Morphological Structure and Development Path of Urban Energy System for Carbon Emission Peak and Carbon Neutrality

被引：0
|
作者：
Bie Z. [1 ]
Ren Y. [1 ]
Li G. [1 ]
Yan Z. [1 ]
Wang Y. [1 ]
Sun S. [1 ]
机构：
[1] School of Electrical and Engineering, Xi’an Jiaotong University, Xi’an
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 17期
基金：
中国国家自然科学基金;
关键词：
coordinated planning; development path; hierarchical distribution; multi-energy coupling; optimal operation; urban energy system;
D O I：
10.7500/AEPS20220601006
中图分类号：
学科分类号：
摘要：
With the proposal of“carbon emission peak and carbon neutrality”in China, the energy industry has become the central link of transition to green and low-carbon development and the core of carbon emission reduction. As the key link connecting the preceding and the following of the integrated energy system, the urban energy system (UES) is undergoing profound changes in the production, transmission, and consumption links, which are reflected in the large-scale integration of distributed energy resource, the wide application of power electronic equipment, and the promotion and use of controllable loads, respectively . Starting from the morphological structure of the UES, this paper analyzes its multi-energy coupling functional structure with fuzzy source-load boundary and bidirectional network flow, and hierarchical spatial structure. Its typical characteristics such as openness, interconnection, mutual benefit, integrated development of energy and transportation systems, and deep cyber-physical fusion are expounded. Furthermore, two key issues, i. e. coordinated planning and optimal operation of the UES, are discussed in detail. Finally, the development path of the UES prospects from four links, including primary energy supply, secondary energy conversion, final energy consumption, and carbon removal is prospected. © 2022 Automation of Electric Power Systems Press. All rights reserved.
引用
收藏
页码：3 / 15
页数：12
相关论文
共 92 条
  • [61] SONG M, SUN W, SHAHIDEHPOUR M, Et al., Multi-time scale coordinated control and scheduling of inverter-based TCLs with variable wind generation ［J］, IEEE Transactions on Sustainable Energy, 12, 1, pp. 46-57, (2021)
  • [62] SONG M, GAO C W，, SHAHIDEHPOUR M，, Et al., Multi-time-scale modeling and parameter estimation of TCLs for smoothing out wind power generation variability［J］, IEEE Transactions on Sustainable Energy, 10, 1, pp. 105-118, (2019)
  • [63] BAHRAMI S, SHEIKHI A., From demand response in smart grid toward integrated demand response in smart energy hub［J］, IEEE Transactions on Smart Grid, 7, 2, pp. 650-658, (2016)
  • [64] DU Gang, ZHAO Dongmei, LIU Xin, Research review on optimal scheduling considering wind power uncertainty［J/OL］
  • [65] LU Zhuoxin, XU Xiaoyuan, YAN Zheng, Et al., Overview on data-driven optimal scheduling methods of power system in uncertain environment ［J］, Automation of Electric Power Systems, 44, 21, pp. 172-183, (2020)
  • [66] NING C，, YOU F Q., Data-driven stochastic robust optimization：general computational framework and algorithm leveraging machine learning for optimization under uncertainty in the big data era［J］, Computers & Chemical Engineering, 111, pp. 115-133, (2018)
  • [67] SHANG C, YOU F Q., Distributionally robust optimization for planning and scheduling under uncertainty［J］, Computers & Chemical Engineering, 110, pp. 53-68, (2018)
  • [68] HANG Lijun, YAN Dong, HU Jiabing, Et al., Review and prospect of key modeling technologies for power electronics system［J］, Proceedings of the CSEE, 41, 9, pp. 2966-2980, (2021)
  • [69] CHEN Yuan, ZHANG Bo, XIE Fan, Et al., Research progress of interrelationship between multi-time-scale modeling and algorithm of power-electronized power system［J］, Automation of Electric Power Systems, 45, 15, pp. 172-183, (2021)
  • [70] YUAN Xiaoming, ZHANG Meiqing, CHI Yongning, Et al., Basic challenges of and technical roadmap to power-electronized power system dynamics issues［J］, Proceedings of the CSEE, 42, 5, pp. 1904-1917, (2022)
12345678910