2012 Progress Report: Dynamic Electricity Generation for Addressing Daily Air Quality Exceedances in the US

EPA Grant Number: R835219
Title: Dynamic Electricity Generation for Addressing Daily Air Quality Exceedances in the US
Investigators: West, J. Jason , Blumsack, Seth , Vizuete, William
Institution: University of North Carolina at Chapel Hill , Pennsylvania State University
EPA Project Officer: Wilson, Wil
Project Period: June 1, 2012 through May 31, 2014 (Extended to May 31, 2015)
Project Period Covered by this Report: June 1, 2012 through May 31,2013
Project Amount: $250,000
RFA: Dynamic Air Quality Management (2011) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Air


Air quality is forecast daily in the United States. This information can inform daily management decisions in the electric power sector, attempting to avoid daily air quality standard exceedances by redispatching generation from regions strongly influencing the exceedance to elsewhere. Here, we propose to design and evaluate a dynamic management system for the electric power sector with the goal of avoiding daily exceedances of air quality standards for ozone in the eastern United States. We will first demonstrate this dynamic system for a selected episode, evaluating choices in how this system might operate, and incorporating model uncertainty into the design. We will then demonstrate its application over a full summer season, and evaluate this system based on costs, fuel consumption, greenhouse gas emissions, electrical system reliability, success in avoiding local ozone exceedances, and changes in ozone and PM2.5 over the eastern United States, considering environmental justice.

Progress Summary:

Overall progress under this grant has been very good, and is expected to lead to important findings in future years. Much of our work so far has involved work on ozone modeling at the University of North Carolina, electrical grid modeling at Penn State University, and working out means of exchanging information between the two groups. We have selected a first high-ozone episode for purposes of demonstrating a dynamic management system, which is August 4, 2005, in the vicinity of Pittsburgh, PA. We have modeled ozone on this day using CAMx, and have implemented the Direct Decopled Method (DDM) in CAMx, such that it will track sensitivities of ozone to emissions of NOx from multiple power generating facilities. In addition to implementing DDM, we have done a series of scoping air quality simulations that has provided information useful for our designing our project. This has focused on the selected episode, investigating the effects of power plant NOx emissions on ozone, the geographic and temporal scales of relevance for ozone exceedances, and on evaluating the accuracy of DDM sensitivities.

In addition, there has been significant work to implement the electrical grid dispatch model for this episode, and work has begun to define the different decision rules that will be evaluated. In particular, we have developed means of using the modeled ozone sensitivities to inform decisions on power plant dispatch to most cost-effectively meet the air quality targets. Finally, work has been completed to harmonize the database of generating facilities in the dispatch model with the air quality model, which required us to match facilities by locations, compare estimates of emissions in the two databases, and make plans for dealing with sources that do not match.

Future Activities:

We plan to complete our analysis of the effectiveness of a dynamic electricity generation system for the selected episode in the next 6 months. This will entail using different decision rules for electricity dispatch (reducing emissions from key power plants). For each of these decision rules, new electricity dispatch decisions will drive new emissions that will be simulated in CAMx to evaluate how effective each is at reducing ozone. We will also evaluate these decision rules for the several criteria outlined in the proposal, including overall costs of electricity provision, electricity reliability, CO2 emissions, and changes in PM2.5 and ozone in the modeling domain. In addition, the accuracy of the DDM sensitivities will also be evaluated. This single episode will help us evaluate the strengths and weaknesses of different decision rules.

Following this focus on a single episode, we will continue to work forward to complete the other tasks of the project. First, we will design decision rules to take into account model forecast uncertainty in both the ozone concentration and sensitivity to power plant emissions. Second, we will plan to set up a run for the entire summer of 2005 for the eastern United States, for selected decision rules. In doing so, we will evaluate whether DDM is the most efficient means of providing ozone sensitivities, or whether another sensitivity tool may be more computationally efficient. Running a whole summer will allow us to evaluate a wide variety of conditions and evaluate how decision rules function under each.

Journal Articles:

No journal articles submitted with this report: View all 2 publications for this project

Supplemental Keywords:

Ozone, electrical generation, dispatch model, PM2.5;

Relevant Websites:

http://www.unc.edu/~jjwest exit EPA
http://www.unc.edu/~vizuete exit EPA
http://www.energy.psu.edu/personnel/SBlumsack.html exit EPA

Progress and Final Reports:

Original Abstract
Final Report