arrow
Return

Three-phase feeder parameter estimation using multi-run optimization and search space refinement strategy

delete2025-12-18
delete0
delete
OA
AI
N
Nien‐Che Yang *
S
Shan-Chun Pai
DOI:10.1016/j.rineng.2025.108816delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
• Eliminates symmetric parameter assumptions. • Achieves MAPE <0.05 % under ±0.5 % noise and <0.26 % under ±5 % noise. • Integrates Pareto front, MRO, and bisection-based. • Identifies outliers and proposes mitigation strategies.
Keywords:
Distribution line parameter estimation
Multi-objective optimization
Pareto front solution set
Multi-run optimization (MRO)
Bisection method
Minimum Manhattan distance (MMD)
Adaptive search space refinement
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Results in Engineering cover
Results in Engineering
IF:
7.9
Papers:
1.2W
Citations:
1.7W

Organization

No organization information available
Cited Papers

Cited Papers

A new multi objective crested porcupines optimization algorithm for solving optimization problems
err2025-04-24
err0
errOAAI
errAdalja, Divya; Patel, Pinank; Mashru, Nikunj; Jangir, Pradeep; Arpita; Jangid, Reena; Gulothungan, G.; Khishe, Mohammad
errShare
errSave
researcher View more