scholarly journals REDUCTION OF ACTIVE POWER LOSS BY ADAPTIVE CHARGED SYSTEM SEARCH ALGORITHM

Author(s):  
K. Lenin

This paper presents a new optimization algorithm called Adaptive Charged System Search Algorithm (ACA) for solving optimal power problem. Coulomb law from electrostatics and the Newtonian laws of mechanics are forming the basics of the proposed algorithm. Adaptive Charged System Search Algorithm (ACA) is a multi-agent approach in which each agent is a Charged Particle (CP) & they affect each other based on their fitness values, separation of distances. The quantity of the resultant force is determined by using the electrostatics laws and the quality of the movement is determined using Newtonian mechanics laws. Proposed Adaptive Charged System Search Algorithm (ACA) has been tested in Standard IEEE 57,118 bus systems & real power loss has been comparatively reduced with voltage profiles are within the limits.

Author(s):  
Kanagasabai Lenin

In this work Opposition based Kidney Search Algorithm (OKS) is used to solve the optimal reactive power problem. Kidney search algorithm imitates the various sequences of functions done by biological kidney. Opposition based learning (OBL) stratagem is engaged to commence the algorithm. This is to make certain high-quality of preliminary population and to expand the exploration steps in case of stagnation of the most excellent solutions. Opposition based learning (OBL) is one of the influential optimization tools to boost the convergence speed of different optimization techniques. The thriving implementation of the OBL engages evaluation of opposite population and existing population in the similar generation to discover the superior candidate solution of a given reactive power problem.  Proposed Opposition based Kidney Search Algorithm (OKS) has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show that the proposed algorithm reduced the real power loss efficiently.


Author(s):  
K. Lenin

In this paper, an Improved Tabu Search (ITS) algorithm has been proposed to solve the optimal reactive power problem. In this work Tabu Search- has been hybridized with Simulated Annealing algorithm to solve the optimal reactive power problem. Hybridization of these two algorithms improves the exploration & exploitation capabilities during the search. Proposed Improved Tabu Search (ITS) algorithm has been tested in Standard IEEE 57,118 bus systems & real power loss has been comparatively reduced with voltage profiles are within the limits.


2018 ◽  
Vol 6 (10) ◽  
pp. 130-138
Author(s):  
K. Lenin

This paper presents Coyote Search Algorithm (CSA) for solving optimal reactive power problem. Coyote Search Algorithm is a new bio – inspired heuristic algorithm which based on coyote preying behaviour. The way coyote search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power problem. And the specialty of coyote is possessing both individual local searching ability & autonomous flocking movement and this special property has been utilized to formulate the search algorithm. The proposed Coyote Search Algorithm (CSA) has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the good performance of the proposed algorithm in reducing the real power loss.


Author(s):  
K. Lenin

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.


2013 ◽  
Vol 397-400 ◽  
pp. 1113-1116
Author(s):  
Xiao Meng Wu ◽  
Wang Hao Fei ◽  
Xiao Mei Xiang ◽  
Wen Juan Wang

In order to solve the problem in reactive power compensation of oilfield distribution systems at present, a Taboo search algorithm is proposed in this paper, by which the optimal location and size of shunt capacitors on distribution systems are determined. Then the voltage profile is improved and the active power loss is reduced. In this paper, Voltage qualified is used as objective function to search an initial solution that meets the voltage constraints so that it is feasible in practicable voltage range; then the global optimum solution can be got when taking the reduced maximum of active power loss as objective unction. The examples show that the improved algorithm is feasible and effective.


2014 ◽  
Vol 41 (4) ◽  
pp. 1168-1175 ◽  
Author(s):  
Radu-Emil Precup ◽  
Radu-Codruţ David ◽  
Emil M. Petriu ◽  
Stefan Preitl ◽  
Mircea-Bogdan Rădac

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