Optimal Positioning and Sizing of Distributed Energy Sources in Distribution System Using Hunter-Prey Optimizer Algorithm
The integration of distributed generation (DG) based on renewable energy (RE), in distribution power networks (DPN) has become indispensable for reducing power losses and voltage deviation along the DPN. Typical DGs are placed adjacent to the load in DPN and locally distribute adequate active and re...
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Veröffentlicht in: | Advances in distributed computing and artificial intelligence journal 2024-12, Vol.13, p.e31639-e31639 |
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Sprache: | eng |
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Zusammenfassung: | The integration of distributed generation (DG) based on renewable energy (RE), in distribution power networks (DPN) has become indispensable for reducing power losses and voltage deviation along the DPN. Typical DGs are placed adjacent to the load in DPN and locally distribute adequate active and reactive power. However, the appropriate placement of DG in DPN at the right location and size is essential to achieve the desired objectives. In this paper, DG is optimized into radial DPN with the aid of a recent bio-inspired hunter-prey optimization (HPO) algorithm. HPO is a bio-inspired and population-based optimization algorithm that mimics the hunting action of an animal. The HPO algorithm evades the local optimal stagnation and reaches the optimal solution rapidly. HPO optimizes solar photovoltaic (PV) and wind turbine (WT) DG systems to minimize multi-objective functions (MOFs) including active power loss (APL) and voltage deviation (VD), and to enhance voltage stability (VS). An optimized solution has been obtained for a standard IEEE 69-bus radial DPN and the optimized simulation result of HPO has been compared with other optimization algorithms with the aim of assessing its effectiveness. The optimized PV and WT DG integration via the proposed HPO algorithm has yielded a power loss reduction of 67.10 % and 90.4 %, respectively. Furthermore, a considerable enhancement in bus voltage and voltage stability has been seen in radial DPN after the inclusion of DG. |
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ISSN: | 2255-2863 2255-2863 |
DOI: | 10.14201/adcaij.31639 |