Wanjun Huang, Changhong Zhao. Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration in the Presence of Renewables[J]. 中国电机工程学会电力与能源系统学报(英文), 2026,12(5):2404-2414.
Wanjun Huang, Changhong Zhao. Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration in the Presence of Renewables[J]. CSEE Journal of Power and Energy Systems, 2026, 12(5): 2404-2414.
Wanjun Huang, Changhong Zhao. Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration in the Presence of Renewables[J]. 中国电机工程学会电力与能源系统学报(英文), 2026,12(5):2404-2414.DOI: 10.17775/CSEEJPES.2022.08060.
Wanjun Huang, Changhong Zhao. Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration in the Presence of Renewables[J]. CSEE Journal of Power and Energy Systems, 2026, 12(5): 2404-2414.DOI: 10.17775/CSEEJPES.2022.08060.
Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration in the Presence of Renewables
摘要
Abstract
We propose an improved successive branch reduction (SBR) method to solve stochastic distribution network reconfiguration (SDNR) in the presence of renewables. This mixed-integer program is known to be computationally challenging. First
for a special distribution network with a single redundant branch
we propose an improved design for a one-stage SBR algorithm in the literature to incorporate uncertain renewable generations and loads. Based on solving stochastic optimal power flow
the improved algorithm identifies and searches through a small set of candidate branches
from which it determines the optimal branch to open and obtains a radial network with the minimum expected operational cost. Then
for a general network with multiple redundant branches
we design a heuristic two-stage SBR algorithm based on a close-and-open procedure that iteratively runs the proposed one-stage SBR algorithm. Numerical results on the IEEE 33-bus and 123-bus distribution network models verify the proposed method in terms of optimality and computational efficiency.
关键词
Keywords
references
29. Open Power System Data platform. “Data package for power system modelling”, 2022. [Online]. Available: https://doi.org/10.25832/time_series/2020-10-06