Planning Multiple Energy Systems Toward Low-Carbon Society: A Decentralized Approach

被引:124
作者
Cheng, Yaohua [1 ]
Zhang, Ning [1 ]
Lu, Zongxiang [1 ]
Kang, Chongqing [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Multiple energy systems; expansion planning; carbon emission constraints; carbon emission flow; bi-level model; STORAGE; GAS;
D O I
10.1109/TSG.2018.2870323
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Coordinating multiple energy systems (MES) enables the synergies of different energy sectors to be exploited. The concept of low-carbon development changes planning approaches for both the district level and the multi-regional level of MES. This paper proposes a bi-level expansion planning model of MES that considers the emission constraints under a decentralized approach. The upper-level model investigates the optimal planning scheme for integrated power and natural gas networks in the multi-regional MES. The lower-level model examines the optimal energy supply configuration of multiple energy carriers in the district MES based on the energy hub modeling approach. The carbon emission flow model is used to allocate the overall carbon emission cap among district MES from the consumption-based perspective and to coordinate the planning of the district level and the multi-regional level. An illustrative example based on a 6-node MES verifies the effectiveness of the proposed model. Finally, a realistic case study based on an MES in northern China is implemented to show the effects of carbon emission constraints on the planning of real-world energy systems.
引用
收藏
页码:4859 / 4869
页数:11
相关论文
共 29 条
[1]   Impact analysis of carbon tax on the renewal planning of energy supply system for an office building [J].
Amano, Y. ;
Ito, K. ;
Yoshida, S. ;
Matsuo, K. ;
Hashizume, T. ;
Favrat, D. ;
Marechal, F. .
ENERGY, 2010, 35 (02) :1040-1046
[2]  
[Anonymous], PROT CONTROL MOD POW
[3]  
[Anonymous], 2003, OUR EN FUT CREAT LOW
[4]   A mixed integer programming model for optimal design of trigeneration in a hospital complex [J].
Arcuri, P. ;
Florio, G. ;
Fragiacomo, P. .
ENERGY, 2007, 32 (08) :1430-1447
[5]   Robust Scheduling for Wind Integrated Energy Systems Considering Gas Pipeline and Power Transmission N-1 Contingencies [J].
Bai, Linquan ;
Li, Fangxing ;
Jiang, Tao ;
Jia, Hongjie .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (02) :1582-1584
[6]   Tracing the flow of electricity [J].
Bialek, J .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1996, 143 (04) :313-320
[7]   Power Generation Expansion Planning Model Towards Low-Carbon Economy and Its Application in China [J].
Chen, Qixin ;
Kang, Chongqing ;
Xia, Qing ;
Zhong, Jin .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2010, 25 (02) :1117-1125
[8]  
Cheng Y, IEEE T SMART GRID
[9]   Long-term Coordination of Transmission and Storage to Integrate Wind Power [J].
Conejo, Antonio J. ;
Cheng, Yaohua ;
Zhang, Ning ;
Kang, Chongqing .
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2017, 3 (01) :36-43
[10]   Multi-Stage Stochastic Programming With Nonanticipativity Constraints for Expansion of Combined Power and Natural Gas Systems [J].
Ding, Tao ;
Hu, Yuan ;
Bie, Zhaohong .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (01) :317-328