摘要
随着新能源装机容量不断攀升,电力系统灵活资源需求缺口不断扩大,新能源消纳问题日益突出。针对新能源发展目标,提出计及新能源不确定性与调峰调频需求的灵活资源多阶段优化配置方法。首先,分析电力系统灵活性供需平衡机理,并在此基础上提出面向灵活资源规划的灵活性评价指标。其次,计及调峰调频需求与新能源不确定性,构建基于多阶段随机规划的灵活资源优化配置模型,结合新能源发展目标与该模型,提出灵活资源多阶段优化配置算法。最后,在改进的IEEE39节点系统上对所提方法进行仿真测试,验证了所提方法的有效性,得到了兼顾新能源发展目标和整体经济性的灵活资源配置方案。
As the installed capacity of new energy continues to rise,the expansion of the gap in flexible resources demand in power systems is accelerating,and the problem of new energy consumption is becoming increasingly prominent.Aiming at the development goal of new energy,this article proposes a flexible resource multi-stage optimal allocation method that takes into account the uncertainty of new energy and the demand of peak and frequency regulation.Firstly,the mechanism of flexible supply and demand balance of power system is analyzed,and on this basis,the flexibility evaluation index for flexible resource planning is proposed.Secondly,taking into account the demand for peak and frequency regulation and the uncertainty of new energy,a flexible resource optimal allocation model based on multi-stage stochastic programming is constructed.Combining the new energy development goal with the model,a flexible resource multi-stage optimal allocation algorithm is proposed.Finally,the proposed method is simulated and tested on an improved IEEE 39-node system,the effectiveness of the proposed method is verified,and a flexible resource allocation scheme that takes into account the new energy development goal and the overall economy is obtained.
作者
余轶
陈峰
曾杨
张籍
颜玉林
李佳勇
YU Yil;CHEN Feng;ZENG Yang;ZHANG Jil;YAN Yulin;LI Jiayong(Economics and Technology Research Institute,State Grid Hubei Electric Power Co.,Ltd.,Wuhan 430072,China;College of Electrical and Information Engineering,Hunan University,Changsha 410082,China)
出处
《武汉大学学报(工学版)》
CAS
CSCD
北大核心
2024年第10期1394-1405,共12页
Engineering Journal of Wuhan University
基金
国网湖北省电力有限公司科技项目(编号:521538220006)。
关键词
灵活资源
优化配置
新能源不确定性
调峰调频
多阶段随机规划
flexible resources
optimal allocation
new energy uncertainty
peak and frequency regulation
multi-stage stochastic programming