Research on a Low-Carbon Optimization Strategy for Regional Power Grids Considering a Dual Demand Response of Electricity and Carbon

被引:0
|
作者
Ma, Famei [1 ]
Ying, Liming [1 ]
Cui, Xue [1 ]
Yu, Qiang [2 ]
机构
[1] Wuhan Univ, Sch Elect Engn & Automat, Hubei Key Lab Power Equipment & Syst Secur Integra, Wuhan 430072, Peoples R China
[2] Yunnan Power Grid Co Ltd, Grid Planning & Construct Res Ctr, Kunming 650011, Peoples R China
关键词
regional power grid; dynamic carbon emission factor; dual demand response of electricity and carbon; multi-objective bi-level optimization;
D O I
10.3390/su16167000
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Considering the characteristics of the power system, where "the source moves with the load", the load side is primarily responsible for the carbon emissions of the regional power grid. Consequently, users' electricity consumption behavior has a significant impact on system carbon emissions. Therefore, this paper proposes a multi-objective bi-level optimization strategy for source-load coordination, considering dual demand responses for both electricity and carbon. The upper layer establishes a multi-objective low-carbon economic dispatch model for power grid operators, aiming to minimize the system's total operating cost, the total direct carbon emissions of the power grid, and the disparity in regional carbon emissions. In the lower layer, a low-carbon economic dispatch model for load aggregators is established to minimize the total cost for load aggregators. To obtain the dynamic carbon emission factor signal, a complex power flow tracking method that considers the power supply path is proposed, and a carbon flow tracking model is established. NSGA-II is used to obtain the Pareto optimal frontier set for the upper model, and the 'optimal' scheme is determined based on the fuzzy satisfaction decision. The example analysis demonstrates that the interactive carbon reduction effect under the guidance of dual signals is the most effective. This approach fully exploits the carbon reduction potential of the flexible load, enhancing both the economic efficiency and low-carbon operation of the system.
引用
收藏
页数:20
相关论文
共 50 条
  • [31] Low-carbon Planning of Power Source Considering Cross-domain Hydrogen Demand
    Yuan, Tiejiang
    Zhang, Yijin
    Ge, Yangyang
    Tian, Xueqin
    Yang, Zijuan
    [J]. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2024, 48 (13): : 30 - 39
  • [32] Positioning Nuclear Power in the Low-Carbon Electricity Transition
    Verbruggen, Aviel
    Yurchenko, Yuliya
    [J]. SUSTAINABILITY, 2017, 9 (01):
  • [33] Global transcontinental power pools for low-carbon electricity
    Yang, Haozhe
    Deshmukh, Ranjit
    Suh, Sangwon
    [J]. NATURE COMMUNICATIONS, 2023, 14 (01)
  • [34] Low-carbon Planning of Power System Considering Carbon Emission Flow
    Zhao, Wei
    Xiong, Zhengyong
    Pan, Yan
    Li, Fuqiang
    Xu, Peng
    Lai, Xiaowen
    [J]. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2023, 47 (09): : 23 - 33
  • [35] Low-Carbon Optimal Scheduling of Integrated Energy System Considering Multiple Uncertainties and Electricity-Heat Integrated Demand Response
    Li, Hongwei
    Li, Xingmin
    Chen, Siyu
    Li, Shuaibing
    Kang, Yongqiang
    Ma, Xiping
    [J]. ENERGIES, 2024, 17 (01)
  • [36] Low-carbon integrated energy system scheduling considering electric vehicle demand response
    Wang, Lunjie
    Luo, Lin
    Yu, Miao
    Pei, Xiaodeng
    [J]. Journal of Cleaner Production, 2024, 480
  • [37] Low-carbon economic scheduling strategy for power system with concentrated solar power plant and wind power considering carbon trading
    Cui, Yang
    Deng, Guibo
    Wang, Zheng
    Wang, Maochun
    Zhao, Yuting
    [J]. Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2021, 41 (09): : 232 - 239
  • [38] Low-carbon optimal operation of the integrated energy system considering integrated demand response
    Ji, Xiu
    Li, Meng
    Li, Meiyue
    Han, Huanhuan
    [J]. FRONTIERS IN ENERGY RESEARCH, 2023, 11
  • [39] Research on cold chain logistics optimization model considering low-carbon emissions
    Tao, Ning
    Yumeng, Han
    Meng, Fu
    [J]. INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES, 2023, 18 : 354 - 366
  • [40] Low-carbon demand response program for power systems considering uncertainty based on the data-driven distributionally robust chance constrained optimization
    Zhao, Ruifeng
    Song, Zehao
    Xu, Yinliang
    Lu, Jiangang
    Guo, Wenxin
    Li, Haobin
    [J]. IET RENEWABLE POWER GENERATION, 2024,