LAPSE:2023.32718
Published Article
LAPSE:2023.32718
Energy−Water−CO2 Synergetic Optimization Based on a Mixed-Integer Linear Resource Planning Model Concerning the Demand Side Management in Beijing’s Power Structure Transformation
Yuan Liu, Qinliang Tan, Jian Han, Mingxin Guo
April 20, 2023
Studies on the energy−water−CO2 synergetic relationship is an effective way to help achieve the peak CO2 emission target and carbon neutral goal in global countries. One of the most valid way is to adjust through the electric power structure transformation. In this study, a mixed-integer linear resource planning model is proposed to investigate the energy−water−CO2 synergetic optimization relationship, concerning the uncertainties in the fuel price and power demand prediction process. Coupled with multiple CO2 emissions and water policy scenarios, Beijing, the capital city of China, is chosen as a case study. Results indicate that the demand-side management (DSM) level and the stricter environmental constraints can effectively push Beijing’s power supply system in a much cleaner direction. The energy−water−CO2 relationship will reach a better balance under stricter environmental constraints and higher DSM level. However, the achievement of the energy−water−CO2 synergetic optimization will be at an expense of high system cost. Decision makers should adjust their strategies flexibly based on the practical planning situations.
Keywords
DSM, energy–water–carbon synergetic optimization, mixed-integer linear programming, power structure transformation, uncertainty
Suggested Citation
Liu Y, Tan Q, Han J, Guo M. Energy−Water−CO2 Synergetic Optimization Based on a Mixed-Integer Linear Resource Planning Model Concerning the Demand Side Management in Beijing’s Power Structure Transformation. (2023). LAPSE:2023.32718
Author Affiliations
Liu Y: School of Economics and Management, North China Electric Power University, Beijing 102206, China [ORCID]
Tan Q: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of Renewable Electric Power and Low Carbon Development, North China Electric Power University, Beijing 102206, China; Research Center
Han J: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Guo M: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Journal Name
Energies
Volume
14
Issue
11
First Page
3268
Year
2021
Publication Date
2021-06-03
Published Version
ISSN
1996-1073
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PII: en14113268, Publication Type: Journal Article
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doi:10.3390/en14113268
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