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The Renewable Energy reasons to economical issues, environmental and rising demand of energy consumption are expanding the day to day. Due to capabilities-aligned decentralized this equipment, Placement program and sizing its, important problem of power system operation. In this paper, a combined approach is presented for optimal placement and sizing recent technology developments of photovoltaic units, DFIG based wind turbine and fuel cell units, only these generators are considered. This work presents a multi objective optimization algorithm for the sitting and sizing of renewable electricity generators. The objectives consist of minimization of costs, active and reactive losses of distributed system. Optimal Placement and sizing of the equipment is carried out by using Particle Swarm Optimization algorithm continuously. Fuzzy logic is used in order to compare the composition of active and reactive losses in optimization. In this paper, softwares DIgSILENT/MatLab , which has bilateral information relation, is also used for the simulations. The studies are executed on a typical IEEE 33 bus test system. The results show that the proposed algorithm can improve performance & efficiency of system.  

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Abstract: This paper presents a modified method based on teaching learning based optimization algorithm to solve the problem of the single- and multi-objective optimal location of distributed generation units to cope up the load growth in the distribution network .Minimizing losses, voltage deviation, energy cost and improved voltage stability are the objective functions in this problem. Load growth in a system is a natural phenomenon. As the value of distribution system indices depend on load growth, any change in load causes changes in distribution system indices. Therefore, for assessing the current studies the level of validity and the adequacy of system in future, load growth in future are discussed. The proposed algorithm integrates an adaptive teaching factor, and a crossover and mutation strategy. In the proposed algorithm, an external repository is considered to save non-dominated (Pareto) solutions. Since the objective functions are not the same, a fuzzy clustering technique is used to select the best compromise solution from the repository. The proposed algorithm is tested on the 33-bus IEEE test system. To demonstrate the effectiveness of the proposed approach, simulation results are compared with the results obtained by other methods.