Dynamic air quality management through electricity dispatch

This thesis presents an efficient approach to improve air quality by considering the two major industries that contribute to the present air pollution levels: transportation and energy. One of the major steps in reducing the pollution levels from the transportation industry is the introduction of Electric Vehicles (EVs). With the expected transition to an electrified vehicle fleet, there will be an increase in electric load. Hence, there exists a trade off between a decrease in the pollutant emissions from the transportation industry and an increase in the emissions from power plants. This thesis presents a novel approach to manage pollutant concentrations using generation economic dispatch at optimum cost.;This thesis first investigates the impact that EVs have on energy prices. EVs have an inherent capability to store energy, and hence can act as short term energy storage devices. To reduce the burden of this extra electric load on grid, it is beneficial to view EVs both as loads and sources of electric energy. This thesis studies the impact of EVs on energy, regulation and reserve prices if they participate as a provider for regulation service, a service required by a grid operator to maintain 60 Hz frequency at all times.;This thesis studies the effect of a peculiar "either/or" constraint in a market of commodities. This thesis shows that such a disjunctive constraint could result in decreasing energy prices with an increase in demand, in contradiction to the expected behavior of increasing prices. This thesis studies and explains this counterintuitive impact on the energy market with EVs supplying regulation. The locational dependence of regulation supply is another important aspect to the study. This thesis analyzes the locational impact of EVs to provide regulation in energy markets and shows that the change in energy prices depends upon the locations EVs choose to supply regulation services.;An increase in the number of electric vehicles will impose an extra load on the electric grid and hence will increase power plant emissions. Sulfur dioxide emissions from power plants are an important precursor to fine particulate matter concentration (PM2.5). PM 2.5 is harmful to human health as it can cause lung and heart related diseases. Because of the negative impacts of PM 2.5 on human health, the US Environmental Protection Agency (EPA) has set standards on the daily mean and the annual average concentrations of PM2.5. This thesis presents a novel approach to reduce the daily mean concentration of PM2.5 by coupling the EPA atmospheric model (CMAQ) and an electricity market model. A linear air quality constraint is introduced in a multi-time period DCOPF to reduce the ammonium sulfate concentration at an arbitrary location and time period using a 36-bus electricity market model. This analysis provides a good proof of concept. To build a more robust framework, this thesis develops techniques to construct a quadratic air quality constraint to reduce the mean concentration of PM2.5 at Lancaster county Pennsylvania on 07/18/05 using a 3357-bus electricity market model. Finally, this thesis presents an operational framework with detailed description of steps to implement the proposed methodology in practice.