考虑不确定变量变分模态分解及绿证-碳联合交易的综合能源系统经济优化调度

doi:10.19595/j.cnki.1000-6753.tces.240967

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Abstract With the increasing volatility and randomness of uncertain variables such as load and new energy, how to rationally dispatch multiple equipment such as cogeneration, gas boiler and energy storage equipment in integrated energy system (IES) according to the response characteristics of the existing potential response resources in IES to cope with the changes of uncertain variables has become the key to explore the differentiated response ability of IES multiple equipment. To solve the above problems, this paper proposes an economic optimal scheduling method for integrated energy systems, which takes into account variational mode decomposition (VMD) of uncertain variables and green certificate-carbon joint trading. By analyzing and mining the potential differential response ability of multiple devices in IES, the response ability of IES system to uncertainty variable volatility and randomness is improved.
Firstly, according to the commonness and difference of multiple types equipment operating response in time scale and regulatory amplitude in IES, uncertain variables such as wind power, electricity/heat/gas load are decomposed into low/medium/high frequency components with different amplitude and frequency through VMD to adapt to the response characteristics of multiple types equipment. Secondly, on the basis of considering the green certificate trading mechanism (GCT) and the carbon trading mechanism (CET), quantitatively calculate the carbon emission reduction of new energy compared with fossil energy in the process of online access, and offset part of the carbon emission through the carbon emission reduction caused by the green certificate, so that the carbon emission source can be reduced to a certain extent in the calculation of carbon emissions, which indirectly affects the carbon trading mechanism. Based on this, the green certificate-carbon joint trading mechanism is constructed. Finally, the medium and large-sized equipment with large inertia responds to the low-frequency component with low frequency and large amplitude, and the energy storage equipment that needs repeated charging and discharging responds to the medium/high-frequency component with small amplitude and positive/negative periodic oscillation, and then an economic optimisation scheduling model of the IES with the objective of minimising the comprehensive cost is established on the basis of the model, which is then passed layer by layer and iteratedly solved based on the order of VMD's low/medium/high-frequency components.
Through theoretical analysis and case simulation, the following conclusions are drawn: (1) The predicted power, electrical load, thermal load and gas load of wind power are decomposed into low, medium and high frequency components through VMD, which are suitable for the operation characteristics and response characteristics of energy storage equipment. The scheduling method proposed in this paper reduces the operation state of overcharge and overdischarge of energy storage equipment, which can effectively improve the utilization rate of energy storage equipment and further improve the system's ability to absorb new energy. (2) Compared with a single energy storage device, the hybrid energy storage system can better smooth and absorb wind power in different frequency bands according to the different frequency characteristics of wind power, so as to eliminate more wind abandonment and reduce the comprehensive cost of the system. (3) Compared with the single CET or GCT mechanism, the GCT-CET linkage mechanism can not only improve the absorption capacity of renewable energy in the integrated energy system, but also promote the further reduction of carbon emissions of the system.

Key words： Variational mode decomposition green certificate trading mechanism carbon trading mechanism wind power consumption integrated energy system

Received: 07 June 2024

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	Liu Xiaojun
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Liu Xiaojun,Xiong Jian,Wang Yibo等. Economic Optimization of Integrated Energy System Scheduling Considering Uncertainty Variables Variational Mode Decomposition and Green Certificate-Carbon Joint Trading[J]. Transactions of China Electrotechnical Society, 2025, 40(13): 4276-4291.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.240967 OR https://dgjsxb.ces-transaction.com/EN/Y2025/V40/I13/4276

[1] 李鹏, 钟瀚明, 马红伟, 等. 基于深度强化学习的有源配电网多时间尺度源荷储协同优化调控[J]. 电工技术学报, 2025, 40(5): 1487-1502.
Li Peng, Zhong Hanming, Ma Hongwei, et al.Multi-timescale optimal dispatch of source-load-storage coordination in active distribution network based on deep reinforcement learning[J]. Transactions of China Electrotechnical Society, 2025, 40(5): 1487-1502.
[2] 宋梦, 林固静, 高赐威, 等. 考虑多重不确定性的广义共享储能优化配置方法[J]. 电工技术学报, 2025, 40(5): 1521-1539.
Song Meng, Lin Gujing, Gao Ciwei, et al.A generalized shared energy storage optimization configuration method considering multiple uncertainties[J]. Transactions of China Electrotechnical Society, 2025, 40(5): 1521-1539.
[3] 印欣, 张锋, 阿地利·巴拉提, 等. 新型电力系统背景下电热负荷参与实时调度研究[J].发电技术, 2023, 44(1): 115-124.
Yin Xin, Zhang Feng, Adili Balati, et al.Study on participation of electricity-driven thermal load in real-time scheduling of new power system[J]. Power Generation Technology, 2023, 44(1): 115-124.
[4] 刘妍, 胡志坚, 陈锦鹏, 等. 含碳捕集电厂与氢能多元利用的综合能源系统低碳经济调度[J]. 电力系统自动化, 2024, 48(1): 31-40.
Liu Yan, Hu Zhijian, Chen Jinpeng, et al.Low-carbon economic dispatch of integrated energy system considering carbon capture power plant and multi-utilization of hydrogen energy[J]. Automation of Electric Power Systems, 2024, 48(1): 31-40.
[5] 叶宇静, 邢海军, 米阳, 等. 考虑低碳需求响应及主从博弈的综合能源系统低碳优化调度[J]. 电力系统自动化, 2024, 48(9): 34-43.
Ye Yujing, Xing Haijun, Mi Yang, et al.Low-carbon optimal scheduling of integrated energy system considering low carbon demand response and Stackelberg game[J]. Automation of Electric Power Systems, 2024, 48(9): 34-43.
[6] 杨航, 张涛, 冉华军, 等.考虑需求响应与碳价不确定性的综合能源系统优化调度[J/OL]. 现代电力, 2024: 1-11. https://doi.org/10.19725/j.cnki.1007-2322.2023.0195.
Yang Hang, Zhang Tao, Ran Huajun, et al.Optimal dispatching of integrated energy systems considering demand response and carbon price uncertainty[J/OL]. Modern Electric Power, 2024: 1-11. https://doi.org/10.19725/j.cnki.1007-2322.2023.0195.
[7] 王利猛, 刘雪梦, 李扬, 等. 阶梯式碳交易机制下考虑需求响应的综合能源系统低碳优化调度[J]. 电力建设, 2024, 45(2): 102-114.
Wang Limeng, Liu Xuemeng, Li Yang, et al.Low-carbon optimal dispatch of integrated energy system considering demand response under the tiered carbon trading mechanism[J]. Electric Power Construction, 2024, 45(2): 102-114.
[8] 曾艾东, 邹宇航, 郝思鹏, 等. 考虑阶梯式碳交易机制的园区工业用户综合需求响应策略[J]. 高电压技术, 2022, 48(11): 4352-4361.
Zeng Aidong, Zou Yuhang, Hao Sipeng, et al.Comprehensive demand response strategy of industrial users in the park considering the stepped carbon trading mechanism[J]. High Voltage Engineer-ing, 2022, 48(11): 4352-4361.
[9] 张晓辉, 刘小琰, 钟嘉庆. 考虑奖惩阶梯型碳交易和电-热转移负荷不确定性的综合能源系统规划[J]. 中国电机工程学报, 2020, 40(19): 6132-6141.
Zhang Xiaohui, Liu Xiaoyan, Zhong Jiaqing.Integrated energy system planning considering a reward and punishment ladder-type\r carbon trading and electric-thermal transfer load uncertainty[J]. Proceedings of the CSEE, 2020, 40(19): 6132-6141.
[10] 骆钊, 秦景辉, 梁俊宇, 等. 含碳-绿色证书联合交易机制的综合能源系统日前优化调度[J]. 电力自动化设备, 2021, 41(9): 248-255.
Luo Zhao, Qin Jinghui, Liang Junyu, et al.Day-ahead optimal scheduling of integrated energy system with carbon-green certificate coordinated trading mechanism[J]. Electric Power Automation Equipment, 2021, 41(9): 248-255.
[11] 蒋轶澄, 曹红霞, 杨莉, 等. 可再生能源配额制的机制设计与影响分析[J]. 电力系统自动化, 2020, 44(7): 187-199.
Jiang Yicheng, Cao Hongxia, Yang Li, et al.Mechanism design and impact analysis of renewable portfolio standard[J]. Automation of Electric Power Systems, 2020, 44(7): 187-199.
[12] 曹雨微, 郭晓鹏, 董厚琦, 等. 计及消纳责任权重的区域综合能源系统运行优化研究[J]. 华北电力大学学报(自然科学版), 2022, 49(3): 84-95.
Cao Yuwei, Guo Xiaopeng, Dong Houqi, et al.Operation optimization of regional integrated energy system under responsibility of renewable energy consumption[J]. Journal of North China Electric Power University (Natural Science Edition), 2022, 49(3): 84-95.
[13] 骆钊, 秦景辉, 梁俊宇, 等. 含绿色证书跨链交易的综合能源系统运行优化[J]. 电网技术, 2021, 45(4): 1311-1319.
Luo Zhao, Qin Jinghui, Liang Junyu, et al.Operation optimization of integrated energy system with green certificate cross-chain transaction[J]. Power System Technology, 2021, 45(4): 1311-1319.
[14] 刘晓军, 聂凡杰, 杨冬锋, 等. 碳捕集电厂-电转气联合运行模式下考虑绿证-碳交易机制的综合能源系统低碳经济调度[J]. 电网技术, 2023, 47(6): 2207-2217.
Liu Xiaojun, Nie Fanjie, Yang Dongfeng, et al.Low carbon economic dispatch of integrated energy systems considering green certificates-carbon trading mechanism under CCPP-P2G joint operation model[J]. Power System Technology, 2023, 47(6): 2207-2217.
[15] 赵靖英, 乔珩埔, 姚帅亮, 等. 考虑储能SOC自恢复的风电波动平抑混合储能容量配置策略[J]. 电工技术学报, 2024, 39(16): 5206-5219.
Zhao Jingying, Qiao Hengpu, Yao Shuailiang, et al.Hybrid energy storage system capacity configuration strategy for stabilizing wind power fluctuation considering SOC self-recovery[J]. Transactions of China Electrotechnical Society, 2024, 39(16): 5206-5219.
[16] 韩丽, 陈硕, 王施琪, 等. 考虑风光消纳与电动汽车灵活性的调度策略[J]. 电工技术学报, 2024, 39(21): 6793-6803.
Han Li, Chen Shuo, Wang Shiqi, et al.Scheduling strategy considering wind and photovoltaic power consumption and the flexibility of electric vehicles[J]. Transactions of China Electrotechnical Society, 2024, 39(21): 6793-6803.
[17] 熊康, 黎灿兵, 樊飞龙, 等. 电池储能温度-功率特性建模及其在综合能源系统中的应用[J]. 电工技术学报, 2024, 39(16): 5238-5250.
Xiong Kang, Li Canbing, Fan Feilong, et al.Modeling of temperature-power characteristics of battery energy storage and its application in integrated energy system[J]. Transactions of China Electrotechnical Society, 2024, 39(16) 5238-5250.
[18] 李建林, 李雅欣, 刘海涛, 等. 计及储能电站安全性的功率分配策略研究[J]. 电工技术学报, 2022, 37(23): 5976-5986.
Li Jianlin, Li Yaxin, Liu Haitao, et al.Research on power distribution strategy considering the safety of energy storage power station[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 5976-5986.
[19] 李翠萍, 司文博, 李军徽, 等. 基于集合经验模态分解和多目标遗传算法的火-多储系统调频功率双层优化[J]. 电工技术学报, 2024, 39(7): 2017-2032.
Li Cuiping, Si Wenbo, Li Junhui, et al.Two-layer optimization of frequency modulated power of thermal generation and multi-storage system based on ensemble empirical mode decomposition and multi-objective genetic algorithm[J]. Transactions of China Electrotechnical Society, 2024, 39(7): 2017-2032.
[20] 马伟, 王玮, 吴学智, 等. 平抑光伏并网功率波动的混合储能系统优化调度策略[J]. 电力系统自动化, 2019, 43(3): 58-66.
Ma Wei, Wang Wei, Wu Xuezhi, et al.Optimal dispatching strategy of hybrid energy storage system for smoothing power fluctuation caused by grid-connected photovoltaic[J]. Automation of Electric Power Systems, 2019, 43(3): 58-66.
[21] Cui Dai, Jin Yicheng, Wang Yibo, et al.Combined thermal power and battery low carbon scheduling method based on variational mode decomposition[J]. International Journal of Electrical Power & Energy Systems, 2023, 145: 108644.
[22] Wang Yongli, Song Fuhao, Ma Yuze, et al.Research on capacity planning and optimization of regional integrated energy system based on hybrid energy storage system[J]. Applied Thermal Engineering, 2020, 180: 115834.
[23] Dragomiretskiy K, Zosso D.Variational mode decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3): 531-544.
[24] 田波, 朴在林, 郭丹, 等. 基于改进EEMD-SE-ARMA的超短期风功率组合预测模型[J]. 电力系统保护与控制, 2017, 45(4): 72-79.
Tian Bo, Piao Zailin, Guo Dan, et al.Wind power ultra short-term model based on improved EEMD-SE-ARMA[J]. Power System Protection and Control, 2017, 45(4): 72-79.
[25] Meng Yuxiang, Ma Gang, Yao Yunting, et al.Nash bargaining based integrated energy agent optimal operation strategy considering negotiation pricing for tradable green certificate[J]. Applied Energy, 2024, 356: 122427.
[26] 崔杨, 曾鹏, 仲悟之, 等. 考虑阶梯式碳交易的电-气-热综合能源系统低碳经济调度[J]. 电力自动化设备, 2021, 41(3): 10-17.
Cui Yang, Zeng Peng, Zhong Wuzhi, et al.Low-carbon economic dispatch of electricity-gas-heat integrated energy system based on ladder-type carbon trading[J]. Electric Power Automation Equipment, 2021, 41(3): 10-17.
[27] Wang Rutian, Wen Xiangyun, Wang Xiuyun, et al.Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading[J]. Applied Energy, 2022, 311: 118664.
[28] Ju Liwei, Lü Shuoshuo, Zhang Zheyu, et al.Data-driven two-stage robust optimization dispatching model and benefit allocation strategy for a novel virtual power plant considering carbon-green certificate equivalence conversion mechanism[J]. Applied Energy, 2024, 362: 122974.
[29] 陈锦鹏, 胡志坚, 陈颖光, 等. 考虑阶梯式碳交易机制与电制氢的综合能源系统热电优化[J]. 电力自动化设备, 2021, 41(9): 48-55.
Chen Jinpeng, Hu Zhijian, Chen Yingguang, et al.Thermoelectric optimization of integrated energy system considering ladder-type carbon trading mechanism and electric hydrogen production[J]. Electric Power Automation Equipment, 2021, 41(9): 48-55.