Open AccessMulti‐objective Taguchi approach for optimal DG integration in distribution systems
Author(s) -
Meend K.,
Swarnkar Anil,
Gupta Nikhil,
Niazi Khaleequr R.
Publication year - 2017
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.2016.2126
Subject(s) - taguchi methods , mathematical optimization , node (physics) , computation , euclidean distance , ideal solution , computer science , similarity (geometry) , orthogonal array , euclidean geometry , algorithm , mathematics , engineering , machine learning , artificial intelligence , physics , geometry , structural engineering , image (mathematics) , thermodynamics
This study presents a new multi‐objective Taguchi approach for optimal integration of distributed generations (DGs) in small and large scale distribution networks. The Taguchi method (TM) is a statistical method and employs orthogonal arrays (OAs) to estimate the output response in less number of computations. In every cycle, OA is updated according to mean response of each parameter at its respective levels in the previous cycle. A new node priority list is proposed to guide TM to select promising nodes. For multi‐objective problems, a trade‐off is developed between various objectives using the technique for order of preference by similarity to ideal solution that reduces Euclidean distances of various objectives from their best solutions and increases Euclidean distances from their worst solutions. A multi‐objective DG integration problem is formulated to demonstrate the applicability of the proposed approach and tested on IEEE 33‐bus, 118‐bus and a practical 201‐bus radial distribution systems. The simulation results are compared with existing multi‐objective optimisation techniques used for optimal DG integration problems in the literature and found to be promising.