Open AccessUncertainty handling in power system expansion planning under a robust multi‐objective framework
Author(s) -
Alizadeh Behnam,
Jadid Shahram
Publication year - 2014
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.2013.0674
Subject(s) - robustness (evolution) , monte carlo method , mathematical optimization , computer science , reliability (semiconductor) , taguchi methods , electric power system , reliability engineering , power (physics) , engineering , mathematics , machine learning , statistics , biochemistry , chemistry , physics , quantum mechanics , gene
In this study, a substantial idea has been reviewed which is useful in the investigation of the planning uncertainties. The concept relies on the optimality of an expansion plan in different conditions rather than the condition it has been optimised for. The method is developed in a manner that can be used in all sub‐systems (i.e. generation, transmission and distribution) expansion planning. However, in this study the idea has been assessed for generation expansion planning (GEP). Cost and reliability have been considered as two major objectives of the planning and robustness has been added as a supplementary objective. The method can deal with uncertainty in both coefficients of the objective functions and the constraints. Two GEP models, one static and the other dynamic, have been proposed to examine the performance of the method in the uncertainty handling. In addition, the efficiency of the Taguchi's orthogonal array testing method has been compared with Monte Carlo simulation in the scenario generation. Two case studies have been provided to simplify the justification on the efficiency of the method.