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Washington, D.C. - 5 plans that will develop technologically sophisticated monitoring networks for advanced fossil energy power systems have been selected for continued research by the D.O.E. (DOE).
The plans will support efforts by the Office of Fossil Energy's (FE) Advanced Research-Coal Utilization Science (CUS) Plan to study novel approaches in model development and validation; monitoring refractory health; and wireless, self-powered sensors for advanced, next-generation power systems. They will monitor the status of equipment, materials degradation, and process conditions that impact the overall health of a component or system in the harsh high-temperature, highly corrosive environments of advanced power plants.
Fossil fuel power plants generate about two-thirds of the world's total electricity and are expected to continue to play an important role in the years ahead. Increasing global energy demands, coupled with the issues of aging, inefficient power plants and increasingly strict emission requirements will require high levels of performance, capacity, efficiency, and environmental controls from future generation facilities.
Advanced condition-monitoring networks will play an essential role in helping meet these challenges by helping enhance the overall reliability, performance optimization, and availability of emerging near-zero emissions power production systems.
The selected plans represent a total investment of $6.5 million, with nearly $5 million from D.O.E. and the remaining $1.5 million in cost share provided by the recipients. FE's National Energy Technology Lab (NETL) will manage the research.
A description of the plans follows:
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Texas Tech University (Lubbock, Texas)-Using an innovative two-tier framework, the suggested research will establish a comprehensive methodology to determine the type, location, and number of sensors required for component condition monitoring and fault diagnosis in fossil energy systems. Algorithms will be developed and tested on a pressure-driven, plant-wide dynamic model of a coal-based integrated gasification combined cycle (IGCC) plant, and a distributed gasifier model will be used to test sensor placement for unit level condition monitoring. The result will be an integrated model-based algorithm for sensor placement in an IGCC plant that is robust and validated with a nonlinear plant-wide dynamic model. (DOE share: $757,992; recipient share: $223,821; duration: 36 months)
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General Electric Company (Niskayuna, N.Y.)-Technology development for this plan will include (1) enhancing accessible gasifier and radiant syngas cooler (RSC) models to include refractory hot surface degradation and RSC fouling and their impact on sensors; (2) implementing a nonlinear, model-based estimation algorithm to monitor the refractory condition and RSC fouling; and (3) nonlinear optimizing for optimal sensor placement (OSP) to achieve condition monitoring requirements in the presence of practical constraints on sensor types and locations. The performance of the OSP algorithm and resulting condition monitoring solution will be demonstrated using representative test cases for gasifier refractory degradation and RSC fouling. The approach will be applicable to condition monitoring of other critical components in coal-fired power plants. (DOE share: $956,714; recipient share: $239,180; duration: 24 months)
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West Virginia University Research Corporation (Morgantown, W.Va.)-The overall plan objective is to develop in-situ corrosion monitoring sensors for ultra-supercritical (USC) boiler tubes. The four-fold research project includes the following: (1) extending the patent-pending technology developed on monitoring hardware corrosion in liquid metal baths to devise high-temperature electrochemical sensors to monitor corrosion of USC boiler tubes; (2) constructing electrochemical models of the corrosion system to develop predictive capabilities relevant to materials corrosion real-life performance; (3) developing thermal-electric-based energy harvesting and telecommunication devices for the self-powered wireless ready sensor system; and (4) testing the sensor systems at the Western Research Institute combustion testing facility. (DOE share: $908,714; recipient share: $267,113; duration: 36 months)
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Siemens Energy, Incorporated (Orlando, Fla.)-This plan will result in a sensor suite that combines fast area sensors with point sensors to enable a real-time, high-accuracy, remote monitoring of rotating turbomachinery. Wireless Smart Turbine Components will be installed and the data integrated with the remaining useful life models and Siemens' Power Diagnostics® engine monitoring program. At program's end, the Smart Turbine Components will have performed in an H-Class engine test and be ready for implementation in a condition-based assessment and maintenance system. (DOE share: $1,196,878; recipient share: $488,868; duration: 36 months)
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Virginia Polytechnic Institute and State University (Blacksburg, Va.)-A high-temperature distributed sensing platform capable of monitoring the space- and time-varying thermal properties of an entrained flow gasifier refractory wall will be developed at the Virginia Tech Center for Photonics Technology. The sensor will operate using optically-generated transient, traveling long-period gratings in a photonic crystal optical fiber to achieve fully distributed measurement of temperatures above 1000ºC with centimeter-level spatial resolution. Virginia Tech will work with Eastman Chemical Co. to develop a baseline requirement matrix for refractory health monitoring. The team will design and build a laboratory-scale, double-layer refractory furnace to demonstrate the distributed measurement of high temperatures between the 2 layers of refractory and prove the sensor's capability to accurately detect hot spots. (DOE share: $1,167,164; recipient share: $292,978; duration: 36 months)
NETL's Advanced Research Plan pursues plans in several key areas of relevance and potential benefit to technologically innovative coal and power systems. The Plan has an extensive national reach, currently involving some 130 organizations from industry, academia, non-profit organizations, and other U.S. national laboratories.
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