The effects of plug-in hybrid vehicles in New York City could be substantial to the city’s efforts to achieve future climate change goals and environmental initiatives. This study focuses on these effects as they correlate to the energy supply system, transportation network, and air quality control. To accomplish this analysis a variety of techniques were used to model the transportation and electric networks around New York City. The transportation system is modeled through close manipulation of U.S Census Data collected in 2000 and 2003 in which citizens were asked questions pertaining to their daily journeys to work. The power grid for the Northeast Power Coordinating Council (NPCC) is modeled using a MATLAB program entitled MATPOWER developed by professors and students at Cornell University. By incorporating real-time load datum, this program has the capability of rendering accurate depictions of changes in power plant loads, emissions, and costs. In addition, the program will distinguish the type of energy used on the margin and locate the geographic region of that energy source. With this capability, the focus of this study surrounded three main objectives: to estimate market growth of PHEVs in the New York metropolitan area, investigate how fuel used to generate power changes with increase in demand, and to analyze the effects on emissions from cars and power plants. Initial analysis indicates that the introduction of plug-in hybrid electric vehicles into the New York City commuter fleet will have a net positive effect on reducing both total emissions and localized emissions around the city’s transportation infrastructure. At an ambitious rate of 20% PHEV penetration, New York could save nearly 625,000 gallons of gasoline per day. This is equivalent to 33,000 barrels of oil. At the current gasoline prices in New York State of $2.087 per gallon, this is a daily savings of $1.3 million dollars per day. In addition, at this penetration the PHEV’s would displace over 29,000 metric tonnes of net carbon dioxide per day.

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