High Density Sensor Network Development


Management and control in self-organizing systems
Management and control in self-organizing systems
Ames National Laboratory
Website:  Ames National Laboratory
Award Number:  FWP-AL-06-205-020
Project Duration:  02/20/2006 – 09/30/2014
Total Award Value:  $2,213,000
DOE Share:  $2,213,000
Performer Share:  $0
Technology Area:  Plant Optimization Technologies
Key Technology:  Sensors and Controls
Location:  Ames, Iowa

Project Description

The goal of this project is to develop the understandings, algorithms, and control strategies needed to utilize large-scale, high-density sensor networks in advanced power plants. A revolution in sensing and control is rapidly approaching. In ten years sensors will be dramatically smaller, less expensive, capable of surviving harsher more challenging environments, and smarter. These microsensors will be able to measure more and different kinds of information. In addition, because they are smaller and relatively less expensive, they will be able to provide many more times the amount of data. They will preprocess the data on the chip and will in some cases be able to respond to requests for new types of data. A first reaction to this revolution in sensing technology is that more data is good. However, there are significant challenges interacting with these microsensors and controlling a new generation power plant. This coming flood of data will challenge our data handling and processing capability, and change how we use sensors to control power plants.

Project Benefits

This project will develop high density sensor networking capability. Providing advancements to algorithms and synchronization strategies will allow for improvements in the control of combustion and gasification technologies. The expected impact of this technology is reduced operating costs and emissions, and increased efficiency of energy systems such as coal-fired furnaces, fluidized beds, gasifiers, fuel cells, and advanced hybrid power plants.

Contact Information

Federal Project Manager 
Steven Seachman: steven.seachman@netl.doe.gov
Technology Manager 
Robert Romanosky: robert.romanosky@netl.doe.gov
Principal Investigator 
Kenneth Bryden: Bryden@ameslab.gov

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