A Residential Hybrid Nanogrid Based on Solid State Transformer Technology

This paper presents a residential hybrid nanogrid architecture featuring a solid-state transformer and a multiport design, facilitating the integration of PV, battery energy storage system, and DC and AC loads. The proposed nanogrid utilizes a hierarchical control system, which includes an energy management system for optimizing resource allocation and a local control system for managing individual converter operations. Through comprehensive simulations, the functionality of the NG is validated under various operational scenarios. The results demonstrate the system's ability to maintain tight voltage regulation, balance power efficiently, facilitate power exchanges with the grid, and operate independently in an islanded mode.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/isie62713.2025.11124809
Citations
1
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.91

Funders

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article

A Residential Hybrid Nanogrid Based on Solid State Transformer Technology

Nasrin Einabadi, Mehrdad Kazerani
1 citations
Neuroscience and Neural Engineering
0.91
article

A Residential Hybrid Nanogrid Based on Solid State Transformer Technology

Nasrin Einabadi, Mehrdad Kazerani
article en
1 citations

Abstract

This paper presents a residential hybrid nanogrid architecture featuring a solid-state transformer and a multiport design, facilitating the integration of PV, battery energy storage system, and DC and AC loads. The proposed nanogrid utilizes a hierarchical control system, which includes an energy management system for optimizing resource allocation and a local control system for managing individual converter operations. Through comprehensive simulations, the functionality of the NG is validated under various operational scenarios. The results demonstrate the system's ability to maintain tight voltage regulation, balance power efficiently, facilitate power exchanges with the grid, and operate independently in an islanded mode.

University of Waterloo (CA)
Natural Sciences and Engineering Research Council of Canada
Affordable and clean energy
Openalex Percentile: Top 23%
Neuroscience and Neural Engineering
0.91
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