Fundamental differences between the optimization strategies for power cycles used in “traditional” and solar-thermal power plants are identified using principles of finite-time thermodynamics. Optimal operating efficiencies for the power cycles in traditional and solar-thermal power plants are derived. In solar-thermal power plants, the added capital cost of a collector field shifts the optimum power cycle operating point to a higher-cycle efficiency when compared to a traditional plant. A model and method for optimizing the thermoeconomic performance of solar-thermal power plants based on the finite-time analysis is presented. The method is demonstrated by optimizing an existing organic Rankine cycle design for use with solar-thermal input. The net investment ratio (capital cost to net power) is improved by 17%, indicating the presence of opportunities for further optimization in some current solar-thermal designs.
SUMMARYThis paper investigates the sensitivity of the long-term performance simulations of solar energy systems to the degree of stratification in both liquid and packed-bed storage units. The degree of stratification is controlled by the number of nodes used in a finite-difference approximation of the storage system temperature distribution. Short-and long-term simulations of typical water heating and solar thermal power plant systems are conducted. The results indicate that the long-term performance of these systems is far less sensitive to the number of nodes used to represent the degree of stratification than expected based on short-term simulations or experimental data. An explanation is offered for this non-intuitive result.
As deployment of parabolic trough concentrating solar power (CSP) INTRODUCTIONThe number of CSP plants under development or under construction has significantly increased in recent years. The need for standardized acceptance testing procedures is amplified as these plants approach the final stages of construction. Both NREL, in conjunction with Kearney & Associates, and the ASME PTC-52 working group are pursuing acceptance test standards for parabolic trough systems. NREL's expedited effort has produced an interim acceptance test guideline [3]. This paper compares performance data obtained from SkyFuel's test loop at the SEGS II facility in Daggett, CA, to performance predicted by the SAM Physical Trough Model (PTM) [1].The trough Performance Test Code (PTC) provides a methodology for comparing the measured performance of a solar field to its expected performance. For complex CSP systems, determining the expected solar field performance is not a trivial exercise. CSP performance is subject to a number of uncontrollable effects. These include solar position, level of direct-normal irradiation (DNI), wind velocity, mirror soiling, and ambient temperature. While the effect of some variables -like DNI -is unquestionably more prominent than others, each significant effect must be quantified in order to obtain a sufficiently precise prediction of solar field performance. PTC tests for non-CSP processes often make use of correction curves to account for off-design operation. However, because of the complex and variable nature of CSP systems, a detailed performance model fills this role during the acceptance test process.The acceptance test focuses on providing a statistically valid methodology for deciding whether a system's performance achieves its objective. Because no measurement technique can perfectly determine the quantity it measures (e.g. every measurement device has inherent uncertainty associated with the value that it reports), the acceptance test's goal is to determine whether the plant performance meets or exceeds the target, given a particular uncertainty and required confidence level. The performance metric will depend on the requirements of the project stakeholders; likely options include thermal efficiency and delivered thermal power. The measured values are compared to the target values provided by the detailed performance model and theoretically can be applied under any operating condition that both the
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