Open AccessDecision support system for optimal location of HIFDs in real distribution network using an integrated EPSO‐fuzzy AHP model
Author(s) -
Khani Milad,
Ghazi Reza,
Nazari Behnam
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6696
Subject(s) - analytic hierarchy process , particle swarm optimization , overhead (engineering) , weighting , ranking (information retrieval) , population , genetic algorithm , fuzzy logic , engineering , reliability engineering , computer science , mathematical optimization , operations research , mathematics , artificial intelligence , machine learning , medicine , demography , electrical engineering , sociology , radiology
Distribution overhead line network faults with the potential threats to public safety are of extreme importance. High‐impedance faults (HIFs) occur on distribution feeders with close proximity to the population. Advanced technology has enabled power distribution utilities to detect a high percentage of HIFs. However, the application of HIF detectors (HIFDs) should meet both operational and economic requirements due to expense and a large number of distribution feeders. Installation of these devices on overhead feeders among several candidate feeders seems to be a challenging issue. Therefore, ranking of feeders is essential for equipping them with HIFDs. This study proposes a practical approach which is an improved fuzzy analytic hierarchy process (AHP), accompanied by a constrained non‐linear optimisation model to extract optimal crisp priorities from fuzzified inputs, considering various criteria with a degree of inconsistency in their real data. This improved integrated model is also able to adequately evaluate both qualitative and subjective parts of the location‐allocation problems. In this study, enhanced particle swarm optimisation (EPSO) is used to deal with the optimisation problem for criteria weight ratio and also finding the individual feeder preference weighting to optimally locate HIFDs in distribution feeders. The proposed model is applied on a real network and then sensitivity analysis is performed in the optimal solution.