Total Environmental Assessment of Life Cycle Impact for Power Generation in Japan

2006 ◽  
Author(s):  
Yucho Sadamichi ◽  
Naoki Maruyama ◽  
Akira Nishimura ◽  
Seizo Kato
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Environmental Assessment ◽  
Life Cycle Impact

scholarly journals Developing a Novel Environmental Assessment Model for Power Generation Plants

2018 ◽  
Author(s):  
Ndala Y. Mulongo ◽  
Cliton Aigbavboa
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Environmental Assessment ◽  
Renewable Energy Sources ◽  
Ecological Impacts ◽  
Assessment Model ◽  
Raw Material ◽  
Solar Thermal ◽  
Coal Gas ◽  
Life Cycle Stages

Environmental assessment is a concept that has been designed to facilitate the present generation to meet their needs without compromising the ability of future generations to meet their own needs as well. Thus, this concept has drawn significant attention from various scholars, researchers and industrial practitioners around the world over the past three decades. Life Cycle Environmental Assessment (LCEA) is a widely metric used to assess the potential ecological impacts, which can be caused by electricity generating supply systems or by other systems than power production plants. However, the current LCEA model is biased and ineffective. Because, its omits factors that are increasingly contributing to the ecological degradation. This study has identified the omitted factors through a critical analysis of a set of previous journal articles conducted in the energy sector. In light of this, this study has developed a novel LCEA framework addressing those blind spots. The framework developed in this study is holistic in nature including all the life cycle stages of a power supply system such as Extraction of the Raw Material (ERM), Transport of Raw Material (TRM), Conversion of Raw into Electricity (CRE), and Transmission and Distribution of Electricity (TDE) to the end users. The novel developed LCEA model has been tested and applied to nine power generation plants such as coal, gas, nuclear, biomass, geothermal, hydro, solar thermal, wind onshore and wind offshore. The results have demonstrated that of conventional technologies including coal, gas, and nuclear, coal energy generating source has got the highest life cycle greenhouse gas Grid Emission Factor (GEF) of 2866 kg CO2e/MWh, followed by gas with 728 kg CO2e/MWh, and nuclear has got the least GEF of 35 kg CO2e/MWh. Whereas of renewable energy sources biomass has got the highest GEF of 1508 kg CO2e/MWh, followed by solar thermal with 46.6 kg CO2e/MWh, hydro 39 kg CO2e/MWh, wind offshore 25.25 kg CO2e/MWh, wind onshore 10.1 kg CO2e/MWh, and geothermal closes the ranking with 6.23 kg CO2e/MWh.

PADDY RESIDUE AS FEEDSTOCK IN ELECTRICITY GENERATION: REDEMPTION OF LIFE CYCLE EMISSIONS AND COST ANALYSIS

2018 ◽  
Vol 13 (Number 1) ◽  
pp. 55-67
Author(s):  
Shafini M. Shafie ◽  
Zakirah Othman ◽  
N Hami
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Cost Analysis ◽  
Positive Feedback ◽  
Energy Supply ◽  
Electricity Generation ◽  
Economic Sector ◽  
Ghg Emission ◽  
Coal Fuel ◽  
Biomass Resources

Malaysia has an abundance of biomass resources that can be utilised for power generation. One of them is paddy residue. Paddy residue creates ahuge potential in the power generation sector. The consumption of paddy residue can help Malaysia become less dependent on conventional sources of energy, mitigate greenhouse gas(GHG) emission, offer positive feedback in the economic sector, and at the same time, provide thebest solution for waste management activities. The forecast datafor 20 years on electricity generation wasused to calculate the GHG emission and its saving when paddy residue is used for electricity generation. The government’scost saving was also identified when paddy residue substituted coal fuel in electricity generation.This paper can provide forecast information so that Malaysia is able to move forward to apply paddy residue as feedstock in energy supply. Hopefully, the data achieved can encourage stakeholder bodies in the implementation of paddy residue inelectricity generation since there is apositive impact towardscost and emission saving.

Life Cycle Analysis of Natural Gas Extraction and Power Generation

2019 ◽  
Author(s):  
James Littlefield ◽  
Selina Roman-White ◽  
Dan Augustine ◽  
Ambica Pegallapati ◽  
George G. Zaimes ◽  
...  
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Natural Gas ◽  
Life Cycle Analysis ◽  
Gas Extraction ◽  
Natural Gas Extraction

scholarly journals Life Cycle Cost of Electricity Production: A Comparative Study of Coal-Fired, Biomass, and Wind Power in China

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3463
Author(s):  
Xueliang Yuan ◽  
Leping Chen ◽  
Xuerou Sheng ◽  
Mengyue Liu ◽  
Yue Xu ◽  
...  
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Wind Power ◽  
Life Cycle Cost ◽  
Raw Material ◽  
Electricity Production ◽  
Maintenance Cost ◽  
External Cost ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity

Economic cost is decisive for the development of different power generation. Life cycle cost (LCC) is a useful tool in calculating the cost at all life stages of electricity generation. This study improves the levelized cost of electricity (LCOE) model as the LCC calculation methods from three aspects, including considering the quantification of external cost, expanding the compositions of internal cost, and discounting power generation. The improved LCOE model is applied to three representative kinds of power generation, namely, coal-fired, biomass, and wind power in China, in the base year 2015. The external cost is quantified based on the ReCiPe model and an economic value conversion factor system. Results show that the internal cost of coal-fired, biomass, and wind power are 0.049, 0.098, and 0.081 USD/kWh, separately. With the quantification of external cost, the LCCs of the three are 0.275, 0.249, and 0.081 USD/kWh, respectively. Sensitivity analysis is conducted on the discount rate and five cost factors, namely, the capital cost, raw material cost, operational and maintenance cost (O&M cost), other annual costs, and external costs. The results provide a quantitative reference for decision makings of electricity production and consumption.

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