Prediction of Carbon Price in EU-ETS Using a Geometric Brownian Motion Model and Its Application to Analyze the Economic Competitiveness of Carbon Capture and Storage

Gwang Goo Lee () and Sung-Won Ham
Additional contact information
Gwang Goo Lee: Department of Mechanical Engineering, Keimyung University, 1095 Dalgubeol-daero, Dalseo-gu, Daegu 42601, Republic of Korea
Sung-Won Ham: Department of Chemical Engineering, Kyungil University, 50 Gamasil-gil, Hayang-eup, Gyeongsan 38428, Republic of Korea

Energies, 2023, vol. 16, issue 17, 1-13

Abstract: To achieve carbon neutrality, many countries and regions are making efforts to promote the commercialization of greenhouse gas (GHG) mitigation technologies using emissions trading systems (ETSs). Accurate predictions of when the cost of GHG reduction technologies will become competitive below carbon prices could be invaluable to engineers and policy makers. In this study, carbon price movement in the EU-ETS was analyzed using a geometric Brownian motion (GBM) model. Using daily price data for the last 10 years, it tested whether the price pattern of the latter three years could be predicted by applying the first seven years of data to the GBM model. The results showed that the GBM model could well predict the upper and lower bounds of the actual carbon price. Based on the acceptable predictability of the GBM model, simulations were performed using carbon price data over the last decade, showing that carbon prices would reach around 200 EUR/tCO 2 by the start of 2026. This is higher than the cost of CO 2 avoided evaluated from the costs of commercial-scale carbon capture facilities for coal-fired power plants. This means that carbon capture technologies in the coal-fired power sector could become economically competitive within the next several years.

Keywords: EU emission trading system (EU-ETS); geometric Brownian motion (GBM); coal-fired power plant; carbon capture and storage (CCS); cost of CO 2 avoided (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/17/6333/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/17/6333/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:17:p:6333-:d:1230219

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().