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Multi-objective Optimization Approach for Allocation and Sizing of Distributed Energy Resources Preserving the Protection Scheme in Distribution Networks

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Abstract

In this paper, a multi-objective optimization approach to solve the problem of optimal allocation and sizing of inverter-based distributed energy resources (DERs) in distribution systems is presented. The objectives of this allocation and sizing problem consist of the minimization of the investment and operation costs, the voltage deviation and the short-circuit currents. The recloser–fuse coordination constraints were included in the mathematical formulation of the problem, in order to preserve the original network protection scheme. It is important to mention that this protection scheme was also carried out in this paper, using the multi-objective approach, to minimize the operating time of the reclosers and fuses. The distribution system considered to evaluate the proposed methodology was the IEEE 34-Node Test Feeder, and the non-dominated sorting genetic algorithm II was used to solve the proposed multi-objective problems. Furthermore, a time-series-based probabilistic approach, through the Monte Carlo simulation, was adopted to deal with the uncertainties of the load and power generated by each DER. Finally, from the results, it was possible to reduce the investment and operation costs by 15.61% when compared to the system without DERs, improve the voltage profile and preserve the original protection scheme present in the network.

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Acknowledgements

This study was financed by the Fundação de Amparo à Pesquisa e Inovação do Espírito Santo— Brazil (FAPES)—Number 026/2021.

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Correspondence to Renato S. F. Ferraz.

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Ferraz, R.S.F., Ferraz, R.S.F. & Rueda–Medina, A.C. Multi-objective Optimization Approach for Allocation and Sizing of Distributed Energy Resources Preserving the Protection Scheme in Distribution Networks. J Control Autom Electr Syst 34, 1080–1092 (2023). https://doi.org/10.1007/s40313-023-01030-4

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  • DOI: https://doi.org/10.1007/s40313-023-01030-4

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