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Brown, Matthew

Publications and source records attributed to Brown, Matthew.

4 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Close roof-mounted system temperature estimation for compliance to IEC TS 63126

When photovoltaic (PV) modules are installed on rooftops, the module temperature depends primarily on the geographic location and the mounting configuration. If the mounting structure does not provide sufficient airflow in a hot environment, the 98th percentile temperature will exceed 70°C, which according to IEC TS 63126 ED. 1, requires higher levels of thermal stability testing. However, there is no clear way to determine the temperature level needed for a particular location and system design. Here, in this work, we identify a relationship between the module standoff to the rooftop and the module temperature and propose methods to describe a minimum standoff for typical PV modules in a simple mounting configuration installed in a given location. For more complex system designs, we show how to determine an equivalent “effective standoff” that can be applied to generic calculations. Lastly, we show measurements and calculations from several systems to demonstrate how this method could work.

14 SOLAR ENERGY↗
NASA NTRS2013

Experiments with a Parallel Multi-Objective Evolutionary Algorithm for Scheduling

Evolutionary multi-objective algorithms have great potential for scheduling in those situations where tradeoffs among competing objectives represent a key requirement. One challenge, however, is runtime performance, as a consequence of evolving not just a single schedule, but an entire population, while attempting to sample the Pareto frontier as accurately and uniformly as possible. The growing availability of multi-core processors in end user workstations, and even laptops, has raised the question of the extent to which such hardware can be used to speed up evolutionary algorithms. In this paper we report on early experiments in parallelizing a Generalized Differential Evolution (GDE) algorithm for scheduling long-range activities on NASA's Deep Space Network. Initial results show that significant speedups can be achieved, but that performance does not necessarily improve as more cores are utilized. We describe our preliminary results and some initial suggestions from parallelizing the GDE algorithm. Directions for future work are outlined.

scheduling↗