Increasing PV Hosting Capacity With an Adjustable Hybrid Power Flow Model

被引:11
作者
Zhang, Luomeng [1 ]
Ye, Hongxing [1 ]
Ding, Fei [2 ]
Li, Zuyi [3 ]
Shahidehpour, Mohammad [3 ]
机构
[1] Xi An Jiao Tong Univ, MOE KLINNS Lab, Xian, Peoples R China
[2] US Natl Renewable Energy Lab, Golden, CO 80401 USA
[3] IIT, Chicago, IL 60616 USA
关键词
Convexification; renewable; surrogate affine policy; uncertainty; DISTRIBUTION NETWORKS; ENERGY-STORAGE; SOLAR PV;
D O I
10.1109/TSTE.2022.3215287
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Physical constraints must be enforced when distributed energy resources, such as PV, are integrated into distribution network. Hosting capacity (HC) is thus introduced to define the maximum renewable generation that distribution system can accommodate. When the grid is further pushed towards decarbonization, improving HC becomes even more important. This work presents a hybrid adjustable power flow model to increase the uncertainty-proof HC, aiming to securely and cost-effectively utilize flexible resources. We propose a novel hybrid relaxation approach to convexifying a two-stage AC model with variable uncertainty set. An iterative algorithm is designed to solve the problem. We perform the case study in a single-phase 141-node system and a three-phase 33-bus system. The proposed approach shows promising performance in accuracy, convergence, and robustness.
引用
收藏
页码:409 / 422
页数:14
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