Area of Interest 1: Sensors, Diagnostics and Controls to Improve Prediction, Performance and Reliability

Subtopic 1A: High-fidelity field testing of technologies

1. Test and Validate Distributed Coaxial Cable Sensors for in situ Condition Monitoring of Coal-Fired Boiler TubesClemson University (Clemson, SC) will test and validate (through the planned field tests in an industrial-scale test facility and an operational utility plant) novel low-cost distributed high-temperature stainless-steel/ceramic coaxial cable sensors, installation methods, instrumentation and data analytics for in situ monitoring of the health status of boiler tubes in existing coal-fired power plants.

DOE Funding: $3,000,000; Non-DOE Funding: $750,000; Total Value: $3,750,000

2. Demonstration of Multi-Gamma Based Sensor Technology for As-Fired Coal Property MeasurementMicrobeam Technologies (Grand Forks, ND) will demonstrate a smart sensor that measures coal properties at the point of injection into burners at a full-scale power plant. Accurate and precise coal property information at the burner provides the opportunity to adjust burner parameters to better follow changing load conditions, optimize flame stability and decrease nitrogen oxide formation at each burner.

DOE Funding: $1,226,094; Non-DOE Funding: $339,586; Total Value: $1,565,680

3. Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate during Ramping for Coal Power PlantsUniversity of Utah (Salt Lake City, UT) will develop and deploy dynamic neural network optimization (D-NNO) technology to minimize heat rate for coal power plants. The project goal is to improve cumulative heat rate by at least 5 percent relative to unoptimized operation and to produce a commercial D-NNO product that can be readily applied.

DOE Funding: $2,992,781; Non-DOE Funding: $792,000; Total Value: $3,784,781

Subtopic 1B: Relevant environment testing of technologies

4. Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power PlantsGeneral Electric Company, GE Research (Niskayuna, NY) aims to estimate then optimize heat rate for improved efficiency at part load, base load, and during transients; increase the ramp rates from part load to base load for supporting the power grid against ever-increasing intermittent energy sources; and determine the health of the major components of coal-fired power plants for improved reliability. General Electric (GE) will achieve these goals via utilization of their coal-fired power plant model library, developing controllers that predict equipment response as a function of both operating point and transient loading.

DOE Funding: $1,999,060; Non-DOE Funding: $499,765; Total Value: $2,498,825

Area of Interest 2: Power Plant Component Improvement

Subtopic 2A: High-fidelity field testing of technologies

5. Elimination of Steam Side Scaling On Grade 91 Steel, Improving Efficiency, Reliability, and Flexibility of Existing Fossil Fired Power Plants Applied Thermal Coatings (Chattanooga, TN) aims to significantly improve the reliability and efficiency of existing coal-fired power plants under flexible operating conditions by deploying a technology to modify the surface chemistry of creep-strength-enhanced steel tubing to substantially improve its steam-side oxidation resistance at a cost and scale that enables its ready acceptance for use by the power generation industry.

DOE Funding: $2,116,507; Non-DOE Funding: $533,000; Total Value: $2,649,507

6. Mitigation of Aerosol Impacts on Ash Deposition and Emissions from Coal Combustion Barr Engineering Company (Minneapolis, MN) will demonstrate the effectiveness of tailored sorbents in mitigating fouling and slagging; develop a benchmark/screening tool for identifying low-cost sorbents; and conduct a techno-economic assessment of the sorbent technology, including a pathway to commercialization.

DOE Funding: $3,996,998; Non-DOE Funding: $999,412; Total Value: $4,996,410

7. Concrete Thermal Energy Storage Enabling Flexible Operation Without Coal Plant CyclingElectric Power Research Institute (Charlotte, NC) will design, construct, and test a pilot-scale concrete thermal energy storage system (CTES) to demonstrate the energy storage potential of the technology when applied to coal-fired power units. The project aims to demonstrate that a CTES system can be integrated with a coal power plant to enable low-cost energy storage that will eliminate the need for excessive operational flexibility and ultimately improve the profitability of the plant.

DOE Funding: $3,910,720; Non-DOE Funding: $977,680; Total Value: $4,888,400

8. Plasma Ignition and Combustion Stabilization Technology to Improve Flexible Operation, Reliability and Economics of An Existing Coal-Fired BoilerGE Steam Power (Windsor, CT) aims to demonstrate improved power plant reliability, flexibility and economics at PacifiCorp Hunter in a field demonstration of the advanced new high-efficiency alternating-current plasma technology. The objective of this program is to advance the plasma ignition technology to be a fully integrated and a field proven system, so it can then be made commercially available for other coal-fired power plants.

DOE Funding: $3,615,340; Non-DOE Funding: $903,835; Total Value: $4,519,175

Subtopic 2B: Relevant environment testing of technologies

9. Investigations of Technologies to Improve Condenser Heat Transfer and Performance in a Relevant Coal-Fired Power Plant Environment Electric Power Research Institute (Palo Alto, CA) will study and demonstrate the effectiveness of modifications that may enhance the performance of heat exchanger tubes for coal-fired power plant applications. Improvements in heat transfer effectiveness could result in power plant condensers having increased efficiency, reliability, and flexibility.

DOE Funding: $2,000,000; Non-DOE Funding: $500,000; Total Value: $2,500,000

10. Flexible Coal Power Plant Operation with Thermal Energy Storage Utilizing Thermosiphons and Cementitious MaterialsLehigh University (Bethlehem, PA) will develop an optimized prototype of a solid media thermal energy storage concept for thermal management applications in coal-fired power plants. The project will involve design, engineering, optimization, and testing of the concept at laboratory- and at prototype-scale at a coal-fired power plant.

DOE Funding: $2,000,000; Non-DOE Funding: $508,039; Total Value: $2,508,039

11. Anti-Biofouling Surface Treatments for Improved Condenser Performance for Coal-Based Power PlantsResearch Triangle Institute (Research Triangle Park, NC) will design and engineer novel surface treatments and secondarily applied remediation components to mitigate biofilm growth on condenser tube surfaces used in coal-fueled power plants. Such modified surfaces can potentially disrupt the landscape for emerging anti-biofouling technologies through the creation of surface environments that interfere with abilities of bacteria to sense and respond to their environment, thereby inhibiting biofilm production and surface attachment.

DOE Funding: $1,350,537; Non-DOE Funding: $337,635; Total Value: $1,688,172

12. Environmental Validation of Materials and Design Concepts to Enable Operational Flexibility of Existing Coal Power PlantsSiemens Corporation, Corporate Technology (Charlotte, NC) will develop a holistic approach for demonstration of multiple operational methodologies and improved materials capability versus baseline to improve efficiency, reliability and flexibility of existing coal-based power plants. The proposed technical approach is focused on performance of improved materials/plant operations on small-scale pilot plant facilities at Cranfield University for power plant component improvements.

DOE Funding: $1,999,998; Non-DOE Funding: $500,000; Total Value: $2,499,998

13. Ash Fouling Free Regenerative Air Preheater for Deep Cyclic OperationUniversity of Kentucky (Lexington, KY) aims to develop a self-cleaning, ash fouling free air preheater to increase the capacity of a coal-fired power plant for load following. Increased use of alternative energy sources presents a challenge to control thermal efficiency. The proposed unit offers a solution to this, especially during deep cyclic operation and is transformative from the state-of-art regenerative heater with either hot-air recycling or a hot water recirculation system.

DOE Funding: $1,999,864; Non-DOE Funding: $500,618; Total Value: $2,500,482

Area of Interest 3: Data Analytics Driven Controls

Subtopic 3A: Adaptive data-driven approaches featuring physics-based attributes for improved flexibility, reliability and performance (referred to as ADAPT)  

14. Hybrid Analytics Solution to Improve Coal Power Plant Operations Expert Microsystem, Inc. (Orangevale, CA) will develop, demonstrate, and commercialize a novel approach to improve coal-fired power plants’ ability to follow loads and handle transient behavior by integrating two proven real-time monitoring techniques. The hybrid analytics approach integrates into a single, integrated solution, an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition, and machine-learning techniques and a well-proven, first-principle thermal heat balance model solution.

DOE Funding: $791,693; Non-DOE Funding: $197,923; Total Value: $989,616

15. Generation Plant Cost of Operations and Cycle Optimization Model National Rural Electric Cooperative Association (Arlington, VA) will develop a tool to estimate the costs of cycling boilers in large coal plants so that coal generators can be fairly considered and efficiently operated as part of a generation and dispatch strategy. The Generation Plant Cost of Operations and Cycle Optimization Model will be refined and integrated with one or more dispatch and generation planning models through an application programming interface.

DOE Funding: $2,000,000; Non-DOE Funding: $500,000; Total Value: $2,500,000

16. Boiler Health Monitoring Using a Hybrid First Principles-Artificial Intelligence Model  — West Virginia University Research Corporation (Morgantown, WV) seeks to develop methodologies and algorithms to accomplish a hybrid first-principles-AI model of the PC boiler; a physics-based approach to material damage informed by ex-service component evaluation; an online health-monitoring framework that synergistically leverages the hybrid models and plant measurements to provide the spatial and temporal profile of key transport variables and characteristic measures for plant health; and a field implementation and demonstration at Southern Company’s Plant Barry.

DOE Funding: $1,984,135; Non-DOE Funding: $524,881; Total Value: $2,509,016

Subtopic 3B: Artificial intelligence for enhanced data analytics and control of coal-based power plants

17. Deep Analysis Net with Causal Embedding for Coal-Fired Power Plant Fault Detection and Diagnosis — General Electric Company, GE Research (Niskayuna, NY) will develop Deep Analysis Net with Causal Embedding for Coal-Fired Power Plant Fault Detection and Diagnosis—a novel end-to-end trainable artificial intelligence-based multivariate time series learning system for flexible and scalable coal power plant fault detection and root cause analysis (i.e., diagnosis).

DOE Funding: $1,999,853; Non-DOE Funding: $499,963; Total Value: $2,499,816