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A Total Cost of Ownership Model for Solid Oxide Fuel Cells in Combined Heat and Power and Power- Only Applications

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A Total Cost of Ownership Model for Solid Oxide Fuel Cells in Combined Heat and Power and Power- Only Applications ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY A Total Cost of Ownership Model for Solid Oxide Fuel Cells in Combined Heat and Power and Power- Only Applications Roberto Scataglini, Ahmad Mayyas1, Max Wei, Shuk Han Chan2, Timothy Lipman1, David Gosselin2, Anna D’Alessio2, Hanna Breunig, Whitney G. Colella3, and Brian D. James3 Environmental Energy Technologies Division December 2015 1University of California, Berkeley, Transportation Sustainability Research Center, Berkeley, California 2University of California, Berkeley, Laboratory for Manufacturing and Sustainability, Department of Mechanical Engineering, Berkeley, California 3Strategic Analysis, Inc. (SA), Energy Services Division, 4075 Wilson Blvd., Suite 200, Arlington VA 22203 This work was supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE) Fuel Cells Technologies Office (FCTO) under Lawrence Berkeley National Laboratory Contract No. DE-AC02- 05CH11231 i DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or The Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or The Regents of the University of California. Ernest Orlando Lawrence Berkeley National Laboratory is an equal opportunity employer. ii ACKNOWLEDGEMENTS The authors gratefully acknowledge the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE) Fuel Cells Technologies Office (FCTO) for their funding and support of this work. The authors would like to thank the following individuals and companies for their expert input on SOFC system designs, system specifications, and manufacturing equipment and processes. • Brian Borglum, Fuel Cell Energy • SOFCpower, Mezzolombardo, Italy • Minh Nguyen, University of California, San Diego • Professor Massimo Santarelli, Polytechnic University of Turin, Italy • Professor Jack Brouwer, University of California, Irvine • Patricia Irving, InnovaTek • Jim W. Dennis, HED international, Inc. • Dixita Bhat, Bionics Scientific Technologies Pvt. Ltd. • Mathias Rachau, FuelCon AG • Alexey Peshkovsky, Industrial Sonomechanics, LLC • Martin De Moya, Haiku Tech, Inc. • Edward Stone, Manncorp • Charles H. Birks, Keith Company • Fabio Pagnotta, Aurel Automation S.p.A • Donald Wang, Ph.D., Inframat Advanced Materials • Nickle Shang, Qingdao Terio Corporation • Dick Wildman, Dowd and Guild Inc. • Chris Betz, CHEMPOINT Inc. • Matthew Dickerson, American Chemical Inc. • Christian Ames, Univar USA iii Executive Summary A total cost of ownership model (TCO) is described for emerging applications in stationary fuel cell systems. Solid oxide fuel cell systems (SOFC) for use in combined heat and power (CHP) and power- only applications from 1 to 250 kilowatts-electric (kWe1) are considered. The total cost of ownership framework expands the direct manufacturing cost modeling framework of other studies to include operational costs and life-cycle impact assessment of possible ancillary financial benefits during operation and at end-of-life. These include credits for reduced emissions of global warming gases such as carbon dioxide (CO2) and methane (CH4), reductions in environmental and health externalities, and end-of-life recycling. System designs and functional specifications for SOFC fuel cell systems (FCS) for CHP and power-only applications were developed across the range of system power levels above. Bottom-up cost estimates were made based on currently installed fuel cell systems for balance of plant (BOP) costs, and detailed design-for-manufacturing-and-assembly2 (DFMA) cost analysis was carried out to estimate the direct manufacturing costs for key fuel cell stack components. The costs of the fuel processor subsystem are also based on a DFMA analysis (James et. al., 2012). The development of high throughput, automated processes achieving high yield are estimated to push the direct manufacturing cost per kWe for the SOFC fuel cell stack to $370/kWe and $180/kWe for a 10-kWe system at 1,000 units per year and 50,000 units per year, respectively. The sub-$200/kWe stack cost projection is below the high volume $238/kWe stack cost target set by the National Energy Technology Laboratory (NETL 2013). Overall system costs including a 50% corporate markup are estimated to be $2380/kWe and $1660/kWe for a 10-kWe system, again at 1000 units per year and 50,000 units per year, respectively. The high volume system cost meets the U.S. Department of Energy’s (DOE) 2020 target of $1700/kWe for 10-kWe fuel cell CHP systems (DOE 2014). At high production volume, material costs make up the largest component of stack costs (up to 59% of overall stack direct cost at highest modeled volume). Based on the decline in stack costs at moderate to larger production volumes, we find that BOP costs (including the fuel processor) dominate overall system direct costs for CHP systems and are thus a key area for further cost reduction. For CHP systems at low power, the fuel processing and electrical power subsystems are the largest cost contributor of total non-stack costs. At high power, the electrical power subsystem is the dominant cost contributor. In this round of cost estimates, a DFMA analysis was not applied to the non-fuel processor balance of plant components and cost estimates were based on industrial price quotes. It is expected that a full DFMA analysis of the non-fuel processor balance of plant components could show a greater trend towards cost reduction with increases in production volume. Life-cycle or use-phase modeling and life cycle impact assessment (LCIA) were carried out for two building types (small hotels and hospitals) in six U.S. cities. At an annual production volume of 100 MWe (e.g., 10-kWe systems at 10,000 units per year or 50-kWe system at 2,000 units per year), life cycle costs for SOFC systems are competitive with grid-based electricity and conventional heating in many parts of the country with the modeled SOFC costs here as an input. In regions in the U.S. with 1 In this report, units of kWe stand for net kW electrical power unless otherwise noted. 2 DFMA is a registered trademark of Boothroyd, Dewhurst, Inc. and is the combination of the design of manufacturing processes and design of assembly processes for ease of manufacturing and assembly and cost reduction. iv high-carbon intensity electricity from the grid3, total cost of ownership credits can further reduce the levelized cost of electricity for buildings with fuel cell CHP. TCO costs for fuel cell CHP systems are dependent on several factors such as the cost of natural gas, utility tariff structure, amount of waste heat utilization, carbon intensity of displaced electricity and conventional heating, carbon price, and valuation of health and environmental externalities. These factors typically depend on geographic location of the CHP installation. For example, a fuel cell CHP system that displaces a large quantity of fossil heating fuel such as heating oil will have a larger environmental benefit than one that displaces natural gas heating fuel. As with CHP systems in general, regions with a higher spark spread are more economically favorable4. Quantification of externality damages to the environment and public health utilized earlier environmental impact assessment work and datasets available at LBNL. Overall, this type of total cost of ownership analysis quantification is important to identify key opportunities for direct cost reduction, to fully value the costs and benefits of fuel cell systems in stationary applications, and to provide a more comprehensive context for future potential policies. 3 In this work, different marginal emissions factors for CO2, NOx, and SO2 from grid-based electricity are assumed for each of the eight North American Electric Reliability Corporation (NERC) regions in the United States (Siler- Evans et al. 2012). 4 Spark spread is defined as follows: SS = Price of Electricity - [(Price of Gas) * (Heat Rate) ] = $/MWh - [($/MMBtu) * (MMBtu / MWh) ], or equivalently, the theoretical gross margin of a gas-fired power plant from selling a unit of electricity. Heat rate is often taken as 2.0 by convention for gas-fired plants. CHP systems powered by natural gas are more economically favorable in regions with large spark spread. v Table of Contents 1 Introduction .................................................................................................................................................. 1 1.2 Emerging applications ............................................................................................................................ 3 1.3 Total Cost of Ownership Modeling .......................................................................................................
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