Integrative Optimization Framework for Strategic Distributed Generation Placement and Sizing to Enhance Loss Minimization and Voltage Stability in Power Distribution Networks

The location and scale of distributed generation (DG) units are critical for minimizing losses and enhancing the performance of distribution networks. This research establishes the optimization approach for establishing the optimal location of the dg, especially solar PV and wind turbines using the IEEE 37-bus system as the test feeder. Having this in mind, this work applied a unified approach based on Pandapower, a versatile Python-based power systems tool, combining optimization and power flow computations. The algorithm analyzes a range of DG technologies and penetration levels to determine the effectiveness of decreasing loss, considering variability in renewable generation and load demand to increase realism. The single-tool forms presented in the paper show practical application potential and offer a better understanding of the best approaches to DG integration that would benefit grid stability and energy efficiency in the distribution networks of the future.

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Publication Details

Published
2025-02-13
DOI
https://doi.org/10.1109/ic363308.2025.10956396
Citations
2
Primary Topic
Power Systems and Technologies
Type
article
Field-Weighted Citation Impact
1.46
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Integrative Optimization Framework for Strategic Distributed Generation Placement and Sizing to Enhance Loss Minimization and Voltage Stability in Power Distribution Networks

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article

Integrative Optimization Framework for Strategic Distributed Generation Placement and Sizing to Enhance Loss Minimization and Voltage Stability in Power Distribution Networks

Aravinda Konidena, Jay Singh, Savita Kumari, Sajjad Ziara, K. S. Nandini Prasad, Atul Singla, Gotlur Karuna
article en
2 citations

Abstract

The location and scale of distributed generation (DG) units are critical for minimizing losses and enhancing the performance of distribution networks. This research establishes the optimization approach for establishing the optimal location of the dg, especially solar PV and wind turbines using the IEEE 37-bus system as the test feeder. Having this in mind, this work applied a unified approach based on Pandapower, a versatile Python-based power systems tool, combining optimization and power flow computations. The algorithm analyzes a range of DG technologies and penetration levels to determine the effectiveness of decreasing loss, considering variability in renewable generation and load demand to increase realism. The single-tool forms presented in the paper show practical application potential and offer a better understanding of the best approaches to DG integration that would benefit grid stability and energy efficiency in the distribution networks of the future.

Lovely Professional University (IN), Galgotias University (IN), Iraqi University (IQ)
Affordable and clean energy
Openalex Percentile: Top 18%
Power Systems and Technologies
1.46
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