Applying Learning Curves to Modeling Future Coal and Gas Power Generation TechnologiesClick to copy article linkArticle link copied!
Abstract
Coal and natural gas have and will likely continue to be key components of the world energy supply for years to come. Currently, the most efficient commercial technologies for power production are supercritical pulverized coal combustion (SCPC) and natural gas combustion with combined cycle (NGCC). Emerging technologies for more efficient power generation from coal include ultra-super-critical pulverized coal (USCPC), advanced ultra-super-critical PC, integrated gasification combined cycle (IGCC), integrated gasification fuel cell combined cycle (IGFC), and direct carbon fuel cell. They each have different capital and operating costs leading to different levelized cost of electricity (LCOE). To forecast each of these competing technologies under various scenarios of electricity demand, fuel cost, and research investment, we created a Power Technology Futures Model (PTFM) based on “learning curves” methodology. Technology learning curves are a powerful tool for forecasting anticipated performance improvements due to a broad range of technical improvements without specifying the parameters of every possible improvement. The model can help planners and policy makers explore, visualize, and communicate how research and development (R&D) investments in certain technologies affect the mix of technologies deployed in the future. We utilized the Analytica modeling package and included detailed economic calculations to estimate the levelized costs for several types of coal and natural gas power plants with and without carbon capture technologies. Future improvements in plant efficiency and reductions in capital and operating and mantainence (O&M) costs were modeled using technology learning curves that were established by a detailed analysis of historic performance data. We used published estimates of future demand and fuel costs where available, but the model allows the user to easily input other numbers as tables or equations. Adoption of carbon capture was modeled in a variety of ways including being driven by a carbon cap or a carbon tax. The results of the model depict the difficulty of meeting a 50% reduction in annual CO2 production by 2050, even with significant R&D investments, ambitious CO2 pricing, and decreased demand for energy from coal and natural gas.
Cited By
Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by ACS Publications if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles.
This article is cited by 9 publications.
- Bipin S. Chikkatti, Ashok M. Sajjan, Nagaraj R. Banapurmath, Javed Khan Bhutto, Rajesh Verma, T. M. Yunus Khan. Fabrication of Flexible Films for Supercapacitors Using Halloysite Nano-Clay Incorporated Poly(lactic acid). Polymers 2023, 15
(23)
, 4587. https://doi.org/10.3390/polym15234587
- Santosh K. Singh, Vishal M. Dhavale, Rabah Boukherroub, Sreekumar Kurungot, Sabine Szunerits. N-doped porous reduced graphene oxide as an efficient electrode material for high performance flexible solid-state supercapacitor. Applied Materials Today 2017, 8 , 141-149. https://doi.org/10.1016/j.apmt.2016.10.002
- Hirotatsu Watanabe, Daisuke Umehara, Katsunori Hanamura. Impact of gas products around the anode on the performance of a direct carbon fuel cell using a carbon/carbonate slurry. Journal of Power Sources 2016, 329 , 567-573. https://doi.org/10.1016/j.jpowsour.2016.08.122
- Jessica R. Lovering, Arthur Yip, Ted Nordhaus. Historical construction costs of global nuclear power reactors. Energy Policy 2016, 91 , 371-382. https://doi.org/10.1016/j.enpol.2016.01.011
- Adam C. Rady, Sarbjit Giddey, Aniruddha Kulkarni, Sukhvinder P.S. Badwal, Sankar Bhattacharya, Bradley P. Ladewig. Direct carbon fuel cell operation on brown coal. Applied Energy 2014, 120 , 56-64. https://doi.org/10.1016/j.apenergy.2014.01.046
- L. Deleebeeck, K. K. Hansen. Hybrid direct carbon fuel cells and their reaction mechanisms—a review. Journal of Solid State Electrochemistry 2014, 18
(4)
, 861-882. https://doi.org/10.1007/s10008-013-2258-1
- L. Deleebeeck, K. Kammer Hansen. HDCFC Performance as a Function of Anode Atmosphere (N
2
-CO
2
). Journal of The Electrochemical Society 2014, 161
(1)
, F33-F46. https://doi.org/10.1149/2.027401jes
- Takashi Nakamura, Keiji Makino, Kunihiko Shibata, Michiaki Harada. Forecast of Advanced Technology for Coal Power Generation Towards the Year of 2050 in CO2 Reduction Model of Japan. Energy Procedia 2013, 37 , 7557-7564. https://doi.org/10.1016/j.egypro.2013.06.699
- Brad Carson. The Economics of Renewable Energy. SSRN Electronic Journal 2012, 5 https://doi.org/10.2139/ssrn.2014773
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.
Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.
The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.