| 引用本文: | 杨茂,朱一丹,于欣楠,苏欣,王宇鑫,王金鑫,刘俊良.多时间尺度下考虑源-荷协同降碳的综合能源系统分布鲁棒低碳调度[J].电力自动化设备,2025,45(2):34-42. |
| YANG Mao,ZHU Yidan,YU Xinnan,SU Xin,WANG Yuxin,WANG Jinxin,LIU Junliang.Distributionally robust low-carbon scheduling of integrated energy system considering source-load collaborative carbon reduction under multiple time scales[J].Electric Power Automation Equipment,2025,45(2):34-42. |
|
| 摘要: |
| 为了降低综合能源系统运行过程中的碳排放水平，并考虑源-荷不确定性对调度结果的影响，提出多时间尺度下考虑源-荷协同降碳的综合能源系统分布鲁棒低碳调度策略。在考虑氢能的储液式碳捕集电厂中加入余热发电装置，建立碳捕集与封存-电制氢-有机朗肯循环模型。在荷侧引入综合需求响应，构建源-荷协同降碳机制，结合荷侧的“削峰填谷”进一步降低系统的碳排放。为了减少可再生能源出力不确定性对系统的影响，提出日前-日内多时间尺度滚动优化策略，日前阶段构建基于数据驱动的分布鲁棒优化模型；日内阶段基于日前调度结果，通过短时间尺度滚动优化降低功率波动的影响。算例仿真结果表明：所提模型和策略可以很好地实现系统低碳性和经济性的均衡。 |
| 关键词: 综合能源系统 源-荷协同降碳 碳捕集电厂 分布鲁棒优化 电制氢 多时间尺度 |
| DOI：10.16081/j.epae.202411012 |
| 分类号:TM73;TK01 |
| 基金项目:吉林省产业技术研究与开发项目(2023C033?5) |
|
| Distributionally robust low-carbon scheduling of integrated energy system considering source-load collaborative carbon reduction under multiple time scales |
|
YANG Mao1, ZHU Yidan1, YU Xinnan1, SU Xin1, WANG Yuxin1, WANG Jinxin1, LIU Junliang2
|
|
1.Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin 132012, China;2.Dandong Power Supply Company of Liaoning Electric Power Co.,Ltd.,Dandong 118000, China
|
| Abstract: |
| In order to reduce the level of carbon emission during the operation of the integrated energy system and consider the influence of the uncertainties of source-load on the scheduling results, a distributionally robust low-carbon scheduling strategy of integrated energy system considering source-load collaborative carbon reduction under multiple time scales is proposed. A waste heat power generation device is added to a liquid-storage carbon capture power plant considering hydrogen energy, and the model of carbon capture and storage-power to hydrogen-organic Rankine cycle is established. The integrated demand response is introduced in the load side, the source-load collaborative carbon reduction mechanism is constructed, and the carbon emission of the system is further reduced by combining the load-side peak shaving. In order to reduce the influence of renewable energy output uncertainty on the system, a day-ahead and intraday multi-time scale rolling optimization strategy is proposed. In the day-ahead stage, a data-driven distributionally robust optimization model is constructed. In the intraday stage, based on the day-ahead scheduling results, the influence of power fluctuation is reduced by the short time scale rolling optimization. The simulative results show that the proposed model and strategy can achieve a good balance between low-carbon performance and economy. |
| Key words: integrated energy system source-load collaborative carbon reduction carbon capture power plant distributionally robust optimization power to hydrogen multiple time scales |
