考虑时序特性的配电网风-光-储随机规划模型

石玉东; 刘晋源; 徐松; 蒋卓臻; 高红均; 刘俊勇; 吕林

引用本文:	石玉东,刘晋源,徐松,等.考虑时序特性的配电网风-光-储随机规划模型[J].电力系统保护与控制,2019,47(10):23-32.
	SHI Yudong,LIU Jinyuan,XU Song,et al.Integrated wind-photovoltaic-storage stochastic planning model considering time-varying characteristics in distribution network[J].Power System Protection and Control,2019,47(10):23-32

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考虑时序特性的配电网风-光-储随机规划模型
石玉东¹,刘晋源²,徐松²,蒋卓臻²,高红均²,刘俊勇²,吕林²
(1.国网四川省电力公司，四川成都 610064;2.四川大学电气信息学院，四川成都 610065)

摘要:

针对分布式电源(Distributed Generation, DG)的不确定性和时序特性，构建了考虑时序特性的配电网风-光-储随机规划模型。首先对风电和光伏的时序特性和不确定性概率分布进行详细建模，并给出储能系统的充放电、容量限制约束模型。为充分融入随机规划，采用ARMA模型对风-光的不确定性运行工况进行场景抽取，并通过Kantorovich方法筛选获得10组典型场景。此外，建立以投资成本和运行成本为综合优化目标，二阶锥松弛支路潮流、储能、DG运行相关约束、安全约束等为约束条件的风-光-储投资随机规划模型。最后，通过修改的IEEE33节点系统进行算例分析，验证了该模型的有效性。

关键词: 配电网随机规划分布式能源时序特性负荷

DOI：10.7667/PSPC20191004

分类号:

基金项目:国家自然科学基金项目资助(51807125);中央高校基本科研业务费专项资金资助(YJ201750)

Integrated wind-photovoltaic-storage stochastic planning model considering time-varying characteristics in distribution network

SHI Yudong¹,LIU Jinyuan²,XU Song²,JIANG Zhuozhen²,GAO Hongjun²,LIU Junyong²,LÜ Lin²

(1. State Grid Sichuan Electric Power Company, Chengdu 610064, China;2. College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China)

Abstract:

Based on the uncertainty and time-varying characteristics of Distributed Generation (DG), a wind-photovoltaic- storage stochastic planning model of distribution network is presented in this paper. Firstly, the time-varying and uncertainty probability distribution of Wind Turbine Generation (WTG) output and Photovoltaic Generation (PVG) output are modeled in detail. The charging and discharging constraint and capacity constraint model of Energy Storage System (ESS) is also given. In order to make the planning model fully integrated into the stochastic programming approach, the ARMA model is used to generate a large amount of uncertain operation conditions of the wind power and solar power. Then 10 typical scenarios are selected from above various conditions by the Kantorovich method. In addition, a wind-photovoltaic-storage investment stochastic planning model is presented, which regards investment cost and operation cost as a comprehensive optimization goal while satisfying second-order cone relaxation based branch power flow model, operation constraints related energy storage and DG, security constraints, etc. Finally, the validity of proposed model is verified by the modified IEEE 33-node system. This work is supported by National Natural Science Foundation of China (No. 51807125) and Fundamental Research Funds for the Central Universities (No. YJ201750).

Key words: distribution network stochastic programming distributed generation (DG) time-varying characteristic

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