Energy–Water–CO 2 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 and Mingxin Guo
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Yuan Liu: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Qinliang Tan: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Jian Han: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Mingxin Guo: School of Economics and Management, North China Electric Power University, Beijing 102206, China

Energies, 2021, vol. 14, issue 11, 1-17

Abstract: Studies on the energy–water–CO 2 synergetic relationship is an effective way to help achieve the peak CO 2 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–CO 2 synergetic optimization relationship, concerning the uncertainties in the fuel price and power demand prediction process. Coupled with multiple CO 2 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–CO 2 relationship will reach a better balance under stricter environmental constraints and higher DSM level. However, the achievement of the energy–water–CO 2 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: energy–water–carbon synergetic optimization; mixed-integer linear programming; uncertainty; DSM; power structure transformation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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