Session: 05-08 Particles for Thermal Storage in CSP 1

Paper Number: 113092

113092 - Optimum System Configuration for Different Nominal Powers in Particle-Based Csp Systems 

Concentrating Solar Power (CSP) is a very promising source of renewable energy thanks to its potential to integrate storage and produce electricity at 0.05-0.06 $/kWh. In order to achieve this price, next-generation CSP plants integrate central receivers to achieve the high temperatures required by high-efficiency sCO₂ power cycles (>700ºC). The heat transfer fluid used in commercial CSP plants is molten salts. However, the next-generation CSP systems has been looking for alternative fluids that can achieve higher temperature without degradation, and recent studies show that particles seem to be one of the best options.

This study analyzes the potential Levelized Cost of Electricity (LCOE) that particle-based systems can achieve for different nominal powers. A techno-economic model developed by Sandia National Laboratories and Universidad Politécnica de Madrid during the last four years has been employed to study different configurations and find the one with the lowest LCOE. While previous analyses up to date only considered the option of one single north-faced receiver, this study analyzes the potential of adding more receivers.

On the one hand, adding more receivers will add complexity to the system, which could increase the total system cost. On the other hand, adding more receivers will grant several advantages. The main one is the better optical efficiency that the system will achieve along the day. But another great advantage specific to free-falling particle receivers may be the reduction of thermal losses due to wind. In the analyzed location (Dagget, CA), north-faced receivers have high thermal losses due to wind. A greater number of receivers allow to change the orientation of this north-faced receiver (or at least reduce its aperture area) to reduce thermal losses.

Several particle-based CSP systems with different nominal powers (5 MWe to 100 MWe) have been optimized to find the minimum LCOE. Although the main objective of this study is to find the optimum number of receivers for different nominal powers, the following variables have been also optimized due to the big effect on the optimum solution: tower height, aperture area and number of heliostats. The heliostat area is also adapted to the different receiver sizes for every configuration. In order to further reduce the LCOE, different potential solutions (such as the use of multistage falling particle receivers or active heliostat control) have been also analyzed.

The results show that two-receiver configurations achieve the lowest LCOE across all nominal powers. However, three-receiver configurations remain a very competitive design. In fact, for other locations (other than Daggett, CA) with different prevailing wind conditions, a 3-receiver design may prove to be superior due to the different influence of wind. For smaller nominal powers, the difference in LCOE between 1-, 2-, and 3-receiver systems is very small. Overall, CSP systems with nominal powers between 20 and 50 MWe had the lowest LCOE with minimums below 0.06 $/kWh. Multistage falling particle receivers could reduce the LCOE around 3% in all the configurations. However, active heliostat control did not show substantial benefits.

Presenting Author: Luis F Gonzalez-Portillo Universidad Politecnica De Madrid

Presenting Author Biography: Dr Luis González-Portillo is Associate Professor at Universidad Politécnica de Madrid and currently Visiting Researcher at Massachusetts Institute of Technology (MIT). He has been working in Concentrating Solar Power (CSP) since 2016. Dr. González-Portillo has collaborated in several international projects in this field, such as the European H2020 project “Application of Solar Thermal Energy to Processes” and the US project “Generation 3 Concentrating Solar Power Systems”. Nowadays he is also working in a novel method to generate hydrogen through methane pyrolysis in collaboration with MIT.