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8 May 2018 The role of sensors and controls in transforming the energy landscape
Aileen Richardson, Dale Keairns, Briggs M. White
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Proceedings Volume 10639, Micro- and Nanotechnology Sensors, Systems, and Applications X; 106390Y (2018) https://doi.org/10.1117/12.2303722
Event: SPIE Defense + Security, 2018, Orlando, FL, United States
Abstract
The U.S. Department of Energy funds a large portfolio of fossil energy R&D projects aimed at transformational improvements in the cost and environmental performance of coal-based power generation while maintaining high reliability standards. The National Energy Technology Laboratory (NETL) manages DOE’s Crosscutting Research Program, which leverages on-going trends in disruptive technology to achieve breakthroughs in sensors and controls. Examples include: advanced manufacturing of embedded sensors with energy harvesting capability; wireless signal transmission and blockchain infrastructure; and the application of data analytics and machine learning to processing distributed sensor signals to create actionable control interfaces. The fossil energy application space requires the development of sensors capable of monitoring key operational parameters (temperature, pressure, and gas compositions) while operating in harsh environments; analytical sensors capable of on-line, real-time evaluation and measurement to support condition-based monitoring. Controls development centers around self-organizing information networks, algorithms for component lifetime assessment and plant-level economics, and distributed intelligence for process control and decision making. All of this must be accomplished while hardening fossil energy assets.

An overview of DOE’s Fossil Energy R&D Program with an emphasis on Sensors and Controls will be presented including discussion of technologies and applications being pursued and their status.
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Aileen Richardson, Dale Keairns, and Briggs M. White "The role of sensors and controls in transforming the energy landscape", Proc. SPIE 10639, Micro- and Nanotechnology Sensors, Systems, and Applications X, 106390Y (8 May 2018); https://doi.org/10.1117/12.2303722
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Cited by 4 scholarly publications.
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KEYWORDS
Control systems
Sensors
Manufacturing
Reliability
System integration
Additive manufacturing
Process control
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