Abstract
In this paper, Enhanced Aggressive Weed Optimization (EWO) algorithm is applied to solve the optimal reactive power Problem. Aggressive Weed Optimization is a stochastic search algorithm that imitate natural deeds of weeds in colonize and detection of appropriate place for growth and reproduction. Enhanced Aggressive Weed Optimization (EWO) algorithm is based on hybridization of genetic algorithm with weed optimization algorithm which refers combination of crossover and mutation of genetic algorithm, and by the use of the cross factor new species are arisen. Proposed Enhanced Aggressive Weed Optimization (EWO) algorithm has been evaluated in standard IEEE 118 & practical 191 bus test systems. Simulation results show that our projected approach outperforms all the entitled reported algorithms in minimization of real power loss and voltage profiles are within the specified limits.
Highlights
To improve the economy and safety of power system optimal reactive power problem has been acknowledged with huge attention
Proposed Enhanced Aggressive Weed Optimization (EWO) algorithm has been evaluated in standard IEEE 118 & practical 191 bus test systems
Simulation results show that our projected approach outperforms all the entitled reported algorithms in minimization of real power loss and voltage profiles are within the specified limits
Summary
To improve the economy and safety of power system optimal reactive power problem has been acknowledged with huge attention. Many conventional methods such as gradient based, interior point, linear programming & quadratic programming [1-6] have been to the reactive power problem. To improve the trade of between exploration & exploitation in order to reach the global solution, a new hybridized algorithm called Enhanced Aggressive Weed Optimization (EWO) algorithm proposed to solve the reactive power flow problem. It imitate the natural deeds of weeds in colonize and found a perfect place for growth and reproduction. Simulation results show that our projected approach outperforms all the entitled reported algorithms in minimization of real power loss and voltage profiles are within the specified limits
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