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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01kd17cw299
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DC FieldValueLanguage
dc.contributor.advisorHazan, Elad-
dc.contributor.authorSandoval, Deborah-
dc.date.accessioned2016-07-01T13:27:34Z-
dc.date.available2016-07-01T13:27:34Z-
dc.date.created2016-04-29-
dc.date.issued2016-07-01-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01kd17cw299-
dc.description.abstractOff-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.extent30 pagesen_US
dc.language.isoen_USen_US
dc.titleDesigning a Task Scheduler for Off-Grid Systemsen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2016en_US
pu.departmentComputer Scienceen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Computer Science, 1987-2023

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