Power Block Off-design Control Strategies for Indirect Solar ORC Cycles

AbstractThe performance of a 5MWel indirect ORC cycle coupled to linear solar collectors with different technologies is assessed, aiming at evaluating the effect of different control strategies on annual electricity output. Two different solutions are considered for solar collectors: a state-of-the-art parabolic trough collector with Therminol VP1 as heat transfer fluid (HTF), reaching 390°C as maximum temperature within the solar field, and a cheaper Linear Fresnel Reflector (LFR) with Therminol 55, limited to an operating temperature of 310°C. A simplified procedure is firstly proposed in order to identify the organic fluid that guarantees the highest performance under design conditions. Toluene is the selected working fluid in a saturated regenerative Rankine cycle configuration. After fluid selection, a more detailed analysis involving turbine sizing and piping estimate is carried on in order to set optimal on-design parameters such as the evaporating pressure of the working fluid. Finally, yearly electricity production is calculated taking into account off-design performance of all plant components as a function of the effective solar radiation. Two different off-design control strategies are considered for the turbine, namely sliding pressure and constant pressure at the turbine inlet. The levelized cost of electricity (LCOE) is computed for both cases. For high temperature collectors the LCOE results respectively about 180 €/MWh with partial admission and 175 €/MWh with sliding pressure off-design control strategy. LFR technology leads to similar LCOE when its specific cost is about half than the parabolic trough collector

Application of a general discrete adjoint method for draft tube optimization

ABSTRACT: Automatic optimization is becoming increasingly important in turbomachinery design to improve the performance of machine components and Evolutionary Algorithms (EAs) play a very important role in this task. The main drawback of EAs is the large number of evaluations that are required to obtain an "optimal" result. Consequently, in order to keep the computational time in an affordable frame for design purposes, either the mesh size has to be limited, thus reducing the resolution of the flow phenomena, or the number of free parameters must be kept small. Adjoint optimization does not suffer from these restrictions, i.e. the optimization time is not affected by the number of parameters. The computational effort for the adjoint method scales only with the grid size and is usually in the range of two times the CFD simulation alone. In this paper, a discrete adjoint method based on a coupled pressure based RANS solver is presented and applied to draft tube optimization. The adjoint solver is general and can therefore deal with any turbulence model supported by the CFD solver as well as any boundary condition, including mixing planes and mesh interfaces needed for multi-stage simulations. Furthermore, there is no restriction on the choice of objective function. The adjoint method is first applied to a baseline draft tube geometry and then again to its EA optimized geometry where the objective function was the minimization of losses in the draft tube. To reduce the complexity for this proof of concept but still including multiple operating points in the optimization, only peak efficiency and full-load were optimized simultaneously. The adjoint optimization can significantly improve the draft tube performance in both cases (baseline and EA optimization). The interplay between local and global optimization seems to be a promising strategy to find optimal geometries for multi-operating point/multi-objective optimization and will be further investigated in subsequent research

Fluid Dynamics Appearing during Simulated Microgravity Using Random Positioning Machines.

Random Positioning Machines (RPMs) are widely used as tools to simulate microgravity on ground. They consist of two gimbal mounted frames, which constantly rotate biological samples around two perpendicular axes and thus distribute the Earth's gravity vector in all directions over time. In recent years, the RPM is increasingly becoming appreciated as a laboratory instrument also in non-space-related research. For instance, it can be applied for the formation of scaffold-free spheroid cell clusters. The kinematic rotation of the RPM, however, does not only distribute the gravity vector in such a way that it averages to zero, but it also introduces local forces to the cell culture. These forces can be described by rigid body analysis. Although RPMs are commonly used in laboratories, the fluid motion in the cell culture flasks on the RPM and the possible effects of such on cells have not been examined until today; thus, such aspects have been widely neglected. In this study, we used a numerical approach to describe the fluid dynamic characteristic occurring inside a cell culture flask turning on an operating RPM. The simulations showed that the fluid motion within the cell culture flask never reached a steady state or neared a steady state condition. The fluid velocity depends on the rotational velocity of the RPM and is in the order of a few centimeters per second. The highest shear stresses are found along the flask walls; depending of the rotational velocity, they can reach up to a few 100 mPa. The shear stresses in the "bulk volume," however, are always smaller, and their magnitude is in the order of 10 mPa. In conclusion, RPMs are highly appreciated as reliable tools in microgravity research. They have even started to become useful instruments in new research fields of mechanobiology. Depending on the experiment, the fluid dynamic on the RPM cannot be neglected and needs to be taken into consideration. The results presented in this study elucidate the fluid motion and provide insight into the convection and shear stresses that occur inside a cell culture flask during RPM experiments

Convection on the RPM over three periods for three different rotational velocities (top: 40 deg/s; middle: 60 deg/s; bottom: 90 deg/s).

<p>Both frames rotate with constant and equal velocity, and the flask is placed at the center of rotation. The flask was divided into two compartments, denoted as the “y-positive compartment” (for y ≥ 0) and “y-negative compartment” (for y < 0). A virtual variable was placed in the “y-positive compartment” only. Subsequently, the variable was left to mix by convection, and the average concentration in the two compartments was monitored. The rapid fluid motion leads to thorough mixing within two to three periods (arrows).</p

Schematic illustration of the working principles of the centrifuge (left), clinostat (middle) and Random Positioning Machine (RPM, right).

<p>Centrifuges are used for hypergravity experiments. Thereby, the sample (red dot) is rotated around a vertical axis within a certain radius from the axis. Clinostats and RPMs are used for simulated microgravity experiments. Whereas the clinostat rotates the samples around one horizontal axis, the RPM rotates the samples around two perpendicular axes.</p

Shear stresses in the flask during three periods on the RPM for three different rotational velocities (40, 60 and 90 deg/s).

<p>Both frames rotate with constant and equal velocity, and the flask is placed at the center of rotation. Top: Volume average of the shear stresses in the “bulk volume” over time. The “bulk volume” is 4 mm smaller than the flask and thus has a 2 mm clearance from the flask wall. Middle: Maximum shear stresses in the “bulk volume” over time. Bottom: Maximum shear stresses along the “cultivation surface” (the two largest flask walls).</p

Effects of shear stresses on various cells.

<p>Effects of shear stresses on various cells.</p