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Part II of II: Deployment of MERESS Model—Designing, Controlling, and Installing Stationary Combined Heat and Power (CHP) Fuel Cell Systems (FCS) to Reduce Costs and Greenhouse Gas (GHG) Emissions

[+] Author Affiliations
Whitney G. Colella

Sandia National Laboratories, Albuquerque, NM

Stephen H. Schneider, Aditya Jhunjhunwala, Nigel Teo

Stanford University, Stanford, CA

Daniel M. Kammen

University of California - Berkeley, Berkeley, CA

Paper No. FuelCell2008-65113, pp. 563-589; 27 pages
  • ASME 2008 6th International Conference on Fuel Cell Science, Engineering and Technology
  • ASME 2008 6th International Conference on Fuel Cell Science, Engineering and Technology
  • Denver, Colorado, USA, June 16–18, 2008
  • Conference Sponsors: Nanotechnology Institute
  • ISBN: 0-7918-4318-1 | eISBN: 0-7918-3822-6
  • Copyright © 2008 by ASME


The Maximizing Emission Reductions and Economic Savings Simulator (MERESS) is an optimization tool that allows users to evaluate avant-garde strategies for installing and operating combined heat and power (CHP) fuel cell systems (FCSs) in buildings. This article discusses the deployment of MERESS to show illustrative results for a California campus town, and, based on these results, makes recommendations for further installations of FCSs to reduce greenhouse gas (GHG) emissions. MERESS is used to evaluate one of the most challenging FCS types to use for GHG reductions, the Phosphoric Acid Fuel Cell (PAFC) system. These PAFC FCSs are tested against a base case of a CHP combined cycle gas turbine (CCGT). Model results show that three competing goals (GHG emission reductions, cost savings to building owners, and FCS manufacturer sales revenue) are best achieved with different strategies, but that all three goals can be met reasonably with a single approach. According to MERESS, relative to a base case of only a CHP CCGT providing heat and electricity with no FCSs, the town achieves the highest 1) GHG emission reductions, 2) cost savings to building owners, and 3) FCS manufacturer sales revenue each with three different operating strategies, under a scenario of full incentives and a $100/tonne carbon dioxide (CO2 ) tax (Scenario D). The town achieves its maximum CO2 emission reduction, 37% relative to the base case, with operating Strategy V: stand alone operation (SA), no load following (NLF), and a fixed heat-to-power ratio (FHP) [SA, NLF, FHP] (Scenario E). The town’s building owners gain the highest cost savings, 25%, with Strategy I: electrically and thermally networked (NW), electricity power load following (ELF), and a variable heat-to-power ratio (VHP) [NW, ELF, VHP] (Scenario D). FCS manufacturers generally have the highest sales revenue with Strategy III: NW, NLF, with a fixed heat-to-power ratio (FHP) [NW, NLF, FHP] (Scenarios B, C, and D). Strategies III and V are partly consistent with the way that FCS manufacturers design their systems today, primarily as NLF with a FHP. By contrast, Strategy I is avant-garde for the fuel cell industry, in particular, in its use of a VHP and thermal networking. Model results further demonstrate that FCS installations can be economical for building owners without any carbon tax or government incentives. Without any carbon tax or state and federal incentives (Scenario A), Strategy I is marginally economical, with 3% energy cost savings, but with a 29% reduction in CO2 emissions. Strategy I is the most economical strategy for building owners in all scenarios (Scenarios A, B, C, and D) and, at the same time, reasonably achieves other goals of large GHG emission reductions and high FCS manufacturer sales revenue. Although no particular building type stands out as consistently achieving the highest emission reductions and cost savings (Scenarios B-2 and E-2), certain building load curves are clear winners. For example, buildings with load curves similar to Stanford’s Mudd Chemistry building (a wet laboratory) achieve maximal cost savings (1.5% with full federal and state incentives but no carbon tax) and maximal CO2 emission reductions (32%) (Scenarios B-2 and E-2). Finally, based on these results, this work makes recommendations for reducing GHG further through FCS deployment. (Part I of II articles discusses the motivation and key assumptions behind the MERESS model development (Colella 2008).)

Copyright © 2008 by ASME



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