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An immune based approach to enhance the performance of electrical distribution system through capacitor placement is proposed in this paper. Major challenges that occur in distribution system are voltage drop and real power losses. The placement and sizing calculations of capacitor gives more insight to solve problems, which occur while maintaining voltage profiles at each bus by reducing voltage drops in each branch. The performance of the electrical distribution system can be improved with the above proposed technique. This technique have two sub methods, one for finding capacitor location through heuristic and second one for finding capacitor size through genetic algorithm and the proposed methods are tested on IEEE 33 and 69 bus systems to reduce the real power losses with better voltage profile at each load buds and the results are validated.
Around 33% of the engendered power is wasted as heat during distribution of puissance. The presence of reactive elements further increases authentic and reactive power losses since they draw more current than resistive elements. Hence in order to amend efficiency of the distribution system, capacitor banks are to be placed at congruous locations.The placement of capacitor banks additionally amends the voltage profile of the system. Thus the capacitor bank placement is vital for power flow control, ameliorating system stability, power factor rectification, voltage profile management and the reduction in energy losses. Capacitor placement is used to minimize active and reactive power losses in electrical distribution system and also attain quality power supply. If proper selection and placement of capacitor is not done then it behaves in abnormal way and voltage drops may increase beyond limits and effects the system with more power losses with poor voltage profile at each load bus. Considering the above problems, many researchers are working for the best solution using various methods. Among them some of the techniques are taken as main choices like Particle swarm optimization, Genetic Algorithm, Ant colony algorithm, Fuzzy evolutionary programming, simulated annealing etc.
A new approach of using immune based optimization to solve capacitor placement problem . In this paper they considered two methods one is simulated annealing[SA] and other is mixed integer programming, SA is used to find computation time and system cost whereas mixed integer programming decomposed into two problems, master and slave. The master is used to determine capacitor location and slave is used to find type and size of the capacitors. It is applied for an IEEE-69 test bus system. Mixed integer programming  is used for determining placement of capacitor and its size, but the assumptions made in this are not permissible. Applying loss sensitivity factor and genetic algorithm for calculating location and size of capacitor  had shown an improvement in voltage regulation. These methods are applied for an IEEE-34 bus, 15 bus,and 69 bus test systems. DG placement in distribution network for power loss minimization using genetic algorithm .Genetic algorithm is applied for a IEEE-33 bus system where the GA are compared with the results of harmony search algorithm using Matlab. Large number of capacitor banks may reduce reactive power demand from conventional generators, but it can affect generators and transmission line performance. In this power DG’s are used with capacities ranging from 1 kW to 1000 MW. To overcome drawbacks like system power less, voltage fluctuation etc
In this paper a new approach of immune based optimization is introduced. For voltage drop reduction and minimization of power loss a pre-eminent approach is done using heuristic and genetic algorithm. The performances before and after proper placement of capacitor drastically improved.
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