Organic Rankine Cycle Solar-Thermal Powerplants

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Organic Rankine Cycle Solar-Thermal Powerplants ( organic-rankine-cycle-solar-thermal-powerplants )

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these high temperatures, and those that can sacrifice many of the advantages that make organic Rankine cycles attractive. Organic Rankine cycles are thus better suited for small-scale applications where the reduced O&M and the ability to operate unattended are of higher value than efficiency. While organic Rankine cycle technology shows great potential, current cycle design practice is not optimized for use with a solar-thermal resource. Using a methodology based on the finite-time thermodynamic analysis, a capital-cost optimization of the APS Saguaro plant showed opportunity for a significant (17%) reduction in capital cost while maintaining design output. The optimized design was achieved by increasing investment in plant heat exchanger area to improve cycle efficiency. The increased cycle efficiency reduced the size of the solar field for the same design power output. The economic viability of organic Rankine cycle solar power systems is dependent on optimizations of this nature. The flexibility of all solar technologies is limited by the natural diurnal variation in insolation. Thermal energy storage represents the most likely near-term option for de- coupling the electric output of parabolic-trough powerplants (both steam and organic Rankine cycle based) from variation in solar radiation. Among the technically feasible thermal energy storage concepts, the single-tank packed-bed thermocline is considered the most attractive compromise between cost and performance. A model of these packed-bed thermocline systems was developed enabling rapid annual simulations while accurately representing performance observed on the Solar One thermocline system. The capacity to consider both direct and indirect storage systems is built into the model. Integrated into TRNSYS, the model provides a valuable tool in analyzing storage system design and control. Optimal integration and control of a storage system is a complex function of many variables including end-user demand, part-load power cycle performance, operating temperatures and fluid stability limits. The number of constraints makes it difficult to draw any general conclusions about optimal storage system integration. To demonstrate 155

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