Proton exchange membrane fuel cells (PEMFCs) are one of the leading candidates in alternative energy conversion devices for transportation, stationary, and portable power generation applications. Such systems with their own fuel conversion unit typically consist of several subsystems: a fuel processing subsystem, a fuel cell stack subsystem, a work recovery-air supply subsystem, and a power electronics subsystem. Since these subsystems have different physical characteristics, their integration into a single system/subsystem level unit make the problems of optimal dynamic system synthesis/design and operation/control highly complex. Thus, dynamic system/subsystem/component modeling and highly effective optimization strategies are required. Furthermore, uncertainties in the results of system synthesis/design and operation/control optimization can be affected by any number of sources of uncertainty such as the load profiles and cost models. These uncertainties can be taken into account by treating the problem probabilistically. The difficulty with doing this, particularly when large-scale dynamic optimization with a large number of degrees of freedom is being used to determine the optimal synthesis/design and operation/control of the system, is that the traditional probabilistic approaches (e.g., Monte Carlo Method) are so computationally intensive that combined with large-scale optimization it renders the problem computationally intractable. This difficulty can be overcome by the use of approximate approaches such as the response sensitivity analysis (RSA) method based on Taylor series expansion. Thus, in this paper, a stochastic modeling and uncertainty analysis methodology for energy system synthesis/design and operation/control which uses the RSA method is proposed and employed for calculating the uncertainties on the system outputs. Their effects on the synthesis/design and operation/control optimization of a 5kWe PEMFC system are assessed by taking the uncertainties into account in the objectives and constraints. It is shown that these uncertainties significantly affect the reliability of being able to meet certain constraints (e.g., that on the CO concentration) during the synthesis/design and operation/control optimization process. These and other results are presented.
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ASME 2008 International Mechanical Engineering Congress and Exposition
October 31–November 6, 2008
Boston, Massachusetts, USA
Conference Sponsors:
- ASME
ISBN:
978-0-7918-4869-2
PROCEEDINGS PAPER
Dynamic Synthesis/Design and Operation/Control Optimization Under Uncertainty of a PEMFC System Available to Purchase
Kihyung Kim,
Kihyung Kim
Virginia Polytechnic Institute and State University, Blacksburg, VA
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Meng Wang,
Meng Wang
Virginia Polytechnic Institute and State University, Blacksburg, VA
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Michael R. von Spakovsky,
Michael R. von Spakovsky
Virginia Polytechnic Institute and State University, Blacksburg, VA
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Douglas J. Nelson
Douglas J. Nelson
Virginia Polytechnic Institute and State University, Blacksburg, VA
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Kihyung Kim
Virginia Polytechnic Institute and State University, Blacksburg, VA
Meng Wang
Virginia Polytechnic Institute and State University, Blacksburg, VA
Michael R. von Spakovsky
Virginia Polytechnic Institute and State University, Blacksburg, VA
Douglas J. Nelson
Virginia Polytechnic Institute and State University, Blacksburg, VA
Paper No:
IMECE2008-68070, pp. 679-689; 11 pages
Published Online:
August 26, 2009
Citation
Kim, K, Wang, M, von Spakovsky, MR, & Nelson, DJ. "Dynamic Synthesis/Design and Operation/Control Optimization Under Uncertainty of a PEMFC System." Proceedings of the ASME 2008 International Mechanical Engineering Congress and Exposition. Volume 8: Energy Systems: Analysis, Thermodynamics and Sustainability; Sustainable Products and Processes. Boston, Massachusetts, USA. October 31–November 6, 2008. pp. 679-689. ASME. https://doi.org/10.1115/IMECE2008-68070
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