combined with the resource characteristics that are available across the United States, and allows for estimation of breakeven price as a function of technology penetration. 937PDF Image | Energy Sector Fundamentals
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