摘要
近年来分布式光伏发展迅猛,其发电功率间歇性和不确定性给配电网运行安全带来巨大威胁,亟需对配电网分布式光伏进行承载能力量化分析,以指导其科学开发.为此,考虑光伏发电功率不确定性,提出了一种基于机会约束规划的配电网分布式光伏承载能力评估方法.首先,基于分布式光伏历史运行数据,采用高斯混合模型对其发电功率概率分布进行建模表征;其次,考虑线路热稳定约束、电压安全约束以及设备运行约束,将光伏出力视作随机变量,建立了基于机会约束规划的配电网分布式光伏承载能力评估模型;然后,推导建立了分布式光伏发电功率与线路潮流、节点电压等系统状态变量间的仿射关系,通过计算累积分布函数在给定置信度下的分位点实现机会约束的确定性转化;最后,在一个改进的测试系统上验证了所提方法的有效性.
The intermittency and uncertainty of rapidly developed distributed PV(DPV)pose great threats to the safe operation of distribution networks,so it is urgent to quantify DPV hosting capacity of the distribution network to facilitate the reasonable and scientific development of DPV.In this regard,considering the uncertainty of PV generation,a chance-constrained DPV hosting capacity assess method for distribution networks is proposed.Firstly,the Gaussian mixture model is adopted to model and characterize the probability distribution of DPV generation based on the yearly historical data.Secondly,considering the power flow constraints,voltage constraints and equipment operating constraints and treating the DPV generation as random variables,a chance-constrained optimization-based distribution network DPV hosting capacity assess model is established.Then,by deriving the affine relationships between DPV generation and state variables such as power flows and node voltages,the chance-constrained terms are converted into deterministic counterparts based on the obtained quantiles at a given confidence level.Finally,case studies on a modified test system verify the effectiveness of the proposed method.
作者
丁琦欣
覃洪培
万灿
彭琰
李昀熠
DING Qixin;QIN Hongpei;WAN Can;PENG Yan;LI Yunyi(College of Electrical Engineering,Zhejiang University,Hangzhou Zhejiang 310027;Polytechnic Institute,Zhejiang University,Hangzhou Zhejiang 310015;State Grid Zhejiang Electric Power Research Institute,Hangzhou Zhejiang 310014)
出处
《东北电力大学学报》
2022年第6期28-38,共11页
Journal of Northeast Electric Power University
基金
国家电网公司科技项目(5108-202218280A-2-446-XG)。
关键词
承载能力分析
配电网
分布式光伏
不确定性
机会约束规划
高斯混合模型
Hosting capacity assessment
Distribution network
Distributed photovoltaic
Uncertainty
Chance constrained programming
Guassian mixture model
