Due to its high efficiency and low environmental impact, fuel cell is regarded as one of the key alternative energy sources. As the fuel cell for power plants is a relatively expensive and specialized product compared to other renewable energy systems, it is important to enter a long-term service agreement (LTSA), a contract in which the generators pay a certain fee to the sellers for guaranteed electricity generation, so that generators can operate the fuel cell power plant without anxiety. The sellers and generators with trade-off relationships in their profits, however, suffer economic losses due to the uncertain factors (e.g., stack life, stack replacement cost, etc.) of the fuel cell system. Therefore, this study aimed to determine the optimal LTSA period and cost considering (i) the economic feasibility of the two participants (i.e., sellers and generators); and (ii) the uncertain factors of the fuel cell system (i.e., the 2.5 MW molten carbonate fuel cell (MCFC) system). Towards this end, this study selected uncertain factors affecting the profitability of sellers and generators using sensitivity analysis, and conducted probabilistic life cycle cost (LCC) analysis using Monte Carlo simulation (MCS). As a result, the range of the optimal LTSA for sellers and generators was determined to be as follows: (i) LTSA period: 6–20 years; and (ii) LTSA cost: US$510,204/year to US$1,623,377/year. The analysis results of this study showed that the proposed optimal LTSA range could be used for sellers and generators as a decision support tool in the fuel cell market. The novel method that was used in this study could be applied in various fields for selecting the optimal LTSA period and cost considering the profitability of each stakeholder and the uncertain factors.
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT; Ministry of Science and ICT) ( NRF-2018R1A2A1A19020868 ).
© 2019 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Building and Construction
- Mechanical Engineering
- Management, Monitoring, Policy and Law