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Figure 5.11: NIR as a function of solar field cost fraction for the optimized case showing variation corresponding to 10 and 20% relative error in all scaling exponents Variation in NIR due to uncertainty in the cost function scaling exponents is not sufficient to dramatically alter the optimized APS design. Only a major shift in the total capital cost distribution between power cycle and solar field would cause a major shift in optimization results. According to Figure 5.11 the solar field cost fraction would need to reduce below 30% in order for the benefits of the optimized cycle design to be negated. Thus, for any cost scenario where the solar field cost dominates total powerplant cost there is substantial room for improvement in the APS design. As the solar field cost fraction reduces, optimum cycle design will shift away from maximum efficiency operation and towards maximum power operation. Evaluation of Other Solar Designs While the performance of the APS plant could be improved by applying the optimization methodology, it is of interest to compare it with other designs for solar powerplants. Figure 5.12 shows heating curves for two parabolic trough solar-thermal powerplant designs using a similar (300oC) HTF temperature and toluene as the working fluid. Based on the general rules developed in the previous sections for evaluating optimal 85PDF Image | Organic Rankine Cycle Solar-Thermal Powerplants
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