A Method for Assessing the Impact of Changes in Demand for Coal on the Structure of Coal Grades Produced by Mines
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Chong, ChinHao & Ma, Linwei & Li, Zheng & Ni, Weidou & Song, Shizhong, 2015. "Logarithmic mean Divisia index (LMDI) decomposition of coal consumption in China based on the energy allocation diagram of coal flows," Energy, Elsevier, vol. 85(C), pages 366-378.
- Smith, Michael, 2000. "Modeling and Short-term Forecasting of New South Wales Electricity System Load," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 465-478, October.
- Michieka, Nyakundi M. & Fletcher, Jerald J., 2012. "An investigation of the role of China's urban population on coal consumption," Energy Policy, Elsevier, vol. 48(C), pages 668-676.
- Joanna Nowicka-Zagrajek & Rafal Weron, 2002. "Modeling electricity loads in California: ARMA models with hyperbolic noise," HSC Research Reports HSC/02/02, Hugo Steinhaus Center, Wroclaw University of Technology.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Amaral, Luiz Felipe & Souza, Reinaldo Castro & Stevenson, Maxwell, 2008. "A smooth transition periodic autoregressive (STPAR) model for short-term load forecasting," International Journal of Forecasting, Elsevier, vol. 24(4), pages 603-615.
- Yanbin Li & Zhen Li, 2019. "Forecasting of Coal Demand in China Based on Support Vector Machine Optimized by the Improved Gravitational Search Algorithm," Energies, MDPI, vol. 12(12), pages 1-20, June.
- Kim, Myung Suk, 2013. "Modeling special-day effects for forecasting intraday electricity demand," European Journal of Operational Research, Elsevier, vol. 230(1), pages 170-180.
- Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601, December.
- Bakirtas, Tahsin & Akpolat, Ahmet Gokce, 2018. "The relationship between energy consumption, urbanization, and economic growth in new emerging-market countries," Energy, Elsevier, vol. 147(C), pages 110-121.
- Pappas, S.Sp. & Ekonomou, L. & Karamousantas, D.Ch. & Chatzarakis, G.E. & Katsikas, S.K. & Liatsis, P., 2008. "Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models," Energy, Elsevier, vol. 33(9), pages 1353-1360.
- Feng Dong & Yuling Pan, 2020. "Evolution of Renewable Energy in BRI Countries: A Combined Econometric and Decomposition Approach," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
- Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
- Shiraki, Hiroto & Matsumoto, Ken'ichi & Shigetomi, Yosuke & Ehara, Tomoki & Ochi, Yuki & Ogawa, Yuki, 2020. "Factors affecting CO2 emissions from private automobiles in Japan: The impact of vehicle occupancy," Applied Energy, Elsevier, vol. 259(C).
- Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
- Vaz, Lucélia Viviane & Filho, Getulio Borges da Silveira, 2017. "Functional Autoregressive Models: An Application to Brazilian Hourly Electricity Load," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(2), November.
- Raza, Muhammad Yousaf & Lin, Boqiang, 2023. "Future outlook and influencing factors analysis of natural gas consumption in Bangladesh: An economic and policy perspectives," Energy Policy, Elsevier, vol. 173(C).
- Zhang, Lixiao & Yang, Min & Zhang, Pengpeng & Hao, Yan & Lu, Zhongming & Shi, Zhimin, 2021. "De-coal process in urban China: What can we learn from Beijing's experience?," Energy, Elsevier, vol. 230(C).
- Cancelo, José Ramón & Espasa, Antoni & Grafe, Rosmarie, 2008. "Forecasting the electricity load from one day to one week ahead for the Spanish system operator," International Journal of Forecasting, Elsevier, vol. 24(4), pages 588-602.
- Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
- Wang, Zhiping & Feng, Chao & Chen, Jinyu & Huang, Jianbai, 2017. "The driving forces of material use in China: An index decomposition analysis," Resources Policy, Elsevier, vol. 52(C), pages 336-348.
- Liu, Lan-Cui & Cheng, Lei & Zhao, Lu-Tao & Cao, Ying & Wang, Ce, 2020. "Investigating the significant variation of coal consumption in China in 2002-2017," Energy, Elsevier, vol. 207(C).
- Smith, Michael Stanley & Shively, Thomas S., 2018.
"Econometric modeling of regional electricity spot prices in the Australian market,"
Energy Economics, Elsevier, vol. 74(C), pages 886-903.
- Michael Stanley Smith & Thomas S. Shively, 2018. "Econometric Modeling of Regional Electricity Spot Prices in the Australian Market," Papers 1804.08218, arXiv.org.
- Liu, Yisheng & Yang, Meng & Cheng, Feiyu & Tian, Jinzhao & Du, Zhuoqun & Song, Pengbo, 2022. "Analysis of regional differences and decomposition of carbon emissions in China based on generalized divisia index method," Energy, Elsevier, vol. 256(C).
- Michiyuki Yagi & Shunsuke Managi, 2018.
"Decomposition analysis of corporate carbon dioxide and greenhouse gas emissions in Japan: Integrating corporate environmental and financial performances,"
Business Strategy and the Environment, Wiley Blackwell, vol. 27(8), pages 1476-1492, December.
- Yagi, Michiyuki & Managi, Shunsuke, 2018. "Decomposition analysis of corporate carbon dioxide and greenhouse gas emissions in Japan: Integrating corporate environmental and financial performances," MPRA Paper 87891, University Library of Munich, Germany.
More about this item
Keywords
algorithm simplex; Monte Carlo simulation;Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7111-:d:669671. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.