Optimal sizing and siting of distributed generation systems incorporating reactive power tariffs via water flow optimization

·Consideration of reactive power tariffs in optimizing the sizing and siting of distributed generation systems (DGs) for improvement of efficiency.·Applying water flow optimization (WFO) method on the problem of optimal sizing and siting of DGs for the first time.·Taking into account power factor li...

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Veröffentlicht in:Electric power systems research 2024-06, Vol.231, p.110278, Article 110278
Hauptverfasser: Ghazagh Jahed, Younes, Mousazadeh Mousavi, Seyyed Yousef, Golestan, Saeed
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Sprache:eng
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Zusammenfassung:·Consideration of reactive power tariffs in optimizing the sizing and siting of distributed generation systems (DGs) for improvement of efficiency.·Applying water flow optimization (WFO) method on the problem of optimal sizing and siting of DGs for the first time.·Taking into account power factor limitations for DGs capable of injecting both active and reactive power.·Examination of multi-objective functions, including DG allocation to minimize economic losses and annual active/reactive power loss. Distributed generation (DG) systems are gaining popularity because they generate electricity closer to the point of consumption. This reduces transmission and distribution losses and enhances system reliability. For the efficient and cost-effective use of these systems, optimal sizing and siting of DGs is crucial. This paper introduces a Water Flow Optimization (WFO)-based method for the optimal placement and sizing of DG systems capable of injecting both active and reactive power simultaneously. This study assesses both the technical and economic facets of the system, taking into account power losses and the comprehensive annual economic costs, including capital investment, deployment, operation, and maintenance. A significant aspect of this research is the DG units' capability to enhance voltage and minimize losses, factoring in the reactive power tariff. The findings show that the WFO method surpasses other optimization techniques, such as particle swarm optimization, whale optimization algorithm, genetic algorithm and gray wolf optimization. Furthermore, the study emphasizes the cost advantages of injecting reactive power. The minimum annual economic losses (AEL) recorded in this study are $19,207 and $13,852 for IEEE-33 and IEEE-69 bus systems, respectively. In comparison, for DGs only injecting active power, the AEL increases to $24,749 and $41,381 for the corresponding systems.
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2024.110278