Analysis of Multi-Region Coordinated Peak-Shaving and Peak-Valley Mutual Operation Mode under the Energy Internet

doi:10.11930/j.issn.1004-9649.201805150

Electric Power ›› 2018, Vol. 51 ›› Issue (8): 64-69.DOI: 10.11930/j.issn.1004-9649.201805150

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Analysis of Multi-Region Coordinated Peak-Shaving and Peak-Valley Mutual Operation Mode under the Energy Internet

XU Zhicheng^1,2, ZHANG Fuqiang^1,2, CHEN Shizhe³, XIE Dongliang⁴, JIAO Bingqi^1,2

1. State Grid Energy Research Institute Co. Ltd., Beijing 102209, China;
2. State Grid Laboratory of Energy and Electric Power Planning, Beijing 102209, China;
3. State Grid Zhejiang Electric Power Co., Ltd. Hangzhou Power Supply Company, Hangzhou 310007, China;
4. NARI Group Corporation(State Grid Electric Power Research Institute), Nanjing 211106, China

Received:2018-05-23 Online:2018-08-05 Published:2018-11-01
Supported by:
This work is supported by Science and Technology Project of State Grid Corporation of China (No.SGZJ0000BGJS1600169).

Abstract

Abstract: It is a preferred method to realize multi-region coordinated peak-shaving operation by using the space-time complementarity characteristics of different regional loads and renewable energy generations. The research on peak shaving method of renewable energy in different regions can provide an important decision support for power network planning and operation mode design. In this paper, on the basis of an analysis of the source-load characteristics of multiple regions, the deterministic analysis method and the uncertainty risk assessment method are used to obtain the typical peak-valley mutual operation mode based on the peak-shaving evaluation indicator system. A comparative analysis is also carried out of the economic benefits of cross-region interconnection peak-shaving under different schemes, and the typical operation mode and economic evaluation results of multi-region coordinated peak-shaving operation are given.

Key words: Energy Internet, coordinated peak-shaving, peak-valley mutual operation, space-time complementarity, risk evaluation

CLC Number:

TM73

XU Zhicheng, ZHANG Fuqiang, CHEN Shizhe, XIE Dongliang, JIAO Bingqi. Analysis of Multi-Region Coordinated Peak-Shaving and Peak-Valley Mutual Operation Mode under the Energy Internet[J]. Electric Power, 2018, 51(8): 64-69.

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References

[1] 刘振亚. 全球能源互联网跨国跨洲互联研究及展望[J]. 中国电机工程学报, 2016, 36(19):5103-5110 LIU Zhenya. Research of global clean energy resource and power grid interconnection[J]. Proceedings of the CSEE, 2016, 36(19):5103-5110
[2] JACOBSON M Z. Review of solutions to global warming, air pollution and energy security[J]. Energy & Environmental Science, 2009, 2(2):148-173.
[3] 刘晓明, 牛新生, 王佰淮, 等. 能源互联网综述研究[J]. 中国电力, 2016, 49(3):24-33 LIU Xiaoming, NIU Xinsheng, WANG Baihuai, et al. A review on the energy internet[J]. Electric Power, 2016, 49(3):24-33
[4] 周海明, 刘广一, 刘超群. 能源互联网技术框架研究[J]. 中国电力, 2014, 47(11):140-144 ZHOU Haiming, LIU Guangyi, LIU Chaoqun. Study on the energy internet technology framework[J]. Electric Power, 2014, 47(11):140-144
[5] 陈世喆. 全球能源互联网调峰运行方式的仿真研究[D]. 南京:南京师范大学, 2017
[6] 袁越, 周建华, 余嘉彦, 等. 含风电场电力系统调峰对策综述[J]. 电网与清洁能源, 2010, 26(6):1-4 YUAN Yue, ZHOU Jianhua, YU Jiayan, et al. An overview of the peak-load regulating countermeasures for power systems containing wind farms[J]. Power System and Clean Energy, 2010, 26(6):1-4
[7] 孙云涛, 宋依群. 基于调峰能力评估的省间调峰互济交易模式[J]. 电力系统保护与控制, 2018, 46(4):86-91 SUN Yuntao, SONG Yiqun. Peak load regulation trading mode for trans-provincial aid based on evaluation of system regulation capability[J]. Power System Protection and Control, 2018, 46(4):86-91
[8] 张宁, 周天睿, 段长刚, 等. 大规模风电场接入对电力系统调峰的影响[J]. 电网技术, 2010, 34(1):152-158 ZHANG Ning, ZHOU Tianrui, DUAN Changgang, et al. Impact of large-scale wind farm connecting with power grid on peak load regulation demand[J]. Power System Technology, 2010, 34(1):152-158
[9] 张宏宇, 印永华, 申洪, 等. 大规模风电接入后的系统调峰充裕性评估[J]. 中国电机工程学报, 2011, 31(22):26-31 ZHANG Hongyu, YIN Yonghua, SHEN Hong, et al. Peak-load regulating adequacy evaluation associated with large-scale wind power integration[J]. Proceedings of the CSEE, 2011, 31(22):26-31
[10] 国网能源研究院有限公司. 全球联网的电力流格局构建方法研究[R]. 2017

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Analysis of Multi-Region Coordinated Peak-Shaving and Peak-Valley Mutual Operation Mode under the Energy Internet

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