摘要
由于没有考虑到历史数据负荷变化对当前电网的影响,造成配电网无法最优状态运行,因此设计一种考虑大数据的主动配电网双层定性规划方法。以风电机组为例,在K-means聚类算法下得到聚类中心曲线与配电网区域间的联系程度描述方式,构建配电网电源出力负荷时序场景,获取配电网上、下层的规划模型,以网损和电压偏差作为优化指标,得到最优的主动配电网双层定性规划方法。算例分析结果表明:不同季节下,所设计的规划方法的算例配电网网损和电压偏差都低于传统的规划方法,说明该规划方法在实际的应用中能够提升配电网的运行状态。
Because the impact of historical data load changes on the current power grid is not considered,the distribution network cannot op-erate optimally,so this paper designs a two-level qualitative planning method for active distribution network considering big data.Taking the wind turbine as an example,under the K-means clustering algorithm,the description method of the connection degree between the cluster center curve and the distribution network region is obtained,the power output load sequence scenario of the distribution network is constructed,the planning model of the distribution network and the lower layer is obtained,and the optimal active distribution network two-level qualitative planning method is obtained by taking the network loss and voltage deviation as the optimization indicators.The analysis result of the example shows that under different seasons,the network loss and voltage de-viation of the distribution network using the planning method designed in this paper are lower than that of the traditional planning method,indicating that the planning method can improve the operation status of the distribution network in practical application.
作者
黄存强
安娟
田旭
李俊贤
米金梁
HUANG Cun-qiang;AN Juan;TIAN Xu;LI Jun-xian;MI Jin-liang(Economic and Technological Research Institute of State Grid Qinghai Electric Power Company,Xining 810000 China)
出处
《自动化技术与应用》
2025年第2期163-166,共4页
Techniques of Automation and Applications
基金
国网青海省电力公司经济技术研究院专题研究项目(SGQHJY00GHJS2100251)。
关键词
大数据
主动配电网
K-MEANS聚类算法
目标函数
big data
active distribution network
K-means clustering algorithm
objective function
