| 引用本文: | 朱健宇,潘学萍,王正风,王吉文,孙晓荣,史雯,秦景辉.兼顾碳减排和新能源消纳的火电机组深度调峰与复合储能协调规划[J].电力自动化设备,2024,44(1):17-23. |
| ZHU Jianyu,PAN Xueping,WANG Zhengfeng,WANG Jiwen,SUN Xiaorong,SHI Wen,QIN Jinghui.Coordinated planning of thermal generator deep peak regulation and composite energy storage considering carbon emission reduction and new energy consumption[J].Electric Power Automation Equipment,2024,44(1):17-23. |
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| 摘要: |
| 火电机组深度调峰、化学储能以及抽水蓄能是电网灵活性资源的重要组成部分，对三者进行协调规划能在保障电网安全低碳运行的同时，提升新能源的接纳能力。从经济性、碳减排量、弃风弃光量3个方面，构建了火电机组深度调峰和复合储能协调的多目标规划模型；提出了基于熵权的改进非支配排序遗传算法(NSGA-Ⅱ)求解多目标规划模型，获得Pareto最优解集，并进一步根据模糊隶属度得到综合最优解。以某省级电网2025年、2030年的预测数据为例进行仿真验证，结果表明：采用改进NSGA-Ⅱ可提升多目标优化的求解速度与精度；火电机组深度调峰协同储能配置可显著减小弃风弃光率，有利于电力系统的低碳经济运行。 |
| 关键词: 火电机组 深度调峰 复合储能 碳减排 新能源消纳 多目标优化 协调规划 改进NSGA-Ⅱ |
| DOI：10.16081/j.epae.202303003 |
| 分类号:TM715 |
| 基金项目:国家自然科学基金资助项目(52077061) |
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| Coordinated planning of thermal generator deep peak regulation and composite energy storage considering carbon emission reduction and new energy consumption |
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ZHU Jianyu1, PAN Xueping1, WANG Zhengfeng2, WANG Jiwen2, SUN Xiaorong1, SHI Wen1, QIN Jinghui1
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1.College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China;2.State Grid Anhui Electric Power Co.,Ltd.,Hefei 230061, China
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| Abstract: |
| Thermal generator deep peak regulation, chemical energy storage and pumped storage are important components of the flexibility resources in power grid. The coordinated planning of these three flexibility resources can ensure the safe and low-carbon operation of power grid and improve the acceptance capacity of new energy. From three aspects of economy, carbon emission reduction and wind and photovoltaic curtailment, a multi-objective coordinated planning model of thermal generator deep peak regulation and composite energy storage is constructed. An improved non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ) based on entropy weight is proposed to solve the multi-objective planning model. The Pareto optimal solution set is obtained, and the comprehensive optimal solution is obtained according to fuzzy membership degree. Taking the predicted data of a provincial power grid in 2025 and 2030 as the example, the simulative results show that the improved NSGA-Ⅱ can improve the solving speed and accuracy of the multi-objective optimization. The coordination of thermal generator deep peak regulation and composite energy storage configuration can significantly reduce the wind and photovoltaic curtailment rate, which is conducive to low-carbon and economic operation of power system. |
| Key words: thermal generators deep peak regulation composite energy storage carbon emission reduction new energy consumption multi-objective optimization coordinated planning improved NSGA-Ⅱ |
