摘要
在全球变暖的背景下,转折天气的频发给电力系统运行安全带来了前所未有的挑战。首先,基于转折天气的定义,明确了不同新能源机组的转折天气,分析其对机组出力的影响,并构建了转折天气下的新能源机组出力模型。其次,提出了一种基于历史数据的典型转折天气场景生成方法,通过提取历史数据中分季节、分时段的基准转折频率,抽样生成转折二进制变量,实现考虑转折过程的转折天气时序生成。再次,基于不同新能源机组的转折特性,构建计及新能源机组-储能联合规划的含多类型储能电源容量优化模型。最后,采用改进的IEEE 30节点系统进行算例分析,结果表明所提出的模型能够有效应对转折天气,从而验证了其有效性。
Against the backdrop of global warming,the increasing frequency of transitional weather poses unprecedented challenges to the operational safety of power systems.Firstly,this paper clarifies the definition of transitional weather for different new energy units,analyzes its impact on unit output,and constructs an output model for new energy units under transitional weather conditions.Additionally,a typical transitional weather scenario generation method based on historical data is proposed.By extracting baseline transitional frequencies by season and time period from historical data and sampling to generate transitional binary variables,the time series generation of transitional weather that considers transitional processes is achieved.Furthermore,based on the transitional characteristics of different new energy units,an energy capacity optimization model incorporating the joint planning of new energy units and multiple types of energy storage is constructed.Finally,an improved IEEE 30-bus system is used for case analysis.The results demonstrate that the proposed model can effectively address transitional weather,verifying its effectiveness.
作者
刘娟
司大军
张程
李鸿生
杨易达
贺帅佳
高红均
LIU Juan;SI Dajun;ZHANG Cheng;LI Hongsheng;YANG Yida;HE Shuaijia;GAO Hongjun(Center of Power Grid Planning and Constructing,Yunnan Power Grid Ltd.,Kunming 650011,China;Guangzhou Haiyi Software Co.,Ltd.,Guangzhou 510660,China;College of Electrical Engineering,Sichuan University,Chengdu 610065,China)
出处
《供用电》
北大核心
2025年第3期3-13,共11页
Distribution & Utilization
基金
国家重点研发计划“支撑20%新能源电量占比场景下的电网智能调度关键技术”(2022YFB2403500)
中国南方电网有限责任公司科技项目“融合安全充裕供电和清洁能源消纳双重目标的新型电力系统规划技术研究及应用”(YNKJXM20230619)。
关键词
转折天气
新能源
场景生成
电力系统
电源容量优化
transitional weather
new energy
scenario generation
power system
power capacity optimization
