Title :
Meta-heuristic algorithms-based real power loss minimisation including line thermal overloading constraints
Author :
El-Fergany, Attia A. ; El-Arini, Mahdi
Author_Institution :
Electr. Power & Machine Dept., Zagazig Univ., Zagazig, Egypt
Abstract :
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.
Keywords :
cost reduction; genetic algorithms; losses; minimisation; power transmission economics; simulated annealing; control variables; equality constraints; genetic algorithm; hybridised simulated annealing; inequality constraints; integrated evolutionary approach; line thermal overloading constraints; load patterns; meta-heuristic algorithm-based real power loss minimisation; pattern search; power transmission; power-system network; single-line outages;
Journal_Title :
Generation, Transmission & Distribution, IET
DOI :
10.1049/iet-gtd.2012.0649