| 引用本文: | 王沛,张汉清,杨楠,邰能灵,赵亮.基于模型预测控制的掺氢微能源网低碳经济调度[J].电力自动化设备,2025,45(3): |
| WANG Pei,ZHANG Hanqing,YANG Nan,TAI Nengling,ZHAO Liang.Low-carbon economic scheduling of hydrogen-doped micro energy grid based on model predictive control[J].Electric Power Automation Equipment,2025,45(3): |
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| 摘要: |
| 为了实现微能源网(MEG)的低碳经济运行，抑制风光出力给系统带来的不确定性，重点考虑氢能制、储、用各环节与MEG的耦合关系，建立考虑绿电-电解-掺氢转换过程的MEG优化调度模型，提出基于深度学习的模型预测控制调度策略。通过夏、冬典型日的仿真验证所提策略的有效性，基于多个典型场景验证氢能交互和阶梯碳价的引入可有效引导MEG低碳经济运行。参数敏感性分析结果表明，燃机掺氢比和碳基价的增大均会提高系统运行成本，有效降低系统碳排放量。 |
| 关键词: 微能源网 掺氢燃机 模型预测控制 阶梯碳交易 低碳经济调度 |
| DOI：10.16081/j.epae.202412032 |
| 分类号:TM73;TK01 |
| 基金项目:国家自然科学基金联合重点项目(U2243243)；国家重点研发计划项目(2022YFE0101600) |
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| Low-carbon economic scheduling of hydrogen-doped micro energy grid based on model predictive control |
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WANG Pei1, ZHANG Hanqing1, YANG Nan2, TAI Nengling3, ZHAO Liang4
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1.College of Electrical and Power Engineering, Hohai University, Nanjing 211100, China;2.Nanjing Power Supply Company, State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 210000, China;3.Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;4.China Southern Power Grid Digital Grid Research Institute Co.,Ltd.,Guangzhou 510700, China
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| Abstract: |
| In order to realize the low-carbon economic operation of micro energy grid(MEG) and suppress the uncertainty brought by wind and photovoltaic power generation output, the coupling relationship between each aspect of hydrogen energy production, storage and usage and MEG is mainly considered, then the optimal scheduling model of MEG considering the green electricity-electrolysis-hydrogen blending conversion process is established and the model predictive control scheduling strategy based on deep learning is proposed. The effectiveness of the proposed strategy is verified by the simulation of typical summer and winter days. The results of several typical scenarios verify that the introduction of hydrogen energy interaction and ladder carbon price can effectively guide the low-carbon economic operation of MEG. The results of parameter sensitivity analysis show that the increase of hydrogen-doped ratio of gas turbine and carbon base price will increase the operation cost of the system and effectively reduce the carbon emission of the system. |
| Key words: micro energy grid hydrogen-doped gas turbine model predictive control ladder carbon trading low-carbon economic scheduling |
