Potential assessment of optimizing energy structure in the city of carbon intensity target. (15th May 2017)
- Record Type:
- Journal Article
- Title:
- Potential assessment of optimizing energy structure in the city of carbon intensity target. (15th May 2017)
- Main Title:
- Potential assessment of optimizing energy structure in the city of carbon intensity target
- Authors:
- Lu, Shibao
Wang, Jianhua
Shang, Yizi
Bao, Haijun
Chen, Huixiong - Abstract:
- Highlights: Establish the low-carbon city development model. GMI (1, 1) model is adopted to predict the carbon intensity development trends. Multiple Regression Forecast of the Primary Energy Consumption. The energy structure optimization is an effective measure to decrease the carbon intensity. Abstract: Optimizing energy structure to reduce carbon intensity is an effective way to build the low-carbon city development model. To assess the contribution potential of energy structure optimization in order to achieve the carbon intensity target in Hangzhou City, the component data prediction, scenario prediction, GMI (1, 1) model and other multidisciplinary approaches were adopted to predict the carbon intensity trends in the above said City from 2014 to 2020. This contribution potential is evaluated based on 9 kinds of combined scenarios. The results show that: 1. Under the same economic growth rate, with the increase in energy structure adjustment range, the carbon intensity "decline range" becomes larger, and the higher is the "contribution potential" of energy structure optimization to achieve the carbon intensity target. 2. Within the same range of energy structure optimization, the economic growth rate is lower, the carbon intensity "decline range" is smaller, and the "contribution potential" of energy structure optimization is higher for the same carbon intensity objective. By optimizing energy structure and industrial structures adjustment, the technology upgrading forHighlights: Establish the low-carbon city development model. GMI (1, 1) model is adopted to predict the carbon intensity development trends. Multiple Regression Forecast of the Primary Energy Consumption. The energy structure optimization is an effective measure to decrease the carbon intensity. Abstract: Optimizing energy structure to reduce carbon intensity is an effective way to build the low-carbon city development model. To assess the contribution potential of energy structure optimization in order to achieve the carbon intensity target in Hangzhou City, the component data prediction, scenario prediction, GMI (1, 1) model and other multidisciplinary approaches were adopted to predict the carbon intensity trends in the above said City from 2014 to 2020. This contribution potential is evaluated based on 9 kinds of combined scenarios. The results show that: 1. Under the same economic growth rate, with the increase in energy structure adjustment range, the carbon intensity "decline range" becomes larger, and the higher is the "contribution potential" of energy structure optimization to achieve the carbon intensity target. 2. Within the same range of energy structure optimization, the economic growth rate is lower, the carbon intensity "decline range" is smaller, and the "contribution potential" of energy structure optimization is higher for the same carbon intensity objective. By optimizing energy structure and industrial structures adjustment, the technology upgrading for carbon emissions and the scientific and technological level of the systematic industrial policies are more conducive to supporting the realization of low-carbon city. … (more)
- Is Part Of:
- Applied energy. Volume 194(2017)
- Journal:
- Applied energy
- Issue:
- Volume 194(2017)
- Issue Display:
- Volume 194, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 194
- Issue:
- 2017
- Issue Sort Value:
- 2017-0194-2017-0000
- Page Start:
- 765
- Page End:
- 773
- Publication Date:
- 2017-05-15
- Subjects:
- Energy structure -- Carbon intensity target -- Carbon emissions -- Scenarios prediction -- Regression analysis -- Component data model -- Hangzhou City
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2016.07.116 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1061.xml