A Full AC Time‐Series Analysis of Photovoltaic Hosting Capacity in Niger's Grid

ABSTRACT The integration of solar photovoltaic (PV) systems into sub‐Saharan African distribution grids presents a transformative opportunity to enhance energy access and sustainability. However, accurately quantifying the hosting capacity (HC), the maximum PV power that can be accommodated without violating operational limits, remains a major challenge under variable generation and demand. This paper presents a full alternating current (AC) time‐series analysis of PV HC in Niger's River‐Zone (RZ) distribution grid using hourly resolution over a full year. The methodology applies α ‐scanning to determine the maximum admissible PV scaling factor ( α max), constrained by voltage and thermal limits. Detailed grid modeling in Pandapower is coupled with dynamic voltage regulation through multi‐step capacitor bank control to capture the benefits of reactive power support. Results showed that HC was a highly time‐dependent metric, with significant intra‐ and inter‐day variability shaped by PV availability, load patterns, and grid conditions. The voltage remained within regulatory bounds (0.9–1.05 p.u), and all thermal constraints were met, thus validating the control strategy. Daily HC values frequently approached or surpassed the available PV generation potential, suggesting that the network retained additional margin for further PV integration under existing operating conditions. The calculated penetration ratio reached up to 50% with minimal intraday variability, indicating consistent alignment between PV output and load demand throughout daylight hours. This dynamic framework offers critical insights for planning high‐renewable penetration in weak grids. It supports informed investment decisions and provides a replicable, data‐driven approach for PV integration across emerging economies.

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Publication Details

Journal
Energy Science & Engineering
Published
2026-02-09
DOI
https://doi.org/10.1002/ese3.70456
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.00

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article

A Full AC Time‐Series Analysis of Photovoltaic Hosting Capacity in Niger's Grid

Yacouba Moumouni, Hamza Abarchi Halarou, Bonkaney Abdou Latif, Amadou Oumarou Fati et al.
Energy Science & Engineering
Optimal Power Flow Distribution
article

A Full AC Time‐Series Analysis of Photovoltaic Hosting Capacity in Niger's Grid

Yacouba Moumouni, Hamza Abarchi Halarou, Bonkaney Abdou Latif, Amadou Oumarou Fati, Madougou Saidou, Abdoulaye Moussa Falmata
article en

Abstract

ABSTRACT The integration of solar photovoltaic (PV) systems into sub‐Saharan African distribution grids presents a transformative opportunity to enhance energy access and sustainability. However, accurately quantifying the hosting capacity (HC), the maximum PV power that can be accommodated without violating operational limits, remains a major challenge under variable generation and demand. This paper presents a full alternating current (AC) time‐series analysis of PV HC in Niger's River‐Zone (RZ) distribution grid using hourly resolution over a full year. The methodology applies α ‐scanning to determine the maximum admissible PV scaling factor ( α max), constrained by voltage and thermal limits. Detailed grid modeling in Pandapower is coupled with dynamic voltage regulation through multi‐step capacitor bank control to capture the benefits of reactive power support. Results showed that HC was a highly time‐dependent metric, with significant intra‐ and inter‐day variability shaped by PV availability, load patterns, and grid conditions. The voltage remained within regulatory bounds (0.9–1.05 p.u), and all thermal constraints were met, thus validating the control strategy. Daily HC values frequently approached or surpassed the available PV generation potential, suggesting that the network retained additional margin for further PV integration under existing operating conditions. The calculated penetration ratio reached up to 50% with minimal intraday variability, indicating consistent alignment between PV output and load demand throughout daylight hours. This dynamic framework offers critical insights for planning high‐renewable penetration in weak grids. It supports informed investment decisions and provides a replicable, data‐driven approach for PV integration across emerging economies.

Energy Science & Engineering
Higher Colleges of Technology (AE), Université Abdou Moumouni (NE), West African Science Service Centre on Climate Change and Adapted Land Use (GH), American University of Ras Al Khaimah (AE)
Bundesministerium für Bildung und Forschung, West African Science Service Centre on Climate Change and Adapted Land Use
Openalex Percentile: Top 62%
Optimal Power Flow Distribution
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