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Full metadata record
DC Field | Value | Language |
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dc.contributor.advisor | Hazan, Elad | - |
dc.contributor.author | Sandoval, Deborah | - |
dc.date.accessioned | 2016-07-01T13:27:34Z | - |
dc.date.available | 2016-07-01T13:27:34Z | - |
dc.date.created | 2016-04-29 | - |
dc.date.issued | 2016-07-01 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01kd17cw299 | - |
dc.description.abstract | Off-grid systems that use solar power can be significantly effected by cloudy days or limited resources. To minimize the use of back-up generators, residents may try to lower their consumption until the sun comes out again, which can be a great inconvenience. A scheduler that uses forecasting methods to predict battery storage levels can be useful in informing a user about the optimal times to complete tasks. The scheduler design uses generation and consumption models from previous work and data from an actual off-grid facility to determine optimal. The scheduler appears to be more efficient than immediate or random task scheduling over the course of a week. There is plenty of room for improvements, as the scheduler makes many assumptions about the states and structures of off-grid systems. | en_US |
dc.format.extent | 30 pages | en_US |
dc.language.iso | en_US | en_US |
dc.title | Designing a Task Scheduler for Off-Grid Systems | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2016 | en_US |
pu.department | Computer Science | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
Appears in Collections: | Computer Science, 1987-2023 |
Files in This Item:
File | Size | Format | |
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Sandoval_Deborah_2016_Thesis.pdf | 620.28 kB | Adobe PDF | Request a copy |
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