TY - JOUR
T1 - Low voltage distribution networks modeling and unbalanced (optimal) power flow
T2 - a comprehensive review
AU - Ibrahim, Ibrahim Anwar
AU - Hossain, M. J.
N1 - Copyright the Author(s). Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2021
Y1 - 2021
N2 - The rapid increase of distributed energy resources (DERs) installation at residential and commercial levels can pose significant technical issues on the voltage levels and capacity of the network assets in distribution networks. Most of these issues occur in low-voltage distribution networks (LVDNs) or near customer premises. A lack of understanding of the networks and advanced planning approaches by distribution network providers (DNSPs) has led to rough estimations for maximum DERs penetration levels that LVDNs can accommodate. These issues might under- or over-estimate the actual hosting capacity of the LVDNs. Limited available data on LVDNs' capacity to host DERs makes planning, installing, and connecting new DERs problematic and complex. In addition, the lack of transparency in LVDN data and information leads to model simplifications, such as ignoring the phase imbalance. This can lead to grossly inaccurate results. The main aim of this paper is to enable the understanding of the true extent of local voltage excursions to allow more targeted investment, improve the network's reliability, enhance solar performance distribution, and increase photovoltaic (PV) penetration levels in LVDNs. Therefore, this paper reviews the state-of-the-art best practices in modeling unbalanced LVDNs as accurately as possible to avoid under- or over-estimation of the network's hosting capacity. In addition, several PV system modeling variations are reviewed, showing their limitations and merits as a trade-off between accuracy, computational burden, and data availability. Moreover, the unbalanced power flow representations, solving algorithms, and available tools are explained extensively by providing a comparative study between these tools and the ones most commonly used in Australia. This paper also presents an overview of unbalanced optimal power flow representations with their related objectives, solving algorithms, and tools.
AB - The rapid increase of distributed energy resources (DERs) installation at residential and commercial levels can pose significant technical issues on the voltage levels and capacity of the network assets in distribution networks. Most of these issues occur in low-voltage distribution networks (LVDNs) or near customer premises. A lack of understanding of the networks and advanced planning approaches by distribution network providers (DNSPs) has led to rough estimations for maximum DERs penetration levels that LVDNs can accommodate. These issues might under- or over-estimate the actual hosting capacity of the LVDNs. Limited available data on LVDNs' capacity to host DERs makes planning, installing, and connecting new DERs problematic and complex. In addition, the lack of transparency in LVDN data and information leads to model simplifications, such as ignoring the phase imbalance. This can lead to grossly inaccurate results. The main aim of this paper is to enable the understanding of the true extent of local voltage excursions to allow more targeted investment, improve the network's reliability, enhance solar performance distribution, and increase photovoltaic (PV) penetration levels in LVDNs. Therefore, this paper reviews the state-of-the-art best practices in modeling unbalanced LVDNs as accurately as possible to avoid under- or over-estimation of the network's hosting capacity. In addition, several PV system modeling variations are reviewed, showing their limitations and merits as a trade-off between accuracy, computational burden, and data availability. Moreover, the unbalanced power flow representations, solving algorithms, and available tools are explained extensively by providing a comparative study between these tools and the ones most commonly used in Australia. This paper also presents an overview of unbalanced optimal power flow representations with their related objectives, solving algorithms, and tools.
UR - http://www.scopus.com/inward/record.url?scp=85117804774&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2021.3120803
DO - 10.1109/ACCESS.2021.3120803
M3 - Review article
SN - 2169-3536
VL - 9
SP - 143026
EP - 143084
JO - IEEE Access
JF - IEEE Access
ER -