Open AccessMeta‐heuristic algorithms‐based real power loss minimisation including line thermal overloading constraints
Author(s) -
ElFergany Attia A.,
ElArini Mahdi
Publication year - 2013
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.2012.0649
Subject(s) - simulated annealing , minimisation (clinical trials) , electric power system , computer science , mathematical optimization , control variable , tie line , transmission line , electric power transmission , transmission loss , algorithm , reliability engineering , power (physics) , mathematics , engineering , statistics , telecommunications , physics , quantum mechanics , machine learning , electrical engineering
This study presents an integrated evolutionary approach to minimise the real power losses in a given power‐system network to improve the system performance and to reduce the overall cost of power transmission. The integration of the genetic algorithm and hybridised simulated annealing with pattern search are proposed and applied to determine the optimum adjustments to the control variables. The approach satisfies and maintains the equality and inequality constraints. The proposed method is applied to many test systems with different operating scenarios. The numerical test results and simulations with different load patterns and single‐line outages were demonstrated and analysed. The effects of changing the control variables were studied and investigated as well. The results obtained show the effectiveness, flexibility and applicability of the proposed approach for power loss minimisation by considering the overload condition of lines with high accuracy and within somehow an acceptable computational time.