scholarly journals Stochastic techno-economic assessment based on Monte Carlo simulation and the Response Surface Methodology: The case of an innovative linear Fresnel CSP (concentrated solar power) system

Energy ◽  
2016 ◽  
Vol 101 ◽  
pp. 309-324 ◽  
Author(s):  
Ilaria Bendato ◽  
Lucia Cassettari ◽  
Marco Mosca ◽  
Roberto Mosca
2019 ◽  
Vol 173 ◽  
pp. 107776 ◽  
Author(s):  
Aneirson Francisco da Silva ◽  
Fernando Augusto Silva Marins ◽  
Erica Ximenes Dias ◽  
Jose Benedito da Silva Oliveira

Author(s):  
Takashi Kobayashi ◽  
Takehide Nomura ◽  
Masaki Kamifuji ◽  
Akira Yao ◽  
Tetsurou Ogushi

A commercial spacecraft should survive on orbit for more than 10 years under the severe circumstances without any maintenance. To realize this subject, not only performance but also other design factors such as reliability, mass, robustness, cost, etc. should be taken into consideration. From point of the thermal design, it is very important to obtain the robust thermal control subsystem with matrix heat pipe layout while minimizing the mass (weight). A new thermal optimization method without compromising the thermal robustness and the mass of thermal subsystem is highly anticipated. This paper proposes a robust thermal design approach for optimizing the heat pipe shape to minimize the mass of the spacecraft panel. We apply a combination of Design of Experiments (DOE), Response Surface Methodology (RSM) and Monte Carlo Simulation to determine the robust design parameters that minimize the mass of the heat pipe structure. Dimensions of the heat pipe design parameters were determined with rationally in a short time and practical robust optimization method was established.


2011 ◽  
Vol 88-89 ◽  
pp. 554-558 ◽  
Author(s):  
Bin Wang

An improved importance sampling method with layer simulation optimization is presented in this paper. Through the solution sequence of the components’ optimum biased factors according to their importance degree to system reliability, the presented technique can further accelerate the convergence speed of the Monte-Carlo simulation. The idea is that the multivariate distribution’ optimization of components in power system is transferred to many steps’ optimization based on importance sampling method with different optimum biased factors. The practice is that the components are layered according to their importance degree to the system reliability before the Monte-Carlo simulation, the more forward, the more important, and the optimum biased factors of components in the latest layer is searched while the importance sampling is carried out until the demanded accuracy is reached. The validity of the presented is verified using the IEEE-RTS79 test system.


Solar Energy ◽  
2017 ◽  
Vol 157 ◽  
pp. 552-558 ◽  
Author(s):  
Riezqa Andika ◽  
Young Kim ◽  
Seok Ho Yoon ◽  
Dong Ho Kim ◽  
Jun Seok Choi ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document