Estimation of a predictable coal power plants carbon tax

2016 ◽  
Vol 5 ◽  
pp. 9-13
Author(s):  
Maxim S. Ivanitsky
2020 ◽  
Vol 24 (3) ◽  
pp. 104-111
Author(s):  
Alexander Kler ◽  
Pavel Zharkov ◽  
Yulia Potanina ◽  
Andrey Marinchenko ◽  
Nikolai Epishkin

AbstractThe paper investigates the effect of the carbon tax on the optimal parameters and indicators of two coal power plants: a steam turbine power unit with coal dust burning in a steam boiler and an internal gasification combined cycle power plant. Sufficiently detailed mathematical models have been developed for the considered plants that are focused on calculating the flow rates of working fluids and coolants and thermodynamic parameters at all points of the flowcharts, as well as the structural characteristics of the plant elements. The problems of optimizing the parameters of these plants related to the problems of nonlinear mathematical programming are formulated. As an efficiency criterion, the price of electricity is used at given value of the internal rate of return on investment. Optimization calculations were carried out with a carbon tax in the range from 0 $/t to 140 $/t in increments of 20 $/t. It is shown that with an increase in the charge for emissions, the optimal efficiency of the plants increases, as well as the specific investment. Specific CO2 emissions are reduced. Throughout the entire range of carbon tax values, IGCC power plant has the best economic and environmental indicators.


2012 ◽  
Author(s):  
Mark Woods ◽  
Michael Matuszewski ◽  
Robert Brasington

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2389
Author(s):  
Samuel Matthew G. Dumlao ◽  
Keiichi N. Ishihara

Despite coal being one of the major contributors of CO2, it remains a cheap and stable source of electricity. However, several countries have turned to solar energy in their goal to “green” their energy generation. Solar energy has the potential to displace coal with support from natural gas. In this study, an hourly power flow analysis was conducted to understand the potential, limitations, and implications of using solar energy as a driver for decommissioning coal power plants. To ensure the results’ robustness, the study presents a straightforward weather-driven scenario analysis that utilizes historical weather and electricity demand to generate representative scenarios. This approach was tested in Japan’s southernmost region, since it represents a regional grid with high PV penetration and a fleet of coal plants older than 40 years. The results revealed that solar power could decommission 3.5 GW of the 7 GW coal capacity in Kyushu. It was discovered that beyond 12 GW, solar power could not reduce the minimum coal capacity, but it could still reduce coal generation. By increasing the solar capacity from 10 GW to 20 GW and the LNG quota from 10 TWh to 28 TWh, solar and LNG electricty generation could reduce the emissions by 37%, but the cost will increase by 5.6%. Results also show various ways to reduce emissions, making the balance between cost and CO2 a policy decision. The results emphasized that investing in solar power alone will not be enough, and another source of energy is necessary, especially for summer and winter. The weather-driven approach highlighted the importance of weather in the analysis, as it affected the results to varying degrees. The approach, with minor changes, could easily be replicated in other nations or regions provided that historical hourly temperature, irradiance, and demand data are available.


2021 ◽  
Vol 1101 (1) ◽  
pp. 012012
Author(s):  
Salmia Beddu ◽  
Mahyun Zainoodin ◽  
Amalina Basri ◽  
Zarina Itam ◽  
Raudhah Ahmadi ◽  
...  

2017 ◽  
Vol 105 ◽  
pp. 297-302 ◽  
Author(s):  
Arif Darmawan ◽  
Dwika Budianto ◽  
Muhammad Aziz ◽  
Koji Tokimatsu

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