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<p>This study compares the optimal location and size of distributed generations (DGs) by applying a hybrid approach of genetic algorithm and tabu search optimization in distribution networks (DNs) with static load models, constant impedance, current and power load models, and realistic load models. This study shows that the proposed algorithm significantly improves the performance of DNs such as real and reactive power loss, voltage profile, network capacity, and voltage regulation. This study also compares the order of performance variation of different load models (LMs) with DGs planning. The proposed algorithm has been demonstrated for 37-bus DNs. This article would be very useful for researchers, scientists, and industrial persons who are performing on the area of DGs planning with different LMs.</p>

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A comparative study of distributed generation planning in distribution networks with different load models using hybrid approach of GA-TS optimization

  • 期刊论文

  • 发表日期：

    2025年8月25日

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  • Deependra Kumar Mishra,
  • V. Mukharjee,
  • Bindeshwar Singh

摘要

This study compares the optimal location and size of distributed generations (DGs) by applying a hybrid approach of genetic algorithm and tabu search optimization in distribution networks (DNs) with static load models, constant impedance, current and power load models, and realistic load models. This study shows that the proposed algorithm significantly improves the performance of DNs such as real and reactive power loss, voltage profile, network capacity, and voltage regulation. This study also compares the order of performance variation of different load models (LMs) with DGs planning. The proposed algorithm has been demonstrated for 37-bus DNs. This article would be very useful for researchers, scientists, and industrial persons who are performing on the area of DGs planning with different LMs.