Title :
Option-game-based method for generation investment analysis considering uncertain carbon reduction policy in the electricity market
Author :
Liu, Guo-Ping ; Zhao, Jun Hua ; Wen, Fushuan ; Yin, X. ; Dong, Zhao Yang
Author_Institution :
Sch. of Electr. Eng., South China Univ. of Technol., Guangzhou, China
fDate :
8/1/2010 12:00:00 AM
Abstract :
Greenhouse gas, especially CO2, emissions impact on global climate has been widely recognised. Emissions reduction has become an important issue. Efforts have been made globally in establishing emission policies and protocols. However, considering the fact that different countries have different carbon reduction schemes, and significant variations are still possible for existing schemas, future CO2 prices can be highly uncertain. The power generation sector will be significantly affected by changing policies and therefore significant uncertainties will be involved in the operation and investment processes. Moreover, investments in thermal power plants are also influenced by many other uncertain factors such as fuel prices, spot electricity prices and the investment behaviours of rival generation companies. An appropriate method is urgently needed to model these uncertainties in the investment process. A novel framework of generation investment decision-making is proposed herewith. The option game theory is employed to handle multiple uncertain factors. The investment decision making will be solved with a Barraquand-Martineau option pricing model-based method. Case studies are conducted to assess the performance of the proposed framework.
Keywords :
air pollution control; game theory; investment; power generation economics; power markets; pricing; thermal power stations; Barraquand-Martineau option pricing model-based method; carbon dioxide emissions; electricity market; generation investment analysis; generation investment decision-making; global climate; greenhouse gas emissions; option-game-based method; thermal power plants; uncertain carbon reduction policy;
Journal_Title :
Generation, Transmission & Distribution, IET
DOI :
10.1049/iet-gtd.2009.0439