Propagating Uncertainty in Solar Panel Performance for Life Cycle Modeling in Early Stage Design

One of the challenges in accurately applying metrics for life cycle assessment lies in accounting for both irreducible and inherent uncertainties in how a design will perform under real world conditions. This paper presents a preliminary study that compares two strategies, one simulation-based and one set-based, for propagating uncertainty in a system. These strategies for uncertainty propagation are then aggregated. This work is conducted in the context of an amorphous photovoltaic (PV) panel, using data gathered from the National Solar Radiation Database, as well as realistic data collected from an experimental hardware setup specifically for this study. Results show that the influence of various sources of uncertainty can vary widely, and in particular that solar radiation intensity is a more significant source of uncertainty than the efficiency of a PV panel. This work also shows both set-based and simulation-based approaches have limitations and must be applied thoughtfully to prevent unrealistic results. Finally, it was found that aggregation of the two uncertainty propagation methods provided faster results than either method alone.Center for Scalable and Integrated NanomanufacturingNational Science Foundation (U.S.) (Nanoscale Science and Engineering Center

New design algorithm and reliability testing of solar powered near-space flight vehicle for defense and security

Broadband telecommunications have become the key factor for economic growths around the world, but rural and hard to reach areas are missing out on the  opportunity. To overcome this problem, we propose a pseudo-satellite system where  telecommunication devices are carried on a perpetually flying solar aircraft cruising at stratospheric altitude. Our aircraft will combine lighter-than-air technology to augment the lift from the wing. Every major components contributing to the aircraft total weight has been considered, resulting in a range of design solutions. We chose wing span and aspect ratio of 50m and 13 respectively, from which other specifications of the aircraft were fixed to. Our design solution has been validated by power and weight balance analysis. System reliability has been demonstrated by Monte Carlo simulation.Keywords: inflatable aircraft; lighter-than-air; solar aircraft; high amplitude platform (HAP)

Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels

This paper investigates ways to obtain consumer preferences for technology products to help designers identify the key attributes that contribute to a product's market success. A case study of residential photovoltaic panels is performed in the context of the California, USA, market within the 2007–2011 time span. First, interviews are conducted with solar panel installers to gain a better understanding of the solar industry. Second, a revealed preference method is implemented using actual market data and technical specifications to extract preferences. The approach is explored with three machine learning methods: Artificial neural networks (ANN), Random Forest decision trees, and Gradient Boosted regression. Finally, a stated preference self-explicated survey is conducted, and the results using the two methods compared. Three common critical attributes are identified from a pool of 34 technical attributes: power warranty, panel efficiency, and time on market. From the survey, additional nontechnical attributes are identified: panel manufacturer's reputation, name recognition, and aesthetics. The work shows that a combination of revealed and stated preference methods may be valuable for identifying both technical and nontechnical attributes to guide design priorities.Center for Scalable and Integrated Nanomanufacturin

Approaches for identifying consumer preferences for the design of technology products : a case study of residential solar panels

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 91-94).This thesis investigates ways to obtain consumer preferences for technology products to help designers identify the key attributes that contribute to a product's market success. A case study of residential solar PV panels is conducted in the context of the California, USA market within the 2007-2011 time span. First, interviews are conducted with solar panel installers to gain a better understanding of the solar industry. Second, a revealed preference method is implemented using actual market data and technical specifications to extract preferences. The approach is explored with three machine learning methods: Artificial Neural Networks, Random Forest decision trees, and Gradient Boosted regression. Finally, a stated preference self-explicated survey is conducted, and the results using the two methods compared. Three common critical attributes are identified from a pool of 34 technical attributes: power warranty, panel efficiency, and time on market. From the survey, additional non-technical attributes are identified: panel manufacturer's reputation, name recognition, and aesthetics. The work shows that a combination of revealed and stated preference methods may be valuable for identifying both technical and non-technical attributes to guide design priorities.by Heidi Qianyi Chen.S.M