Open AccessOrdinal optimisation approach for complex distribution network reconfiguration
Author(s) -
Xing Haijun,
Hong Shaoyun
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9356
Subject(s) - control reconfiguration , computer science , ordinal optimization , mathematical optimization , genetic algorithm , encoding (memory) , node (physics) , estimation of distribution algorithm , tree (set theory) , algorithm , mathematics , artificial intelligence , embedded system , ordinal data , machine learning , engineering , mathematical analysis , structural engineering
The increasing complexity of the distribution system makes the practical distribution network operation much difficult. This paper presents an ordinal optimisation (OO) approach to solve the distribution network reconfiguration, which is an NP‐ hard problem with discrete control variables. OO uses crude and computationally fast model to reduce the search space. The spirit of OO is to seek the good enough solution instead of the best with high probability. The proposed approach is validated with two practical distribution systems, TPC 84 node test system. The results are compared with Optimal Flow Pattern (OFP), Common Genetic Algorithm (CGA), Partheno Genetic Algorithm with Tree Structure Encoding technology (TSE‐PGA) and Second‐Order Cone Programming (SOCP).