Provide a practical approach in planning and placement of distributed generation sources based on multi-objective genetic algorithms

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Abstract

Increasing rate of scattered productions in electrical energy resources has led to pay more attention in planning accuracy. For example, location, capacity and DG incorrect numbers, can increase the rate of losses and damages to the power grids. Diversity and contradiction in objective functions, the uncertainty of the usefulness or having problem with a proper procedure, are the issues that are discussed in new techniques for energy resources. In this paper, in order to increase the accuracy and processing speed, instead of the conventional single-objective algorithms such as genetic algorithm, particle swarm algorithm, ant colony algorithm and etc, a multi-objective optimization location and determination of DG capacities in the power systems has been discussed. The sample network with planning horizon for implementing and using non-dominant sorting genetic algorithm, has been modeled in Matpower toolbox in MATLAB. DG initial and operational planning costs with respect to the certain proposed time period has been considered. The results show that the proposed multi objective plan, lets us to apply various solutions. It also gives the independency from the grid and maximum yield by choosing less objective functions.

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History

  • Receive Date: 30 January 2019
  • Revise Date: 25 November 2024
  • Accept Date: 30 January 2019
  • Publish Date: 22 June 2018

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