Low-carbon Optimal Scheduling of Integrated Electricity-gas Energy Systems Considering CCUS-P2G Technology and Risk of Carbon Market

被引：0
|
作者：
Guo J. [1 ]
Xiang Y. [1 ]
Wu J. [2 ]
Wu G. [3 ]
机构：
[1] College of Electrical Engineering, Sichuan University, Sichuan Province, Chengdu
[2] The Wang Yanan Institute for Studies in Economics, Xiamen University, Fujian Province, Xiamen
[3] State Grid Sichuan Economic Research Institute, Sichuan Province, Chengdu
来源：
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2023年 / 43卷 / 04期
基金：
中国国家自然科学基金;
关键词：
carbon capture utilization and storage system; generalized auto regressive conditional heteroskedasticity model; integrated electricity-gas energy system; optimal dispatch; power to gas;
D O I：
10.13334/j.0258-8013.pcsee.221255
中图分类号：
学科分类号：
摘要：
In the context of carbon market price risk, it is urgent to quantify the risk of carbon market volatility and formulate corresponding low-carbon operation strategies for energy systems to reduce operation costs and carbon emissions. A low-carbon optimal dispatching model for integrated electricity-gas energy system (IEGS) considering carbon price risk with carbon capture utilization and storage system (CCUS) and power to gas (P2G) synergistic operation is proposed. First, the generalized auto regressive conditional heteroskedasticity model is used to predict the carbon price on the next trading day, and the conditional value at risk model is used to measure the risk of price fluctuations to provide a carbon price basis for IEGS. Then, the CCUS-P2G operation framework is introduced. The CO2 captured by the carbon capture unit is used as the raw material for P2G conversion, and the curtailed wind power is used to produce natural gas by P2G units during the load valley period. The optimal scheduling model is established to minimize the operation cost and risk of carbon trading. Finally, simulations are conducted in an IEGS composed of an improved IEEE 24-bus system and a natural gas 6-node system. The results demonstrate that the proposed scheduling model can accurately measure the risk during the fluctuation period of the carbon market and increase the renewable energy consumption of the IEGS, and thus achieve reductions in total operation costs and carbon emissions. ©2023 Chin.Soc.for Elec.Eng.
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页码：1290 / 1302
页数：12
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