GENETIC ALGORITHM-BASED OPTIMIZATION OF DISTRIBUTED GENERATOR PLACEMENT IN DISTRIBUTION NETWORKS TO MINIMIZE POWER LOSSES

Authors

  • Nurul An-nizha State Polytechnic of Ujung Pandang
  • Sofyan State Polytechnic of Ujung Pandang
  • Ahmad Rizal Sultan State Polytechnic of Ujung Pandang
  • Muh. Imran Bachtiar State Polytechnic of Ujung Pandang
  • Umar Muhammad State Polytechnic of Ujung Pandang
  • Sitti Arni State Polytechnic of Ujung Pandang

Keywords:

Distributed Generation, Optimization, Genetic Algorithms, Newton Raphson Method, Power Losses

Abstract

An increase in electrical energy can lead to an increase in power losses and a decrease in voltage in the system. One of the efforts made to reduce power losses that occur in the distribution network is by placing the optimal Distributed Generation (DG) in the right location. Installation of DGs with suboptimal capacity and placement location can result in greater active power losses and further reduce voltage stability. This study discusses the optimization of DG placement in the electric power distribution network using genetic algorithm methods that are known to be effective in solving complex optimization problems. The IEEE 33 bus distribution system, which is a standard system frequently employed in power flow research, was the subject of the case study. The Newton-Raphson method is a commonly used iterative method for power flow analysis due to its accuracy in calculating power flow in electrical networks. The research findings indicate that the most suitable location for two DG units with an injection power of 6,626 MW is on buses 3 and 4. The placement of this DG has the potential to substantially mitigate power losses within the distribution network. The placement of two DG units on buses 3 and 4 results in a more significant improvement in system power losses than the placement of DG units on other buses. Power losses of buses 3 and 4 experienced power losses of 67724.69 MW, while system losses were reduced by 1137621.21 MW, or 5.61 percent.

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Published

2024-11-21

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