کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8111873 | 1522302 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A meta-frontier DEA approach to efficiency comparison of carbon reduction technologies on project level
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Carbon reduction technologies such as renewable energy, nuclear energy and CCS technology for the power industry play a significant role in achieving low-carbon development goals. This research employed a meta-frontier DEA approach to evaluate carbon reduction efficiency of technologies on project level. The sample consists of several groups of projects such as nuclear energy, hydro-electric energy, wind energy, solar energy and biomass energy and CCS technology in power plants. The comparison study takes consideration the carbon reduction efficiency gap and management level of different technologies for the power industry. The results reveal that 1) Biomass energy power plants and conventional power plants installed with CCS have the highest efficiency in carbon reduction efficiency, with potential improvement in management. 2) Nuclear power plants show a high efficiency in carbon reduction while facing some constraints from safety and stability issues. 3) Although wind power, hydro-electric power and solar power have been exploited in power generation for a long time, they still have low efficiency in reducing carbon emission from the power industry. Suggestions are provided for policy makers to choose appropriate low-carbon development route of the power industry.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable and Sustainable Energy Reviews - Volume 82, Part 3, February 2018, Pages 2606-2612
Journal: Renewable and Sustainable Energy Reviews - Volume 82, Part 3, February 2018, Pages 2606-2612
نویسندگان
Nannan Wang, Ji Chen, Shengnan Yao, Yen-Chiang Chang,