Quigley, Kevin (2022) Providing Charge Forecasting Analytics for EV Owners. Masters thesis, Dublin, National College of Ireland.
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Abstract
During the era of Global warming and Russia’s war in Ukraine, there has never been more urgency in helping Ireland’s electric grid migrate from fossil fuels to renewables. However, renewable power supply sometimes exceeds demand, leading to the disconnection of wind farms and the wastage of potential electricity. This paper is primarily concerned with providing forecasting tools for users to find when electricity rates are lowest due to high supply. In addition, this paper proposes an alternative expenses model for electricity providers which could results in savings for users and increased demand at peak times. This model was found to be 25% cheaper then current pricing models, using whole-sale electricity prices.
Item Type: | Thesis (Masters) |
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Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TD Environmental technology. Sanitary engineering T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electricity Supply |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Tamara Malone |
Date Deposited: | 01 Mar 2023 11:43 |
Last Modified: | 01 Mar 2023 11:43 |
URI: | https://norma.ncirl.ie/id/eprint/6265 |
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