Session: 17-13-01: Plant Performance, Fluid Dynamics and Thermal Hydraulics in Energy and Power Applications

Paper Number: 165032

Real-Time Assessment of the Influence of Fuel Moisture on Coal-Fired EGU Heat Rate 

This paper employs an on-line method to assess the boiler efficiency and heat rate of a coal-fired electric generating unit. By utilizing flue gas oxygen concentration measurements on both a dry and wet basis at the economizer exit, it is possible to instantaneously quantify the coal moisture in real-time as it is burned. Most EGUs currently do not perform such measurements concurrently, but installation of the necessary instrumentation is presumably straightforward and relatively inexpensive. Accurate, robust, and affordable methods to monitor fuel moisture in real-time are currently unavailable. Hence the approach advocated in this study obviates the need to utilize such unreliable technology to monitor fuel moisture in real-time. Otherwise, the methodology proposed in this study utilizes existing plant instrumentation, and so doesn’t require extensive retrofits for most EGUs. It is shown that this approach is capable of predicting the as-fired coal composition over a range of boiler loads, provided that accurate continuous emissions monitoring systems data are available. This is particularly true for the case where the load is maintained at its nominal value, which corresponds to the condition at which the plant is typically operated. An uncertainty study is performed, wherein the economizer exit dry basis oxygen concentration measurement is deemed to be exact, but the corresponding wet basis measurements are subject to a presumed inaccuracy of ±2%. This analysis demonstrates that such wet basis oxygen concentration measurement uncertainties yield predictions of fuel moisture that exhibit considerable variations from the genuine value. However, this had a relatively insignificant impact on calculated EGU performance parameters such as boiler efficiency and heat rate. This is compatible with observations from previous investigations where it was suggested that measurement errors associated with the steam heat transfer rate, the coal mass flowrate, and the carbon dioxide concentration at the economizer exit, had the most consequential influence on predicted real-time EGU performance. Since the predicted fuel moisture varied depending on the presumed wet basis oxygen measurement accuracy, this study explicitly takes into account the influence of fuel moisture on coal higher heating value. However, the CEMS-based performance approach utilizing simultaneous dry and wet basis oxygen concentration measurements at the economizer exit is capable of measuring thermal performance of the plant in real-time, provided that the coal higher heating value is accurately known. Application of the real-time CEMS-based algorithm informs plant operators as they make control decisions regarding how to improve the heat rate of a particular EGU, and therefore helps a utility company to decide which plant should function at full or part load as electricity demand changes.

Presenting Author: Robert Craven Tennessee Tech Univ

Presenting Author Biography: Robert P.M. Craven
Email rcraven@tntech.edu ; Tel (931) 372-3487;
1020 Stadium Drive, PRSC 233 CESR Box 5032., Cookeville, TN 38505

Professional Preparation:
West Virginia University, Morgantown, WV; Bachelor of Science in Chemical Engineering (September 1980-August 1984).

Appointments:
R&D Engineer, Tennessee Tech University (October 2000, present) - Build new capabilities, maintain functionality, and perform research in a Smart Grid Laboratory. ARC HILLTOP researcher and modeler. Advance the smart agent rebirth of the scale model power grid consisting of multiple generators, multiple bus systems, multiple impedance lines, loads etc. with an in house developed SCADA and data historian. This permits real-world research on a laboratory power grid which can either be connected to the big grid or kept separate to research self-healing grids, fault tolerance, protection renewable integration, and battery storage. https://www.tntech.edu/engineering/research/cesr/smartgrid/
o Work with Dr. VanNeste in Quasi-Wireless Capacitive Power
o Mentor students in their research topics.
o Maintain power-plant heatrate code, including customization for various power-plants. Requires travel, meeting with sponsors, programming in C, C++, and Visual Basic.
o Setup data-acquisition systems for laboratories.

Research Associate, West Virginia University (1990-2000) - Designed and developed software for on-the-road heavy duty diesel engine emissions measurement, including analog measurements of temperature, pressure, flow, etc. and digital measurements from global positioning satellite receivers, engine electronic control units, and emissions measurement instruments. Results were post processed and then stored in a database for further studies and reports. Also worked on many patented inventions and mentored numerous students in their research.

Publications (Ten Total):
Products Most Closely Related (10 total)
• Rajesh Manicavasagam, Anthony Palmer, Mike Rogers, Satish Mahajan, Robert Craven, Chikezie Emeghara and Ryan Senz, “Testbed for Evaluating and Analyzing Smart Grid Behavior in Demand Response Scenarios”, Nov 18 2022 14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), IEEE
• Robert Craven, Keith Kirkpatrick, Stephen Idem; “Combustion Turbine Exhaust Duct, Silencer, and Stack Scale Modeling”, Power2021-64118, July 20-22, 2021, Online Virtual Proceedings of the ASME 2021 Power Conference
• Charles A. Robinson, Brandon T. Nieman, Robert Craven, Muhammed Enagi Bima, C.W. Van Neste, “Development of a Wireless Power Transmission System for Agriculture Sensor Devices”, 2020 IEEE International Conference on Big Data, paper ID: s09204, Dec 10-13, 2020
• “Adaptive Immune System Reinforcement Learning-Based algorithm for real-time Cascading Failures prevention”, Babalola, Adeniyi Abdulrasheed; Belkacemi, Rabie; Zarrabian, Sina; Craven, Robert, Engineering Applications of Artificial Intelligence, January 2017, Vol.57, pp.118-133 Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, TN 38505, USA
• “Simulation of load-sharing in standalone distributed generation system,” Titus O Ajewole, Robert P M Craven, Olakunle Kayode, and Olufisayo S Babalola, 2018 7th International Conference on Clean and Green Energy-ICCGE 2018, Paris, France, February 7, 2018
• “AIS-MAS Algorithm for Cascading Failures Prevention in Power Systems,” Adeniyi Babalola, Dr. Rabie Belkacemi, Sina Zarrabian, and Robert Craven, IEEE PES GM, Denver Co, July 26 2015
• “Development of a Real Time Wind Turbine Emulator based on RTDS using Advanced Perturbation Methods,” (R. V. Gokhale, B. Abegaz, R. Craven, and S. M. Mahajan), Proceedings of the International Conference on Environment and Electrical Engineering, EEEIC, Rome Italy, June 2015.
• “Experimental Transient Stability Analysis of MicroGrid Systems: lessons learned,” R. Belkacemi, S. Zarrabian, A. Babalola and R. Craven, in IEEE Power and Energy Society General Meeting, 2015.
• “Multi-Agent System Algorithm for Preventing Cascading Failures in Smart Grid Systems,” R. Belkacemi, A. Babalola, S. Zarrabian and R. Craven, in North American Power Symposium, Pullman, WA., Sept. 2014, pp. 1-6.
• “Microgrid-tied Solar Power Generation using Three-Phase IGBT Inverter” by Funso Ariyo and Robert Craven, poster session, IEEE SouthEastCon 2014

Authors:

Robert P. M. Craven Tennessee Tech Univ
Sastry Munukutla Tennessee Tech University
Stephen Idem Tennessee Tech University