Photovoltaic Hosting Capacity: An Approach Based on Optimal Power Flow

The growing integration of photovoltaic (PV) distributed generation (DG) presents challenges and opportunities for distribution networks, requiring a precise evaluation of the network’s Maximum Hosting Capacity (MHC). This study aims to determine the Maximum Hosting Capacity (MHC) of the EPRI ckt5 distribution system using optimization techniques based on the optimal power flow (OPF) approach, considering technical constraints such as voltage limits. The methodology for simulation was implemented in Python using OpenDSS. Two methods were applied: centralized allocation, which evaluates each bus individually, and distributed allocation, which considers simultaneous PV allocation across multiple buses. The results show an average MHC of 75.40 kW in the centralized approach, while the distributed approach resulted in a lower average of 35.84 kW, reflecting the impact of equitable resource allocation. The study highlights the trade-offs between maximizing technical capacity and promoting fair access to PV generation.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/wcnps65035.2024.10814476
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00

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article

Photovoltaic Hosting Capacity: An Approach Based on Optimal Power Flow

Caio Cesar Amorim Silva, Bruno H. Dias, Walquíria N. Silva
Power Systems and Renewable Energy
article

Photovoltaic Hosting Capacity: An Approach Based on Optimal Power Flow

Caio Cesar Amorim Silva, Bruno H. Dias, Walquíria N. Silva
article en

Abstract

The growing integration of photovoltaic (PV) distributed generation (DG) presents challenges and opportunities for distribution networks, requiring a precise evaluation of the network’s Maximum Hosting Capacity (MHC). This study aims to determine the Maximum Hosting Capacity (MHC) of the EPRI ckt5 distribution system using optimization techniques based on the optimal power flow (OPF) approach, considering technical constraints such as voltage limits. The methodology for simulation was implemented in Python using OpenDSS. Two methods were applied: centralized allocation, which evaluates each bus individually, and distributed allocation, which considers simultaneous PV allocation across multiple buses. The results show an average MHC of 75.40 kW in the centralized approach, while the distributed approach resulted in a lower average of 35.84 kW, reflecting the impact of equitable resource allocation. The study highlights the trade-offs between maximizing technical capacity and promoting fair access to PV generation.

Universidade Federal de Juiz de Fora (BR)
EMI, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Affordable and clean energy
Openalex Percentile: Top 74%
Power Systems and Renewable Energy
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Photovoltaic Hosting Capacity: An Approach Based on Optimal Power Flow — Caio Cesar Amorim Silva, Bruno H. Dias, et al. · (2024) | TGRS Research Map | TGRS