Increasing PV hosting capacity with phase rebalancing in LV networks: A network-agnostic rule-based approach

Most residential photovoltaic (PV) systems are single-phase installations and, therefore, can increase unbalance. More unbalance exacerbates voltage rise issues on certain phases, potentially limiting the PV hosting capacity of low voltage (LV) networks. Rebalancing customers by adequately switching their phase connection can reduce unbalance and improve voltage headroom, allowing for more PV systems. However, this needs to be done quickly to cater for the normal variations in net demand. Furthermore, since most distribution companies do not have accurate, detailed three-phase LV network models, a solution independent of such models is desirable so it can be implemented. This paper proposes a fast, network-agnostic rule-based rebalancing approach that only requires knowledge of the phase groups, i.e., no network models are needed. Its feasibility is mathematically proven, and its effectiveness is benchmarked against a model-driven AC Optimal Power Flow (OPF)-based approach formulated as MINLP. Using a realistic Australian LV feeder with 29 single-phase customers, results show that the proposed approach mitigates unbalance as effectively as the OPF-based approach, in sub-seconds and without network models. Crucially, this paper demonstrates how a practical and scalable approach to reduce unbalance in two Australian LV networks—with different number of LV feeders and customers—can significantly increase the PV hosting capacity without resorting to PV curtailment.

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Publication Details

Journal
Sustainable Energy Grids and Networks
Published
2024-12-27
DOI
https://doi.org/10.1016/j.segan.2024.101615
Citations
3
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.63
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article

Increasing PV hosting capacity with phase rebalancing in LV networks: A network-agnostic rule-based approach

Luis F. Ochoa, Yushan Hou, Michael Z. Liu, Arthur Gonçalves Givisiez
3 citations
Sustainable Energy Grids and Networks
Optimal Power Flow Distribution
0.63
article

Increasing PV hosting capacity with phase rebalancing in LV networks: A network-agnostic rule-based approach

Luis F. Ochoa, Yushan Hou, Michael Z. Liu, Arthur Gonçalves Givisiez
article en
3 citations

Abstract

Most residential photovoltaic (PV) systems are single-phase installations and, therefore, can increase unbalance. More unbalance exacerbates voltage rise issues on certain phases, potentially limiting the PV hosting capacity of low voltage (LV) networks. Rebalancing customers by adequately switching their phase connection can reduce unbalance and improve voltage headroom, allowing for more PV systems. However, this needs to be done quickly to cater for the normal variations in net demand. Furthermore, since most distribution companies do not have accurate, detailed three-phase LV network models, a solution independent of such models is desirable so it can be implemented. This paper proposes a fast, network-agnostic rule-based rebalancing approach that only requires knowledge of the phase groups, i.e., no network models are needed. Its feasibility is mathematically proven, and its effectiveness is benchmarked against a model-driven AC Optimal Power Flow (OPF)-based approach formulated as MINLP. Using a realistic Australian LV feeder with 29 single-phase customers, results show that the proposed approach mitigates unbalance as effectively as the OPF-based approach, in sub-seconds and without network models. Crucially, this paper demonstrates how a practical and scalable approach to reduce unbalance in two Australian LV networks—with different number of LV feeders and customers—can significantly increase the PV hosting capacity without resorting to PV curtailment.

Sustainable Energy Grids and NetworksVol. 41
Volvo (Sweden) (SE), The University of Melbourne (AU)
Openalex Percentile: Top 30%
Optimal Power Flow Distribution
0.63
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Increasing PV hosting capacity with phase rebalancing in LV networks: A network-agnostic rule-based approach — Luis F. Ochoa, Yushan Hou, et al. · Sustainable Energy Grids and Networks (2024) | TGRS Research Map | TGRS