Low-carbon optimal operation of electricity-heat-gas systems based on bi-directional tiered-pricing carbon trading

被引:7
|
作者
Lv, Gang [1 ]
Zhang, Yangyu [1 ]
Zhu, Jing [2 ]
Liu, Lei [2 ]
Wu, Yahui [1 ]
Wang, Tian [2 ]
机构
[1] State Grid Integrated Energy Serv Grp Co Ltd, Beijing 100052, Peoples R China
[2] State Grid Integrated Energy Planning D&R Inst, Beijing 100052, Peoples R China
关键词
EHGIES; Bi-directional tiered-pricing carbon trading; P2G; Optimal operation; Low carbon;
D O I
10.1016/j.egyr.2023.04.116
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In the context of carbon peak and carbon neutrality target of China, multi-energy systems have become a key way to meet the needs of a low-carbon economy in the energy sector, and can achieve optimization and integration of multi-energy sources. For the purpose of maximize the low-carbon and economic of multi-energy systems, this paper proposes an optimization operation strategy of electricity-heat-gas integrated energy systems (EHGIES) based on bi-directional tiered-pricing carbon trading. The paper first establishes a multi-energy system model with CHP system and P2G conversion, introduces a bi-directional tiered-pricing carbon trading mechanism. Subsequently, an optimization model with objective function of the lowest carbon trading cost and energy purchase cost is established. The nonlinear optimization model is converted to a linear model by the CPLEX solver. Finally, this paper analyzes the trading mechanism, the interval length of tiered-pricing and carbon trading price on carbon emissions and carbon trading cost of EHGIES. The results show that different carbon trading price ranges and price growth rates have different impacts on carbon emissions and carbon trading costs. At the same time, the bi-directional tiered-pricing carbon trading mechanism established can reduce the overall carbon emissions effectively and is conducive to the low-carbon operation, and the low-carbon and economic nature of system operation can effectively be taken into account. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:377 / 387
页数:11
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