Research Grants/Fellowships/SBIR

Time-Series Modeling of Integrated Wind/Gas/Battery Systems for Minimization of CO2 and NOx Emissions

EPA Grant Number: FP917157
Title: Time-Series Modeling of Integrated Wind/Gas/Battery Systems for Minimization of CO2 and NOx Emissions
Investigators: Hittinger, Eric S
Institution: Carnegie Mellon University
EPA Project Officer: Zambrana, Jose
Project Period: August 25, 2010 through August 24, 2013
Project Amount: $111,000
RFA: STAR Graduate Fellowships (2010) RFA Text |  Recipients Lists
Research Category: Academic Fellowships , Fellowship - Science & Technology for Sustainability: Energy



In order to reduce carbon emissions, increasing amounts of renewable electricity generation will be required. But most renewable energy systems, such as wind and solar, have variable power output and require dispatchable generation or energy storage to provide fill-in energy. This study examines the costs and emissions of generation/energy storage systems designed to support increasing amounts of wind generation.

There is a growing public and private interest in renewable energy deployment for a variety of reasons, such as carbon emission reduction and energy independence. But the variability of such technologies as wind and solar generation is a formidable barrier to large-scale deployment. This research examines the costs and emissions of specific systems providing fill-in power for wind farms and seeks to identify ways to affordable compensate for wind variability without increased emissions.


This study will use time-series analysis of wind output, coupled with realistic modeling of gas generators and energy storage devices, for a realistic view of the potential capabilities of a composite wind/natural gas/energy storage system. By studying these composite systems with realistically modeled operation at a fine time resolution (10 seconds), we can determine the costs of operation, emissions, and operational parameters of variously composed wind/gas/storage generation blocks. This data will help identify systems that have low emissions at a reasonable cost and can help inform policy and technology decisions.

Expected Results:

Firstly, and most basically, this study will demonstrate that modeling varying and compensating resources using shorter time scales produces results notably different than modeling them in longer blocks. Secondly, it should demonstrate that a small amount of energy storage co-located with the fluctuating resources will reduce both the average cost of power and the emissions from compensating resources. Thirdly, a fully operational model as described above can immediately be used to study a number of effects related to these composite systems, such as the effect of emissions prices or improvement of energy storage technology.

Potential to Further Environmental/Human Health Protection
Deploying renewable electricity generation is an important part of reducing carbon emissions. Thus, addressing the barriers to large-scale renewable generation is necessary to achieving a low-carbon electrical grid. This study examines methods to accommodate increased wind energy at a reasonable cost while using established technologies.

Supplemental Keywords:

wind integration, energy storage, carbon emissions, wind variability, renewable portfolio standards,