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dc.contributor.authorMo, Jung Younen_US
dc.date.accessioned2012-06-28T20:57:10Z
dc.date.available2017-06-01T06:00:32Z
dc.date.issued2012-01-31en_US
dc.identifier.otherbibid: 7745219
dc.identifier.urihttps://hdl.handle.net/1813/29353
dc.description.abstractThis thesis contains three analyses relating to energy and the transition to a low-carbon economy. In Chapter 1, an hourly model is estimated to predict electricity load and price simultaneously. This model is used to calculate how electric vehicles affect electricity markets in New York City and the Hudson Valley for different penetration rates. Charging electric vehicles at night increases the off-peak prices for all customers. The net monthly cost for a PHEV user is about $9 compared to a savings of $115 in gasoline. The extra cost for non-users is only $2. If the feedback effect of load on price is ignored, the extra monthly cost per customer is underestimated by nearly 50%. The costs of PHEV can be reduced substantially by introducing a Vehicle-to-Grid program because it reduces the on-peak prices for all customers and is more than enough to offset the higher off-peak prices. Chapter 2 determines the optimal energy use portfolio, carbon cap, and carbon shadow price from the Regional Greenhouse Gas Initiative (RGGI) by developing an algorithm to maximize social welfare with a carbon damage cost. By introducing a carbon damage cost, coal and natural gas consumption is reduced over time because the damage from burning fossil fuels increases dramatically over time. The optimum carbon price is determined to be $60/tCO2e compared to the current RGGI price of $2/tCO2e. Chapter 3 presents the first analysis to use a dynamic structural model to divide the total electricity load into Temperature Sensitive Load (TSL) and Non-Temperature Sensitive Load. (N-TSL). The analysis shows how the system cost can be minimized when controllable thermal storage is used to offset traditional air conditioning demand in New York State and New England. Benefits from reductions in both the energy cost and capacity cost are calculated for thermal storage owners and non-owners. Using only 30% of the TSL, the optimum daily patterns of load and price are effectively flat. However, the main savings are from reducing the peak load, and the associated capacity costs, and not from the lower cost of purchasing electricity.en_US
dc.language.isoen_USen_US
dc.subjectelectric vehiclesen_US
dc.subjectcarbon marketsen_US
dc.subjecttemperature-sensitive loadsen_US
dc.titleEconomic Analyses Of Plug-In Hybrid Electric Vehicles, Carbon Markets, And Temperature-Sensitive Loadsen_US
dc.typedissertation or thesisen_US
thesis.degree.disciplineAgricultural Economics
thesis.degree.grantorCornell Universityen_US
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Agricultural Economics
dc.contributor.chairMount, Timothy Douglasen_US
dc.contributor.committeeMemberBento, Antonio Miguel R.en_US
dc.contributor.committeeMemberConrad, Jon Men_US
dc.contributor.committeeMemberBogan, Vicki L.en_US


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