Optimal sizing and sitting of distributed generation using Hybrid GA-PSO Algorithm

    This project is design based on the concept "Optimal sizing and sitting of distributed generation using Particle Swarm Optimization Guided Genetic Algorithm".  This project attempts to minimize losses and at the same time maintain acceptable voltage profiles in a radial distribution system. Distributed generation (DG) is a hot topic due to the ever-increasing demands for electrical energy. Thus, this project optimally size and place DGs in appropriate buses in the system, making the problem such a way reducing real power losses, operating cost and enhancing the voltage stability, which becomes the objective function. Voltage profile improvement is considered as a constraint in finding the optimal placement of DG. Since the problem involves optimization of variables, a new hybrid optimization method integrating two powerful well-established techniques is proposed. The prime idea of the proposed technique is to utilize the key features of both techniques to collectively and effectively search for better optimization results. The proposed algorithm is applied and demonstrated on the IEEE 33 bus distribution systems. The results obtained depict the effectiveness of the proposed hybrid GA-PSO algorithm in comparison with those of GA and PSO methods when applied independently.

Flowchart of Proposed Method Hybrid GA-PSO

Design Specifications

  • IEEE Bus System-33
  • No of DG-3
  • Methods-PSO, GA and Hybrid GA+PSO
Result Evaluation
  • Convergence period for (graph)
  • Voltage vs Bus Number (graph)
  • Total Power loss with DG and without DG(values)
  • Voltages vs buses with DG and Without DG (graph)
  • Optimal size and location (values)
  • Design evaluation of three methods
Reference Paper:  Optimal sizing and sitting of distributed generation using Particle Swarm Optimization Guided Genetic Algorithm
Author’s Name: V. Jagan Mohan and T. Arul Dass Albert
Source:  Advances in Computational Sciences and Technology(Research India Publications)
Year:2017

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SIMULATION VIDEO DEMO                                                                                                                                     


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