Maximizing Hosting Capacity of Single-Phase Rooftop PVs in Unbalanced Distribution Systems

Increased installation of single-phase rooftop photovoltaic (PV) systems (SPPVs) and unbalanced loads in low-voltage distribution networks (LVDNs) may cause deterioration in the overall network performance. Major impacts include voltage unbalance, power losses, thermal overloading of lines, and other power quality issues. Therefore, it is crucial for robust integration coordination of SPPVs with proper sizing and placement to sustain the acceptable limits of power quality indices especially in unbalanced three-phase systems. This paper proposes an optimal capacity allocation of SPPVs method, which not only aids in minimizing the voltage unbalance, power losses, and lines’ overloads but also increases the hosting capacity (HC) of LVDNs. HC boosting enables to accommodating of an excessive capacity of SPPVs besides reducing the exchanged power through the utility grid. This work is demonstrated using an IEEE 123-bus unbalanced distribution system and simulated using daily curves of PV generations and load demands by co-simulation between MATLAB and OpenDSS platforms. Initially, the studied LVDN is divided into five operational zones, each zone has aggregated bulk generation of SPPVs switched only on single-phase. Then, the multi-objective grey wolf optimization (MOGWO) algorithm is operated to select the appropriate capacity, connected phase, and location of SPPVs at each operational zone. As a result, the voltage unbalance, power losses, and imported grid power, declined by 10%, 32% (31 kW at 100% overloading), and 26%, respectively. Further, the HC of LVDNs is increased by 185%, which highlights that the integration of SPPVs can improve power quality using accurate capacity allocation for bulk generation.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/isgteurope62998.2024.10863687
Citations
3
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
0.63

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Maximizing Hosting Capacity of Single-Phase Rooftop PVs in Unbalanced Distribution Systems

Matti Lehtonen, Karar Mahmoud, Hossam H. H. Mousa
3 citations
Islanding Detection in Power Systems
0.63
article

Maximizing Hosting Capacity of Single-Phase Rooftop PVs in Unbalanced Distribution Systems

Matti Lehtonen, Karar Mahmoud, Hossam H. H. Mousa
article en
3 citations

Abstract

Increased installation of single-phase rooftop photovoltaic (PV) systems (SPPVs) and unbalanced loads in low-voltage distribution networks (LVDNs) may cause deterioration in the overall network performance. Major impacts include voltage unbalance, power losses, thermal overloading of lines, and other power quality issues. Therefore, it is crucial for robust integration coordination of SPPVs with proper sizing and placement to sustain the acceptable limits of power quality indices especially in unbalanced three-phase systems. This paper proposes an optimal capacity allocation of SPPVs method, which not only aids in minimizing the voltage unbalance, power losses, and lines’ overloads but also increases the hosting capacity (HC) of LVDNs. HC boosting enables to accommodating of an excessive capacity of SPPVs besides reducing the exchanged power through the utility grid. This work is demonstrated using an IEEE 123-bus unbalanced distribution system and simulated using daily curves of PV generations and load demands by co-simulation between MATLAB and OpenDSS platforms. Initially, the studied LVDN is divided into five operational zones, each zone has aggregated bulk generation of SPPVs switched only on single-phase. Then, the multi-objective grey wolf optimization (MOGWO) algorithm is operated to select the appropriate capacity, connected phase, and location of SPPVs at each operational zone. As a result, the voltage unbalance, power losses, and imported grid power, declined by 10%, 32% (31 kW at 100% overloading), and 26%, respectively. Further, the HC of LVDNs is increased by 185%, which highlights that the integration of SPPVs can improve power quality using accurate capacity allocation for bulk generation.

Aswan University (EG), Aalto University (FI)
Ministry of Higher Education
Openalex Percentile: Top 30%
Islanding Detection in Power Systems
0.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.