| Description |
94 p. |
| Note |
Advisor: Carol J. Miller. |
| Thesis |
Thesis (M.S.)--Wayne State University, 2012. |
| Summary |
Over the course of a day, power utilities must respond to changing demand by dispatching or shedding output from different generators. Each generator is associated with a unique profile of air emissions, based on the type of fuel consumed, installed pollution controls, and the generator's efficiency. The aim of this study is to determine whether shifting electric demand to times when cleaner generation sources are available would result in overall emissions reduction. Dynamic wholesale pricing in the electric power market, specifically the Locational Marginal Price (LMP), provides a means to estimate the marginal generator fuel type. This knowledge was used to roughly estimate hourly local emission rates. Based on these estimated historical emission rates of five different pollutants, best and worst case timing schedules were determined for five household appliances and for the charging of electric vehicle batteries. On average for the five pollutants, an estimated 70% emissions reduction from the worst to best case was achieved by shifting the run times of appliances. By selectively timing electric vehicle battery charging, the average emissions reduction from worst to best case varied from 10-20%, depending on type of charging available. A smartphone app called HERO, or Home Emissions Read-Out, has been created to provide consumers with real-time emissions information at their fingertips. HERO serves to educate people and lets them take on a sense of personal responsibility for the emissions that result from their energy use. |
| Subject |
Environmental engineering
|
|
Air -- Pollution
|
| Added Title |
Wayne State University thesis (M.S.) : Civil Engineering.
|
| OCLC # |
862738263 |
|
