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Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II

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PROJECT TITLE :

Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II

ABSTRACT:

An improved nondominated sorting genetic algorithm-II (INSGA-II) has been proposed for optimal coming up with of multiple distributed generation (DG) units during this paper. First, multiobjective functions that take minimum line loss, minimum voltage deviation, and maximal voltage stability margin into thought have been shaped. Then, using the proposed INSGA-II algorithm to resolve the multiobjective designing drawback has been described well. The improved sorting strategy and the novel truncation strategy based mostly on hierarchical agglomerative clustering are utilised to keep the range of population. In order to strengthen the global optimal searching capability, the mutation and recombination ways in differential evolution are introduced to interchange the original one. Yet, a tradeoff method based on fuzzy set theory is employed to get the best compromise solution from the Pareto-optimal set. Finally, many experiments are made on the IEEE thirty three-bus take a look at case and multiple actual take a look at cases with the thought of multiple DG units. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been proved.


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Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II - 4.8 out of 5 based on 49 votes

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