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DC Field | Value | Language |
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dc.contributor.advisor | Sircar, Ronnie | - |
dc.contributor.author | Veo, Nicholas | - |
dc.date.accessioned | 2019-08-16T15:27:01Z | - |
dc.date.available | 2019-08-16T15:27:01Z | - |
dc.date.created | 2019-04-16 | - |
dc.date.issued | 2019-08-16 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp015m60qv76w | - |
dc.description.abstract | The duck curve is a plot of electricity consumed from nonrenewable sources in California over the course of a day. It is lowest around noon due to the availability of solar energy and resembles the shape of a duck. This thesis investigates the long term effects of California’s Renewable Portfolio Standard program on the duck curve and wholesale electricity prices as the state attempts to meet the program’s renewable generation requirements. The prices are investigated from the bottom up, beginning with the generation capacity of each plant and the state’s projected demands for each county. A network flow optimization is implemented to determine the market price of wholesale electricity based upon costs incurred during generation and transmission. California has also created a plan to implement more electricity storage into it’s cur- rent electricity grid. This thesis includes an examination of the long term effect of growing electricity storage on the duck curve and the volatility of California’s wholesale electricity prices. The effects of storage are explored using the a similar network flow problem that accounts for energy collection during the day and consumption of the same energy at night. This model results suggest that the duck curve will become more pronounced as the state increases its renewable requirements but the severity of the curve can be partially reduced by an increase in storage capacity. | en_US |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | en_US |
dc.title | Flattening the Duck Curve: A Network Optimization Approach to Electricity Transmission in California | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2019 | en_US |
pu.department | Operations Research and Financial Engineering | * |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 961153839 | - |
pu.certificate | Center for Statistics and Machine Learning | en_US |
Appears in Collections: | Operations Research and Financial Engineering, 2000-2020 |
Files in This Item:
File | Description | Size | Format | |
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VEO-NICHOLAS-THESIS.pdf | 2.14 MB | Adobe PDF | Request a copy |
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