计及频率特性的高比例可再生能源电力系统概率潮流分析Probabilistic Power Flow Analysis of High-proportion Renewable Energy Power System Considering Frequency Characteristics
朱轶伦,张东波,陈新建,丁春燕,王周虹,洪骋怀
ZHU Yilun,ZHANG Dongbo,CHEN Xinjian,DING Chunyan,WANG Zhouhong,HONG Chenghuai
摘要(Abstract):
在当前国家大力实施清洁能源战略的背景下,为提高电力系统概率潮流分析的准确性,设计了一种计及频率特性的高比例可再生能源电力系统概率潮流分析方法。首先建立交流潮流模型,将影响因素记作输入随机变量,得到系统潮流的随机变量线性组合形式;在此基础上,对输入随机变量进行相关性处理;最后,考虑系统频率偏差,对发电机出力进行迭代计算,实现概率潮流的实时计算。应用上述方法对IEEE 14节点算例进行概率潮流仿真计算,结果表明该方法在准确性方面具有明显优势,具有实际应用意义。
In the context of vigorous promotion of clean energy strategy in China, a probabilistic power flow analysis method of high-proportion renewable energy power system considering frequency characteristics is formulated to improve probabilistic power flow analysis accuracy of power system. Firstly, an AC power flow model is established, where the influencing factors are represented as random input variables, and the power flow of the system is obtained in the form of a linear combination of random variables. Then, the problem of correlated random variables is solved. Finally, in view of the system frequency deviation, iterative calculation on the output power of generators is carried out to realize real-time calculation of probabilistic power flow.The proposed method is employed in probabilistic power flow calculation on IEEE 14 bus, and the result shows that it is of superiority in precision and practicability.
关键词(KeyWords):
可再生能源;电力系统;概率潮流;随机变量相关性
renewable energy;power system;probabilistic power flow;correlation of random variables
基金项目(Foundation): 浙江省电力学会软科学研究项目(2020KJ-R02)
作者(Author):
朱轶伦,张东波,陈新建,丁春燕,王周虹,洪骋怀
ZHU Yilun,ZHANG Dongbo,CHEN Xinjian,DING Chunyan,WANG Zhouhong,HONG Chenghuai
DOI: 10.19585/j.zjdl.202105002
参考文献(References):
- [1]SUN W G,ZAMANI M,HESAMZADEH M R,et al.Datadriven probabilistic optimal power flow with nonparametric Bayesian modeling and inference[J].IEEE Transactions on Smart Grid,2020,11(2):1077-1090.
- [2]刘宇,高山,杨胜春,等.电力系统概率潮流算法综述[J].电力系统自动化,2014,38(23):127-135.
- [3]SHU T,LIN X Y,PENG S,et al.Probabilistic power flow analysis for hybrid HVAC and LCC-VSC HVDC system[J].IEEE Access,2019,7:142038-142052.
- [4]叶晨,崔双喜,王维庆.含风电的电力系统概率潮流计算[J].电网与清洁能源,2018,34(2):167-172.
- [5]PERNINGE M,LINDSKOG F,SODER L.Importance sampling of injected Powers for electric power system security analysis[J].IEEE Transactions on Power Systems,2012,27(1):3-11.
- [6]王晗,严正,徐潇源,等.计及可再生能源不确定性的孤岛微电网概率潮流计算[J].电力系统自动化,2018,42(15):110-117.
- [7]ZOU B,XIAO Q.Solving probabilistic optimal power flow problem using quasi Monte Carlo method and ninth-order polynomial normal transformation[J].IEEE Transactions on Power Systems,2014,29(1):300-306.
- [8]SAUNDERS C S.Point estimate method addressing correlated wind power for probabilistic optimal power flow[J].IEEE Transactions on Power Systems,2014,29(3):1045-1054.
- [9]VERBIC G,CANIZARES C A.Probabilistic optimal power flow in electricity markets based on a two-point estimate method[J].IEEE Transactions on Power Systems,2006,21(4):1883-1893.
- [10]LI X,LI Y Z,ZHANG S H.Analysis of probabilistic optimal power flow taking account of the variation of load power[J].IEEE Transactions on Power Systems,2008,23(3):992-999.
- [11]MOHAMMADI M,BASIRAT H,KARGARIAN A.Nonparametric probabilistic load flow with saddle point approximation[J].IEEE Transactions on Smart Grid,2018,9(5):4796-4804.
- [12]SCHELLENBERG A,ROSEHART W,AGUADO J.Cu mulant-based probabilistic optimal power flow(P-OPF)with Gaussian and gamma distributions[J].IEEE Transactions on Power Systems,2005,20(2):773-781.
- [13]TAMTUM A,SCHELLENBERG A,ROSEHART W D.Enhancements to the cumulant method for probabilistic optimal power flow studies[J].IEEE Transactions on Power Systems,2009,24(4):1739-1746.
- [14]余昆,曹一家,陈星莺,等.含分布式电源的地区电网动态概率潮流计算[J].中国电机工程学报,2011,31(1):20-25.
- [15]WANG Z W,SHEN C,LIU F,et al.Analytical expressions for joint distributions in probabilistic load flow[J].IEEE Transactions on Power Systems,2017,32(3):2473-2474.
- [16]刘梦依,邱晓燕,张楷,等.计及源-荷不确定性的高比例可再生能源系统协同优化运行[J].电力建设,2018,39(12):55-62.
- [17]程耀华,张宁,王佳明,等.面向高比例可再生能源并网的输电网规划方案综合评价[J].电力系统自动化,2019,43(3):33-42.
- [18]秦玉杰,胡健,焦提操.基于泛在电力物联网的分布式可再生能源(DRE)理性消纳调峰模型[J].电力建设,2019,40(12):120-128.
- [19]何剑.泛欧电力系统概率充裕性评估应用及启示[J].电网技术,2018,42(8):2681-2686.
- [20]赵昱宣,韩畅,林振智,等.含可再生能源的电力系统两阶段核心骨干网架优化策略[J].电网技术,2019,43(2):371-386.
- [21]林鸿基,闫园,文福拴,等.高比例可再生能源电力系统中计及灵活调节产品的实时调度[J].电力建设,2019,40(10):18-27.
- [22]张旭,王洪涛.高比例可再生能源电力系统的输配协同优化调度方法[J].电力系统自动化,2019,43(3):67-75.
- [23]柳志航,卫志农,高昇宇,等.源-荷互动环境下含高比例风电并网的自适应线性化概率潮流计算[J].电网技术,2019,43(11):3926-3937.
- [24]苏宏升,严岩,车玉龙.含光伏电场的电力系统概率潮流计算[J].控制工程,2018,25(12):2197-2202.
- [25]毛晓明,叶嘉俊.主元分析结合Cornish-Fisher展开的概率潮流三点估计法[J].电力系统保护与控制,2019,47(6):66-72.
- [26]董晓阳,苏宏升,罗世昌.考虑风电出力相关性的概率最优潮流计算[J].三峡大学学报(自然科学版),2019,41(5):90-95.
- [27]麻金碧,贾燕冰,李玉博.基于概率潮流的电力系统关键线路辨识方法[J].计算机仿真,2019,36(8):96-102.
- [28]廖星星,吴奕,卫志农,等.基于GMM及多点线性半不变量法的电-热互联综合能源系统概率潮流分析[J].电力自动化设备,2019,39(8):55-62.
- [29]王之伟,陆晓,刁瑞盛,等.基于深度强化学习的电网自主控制与决策技术[J].电力工程技术,2020,39(6):34-43.
- [30]李雪亮,田鑫,郝露茜,等.基于概率潮流风险计算的电网优化规划方法研究[J].电网与清洁能源,2020,36(11):90-99.
- [31]李韵喻,梁有珍,甄文喜,等.考虑光伏非线性相关性的电力系统概率潮流计算[J].电网与清洁能源,2019,35(6):69-75.
- [32]张亚丽,饶日晟,苗丽芳,等.基于概率潮流的电网安全风险分析[J].内蒙古电力技术,2019,37(5):1-5.
- [33]储琳琳,张宇俊,刘云晖,等.计及分布式电源随机出力的配电网多目标无功优化[J].电器与能效管理技术,2019(12):42-48.
- 可再生能源
- 电力系统
- 概率潮流
- 随机变量相关性
renewable energy - power system
- probabilistic power flow
- correlation of random variables