Probabilistic Methodology for Calculating PV Hosting Capacity in LV Networks Using Actual Building Roof Data
Open accessAbstract
There has been an increasing trend of integrating photovoltaic power plants (PVs). One of the important challenges for distribution system operators is to evaluate the total installed power of a PV that a particular network can host (or PV hosting capacity) while keeping voltage and element constraints within required limits. The major drawback of the existing methods for calculating PV hosting capacity is that they use the same installed power of the PV systems for all simulated PVs, as these methods do not use external data sources about building roofs. As a consequence, this has a significant impact on the final accuracy of the results. This paper presents a probabilistic methodology for calculating the PV hosting capacity in low voltage (LV) networks. The main contribution of this paper is the improved modeling of PV generation using actual building roof data when calculating the PV hosting capacity, as every building is treated according to its actual solar potential. Monte Carlo simulations with incorporated stochastic consumption and PV generation models are utilized for load flow calculations of the actual LV network. The simulation results presented in this paper prove that the proposed methodology increases the accuracy of the final PV hosting capacity calculations.
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The approach in [100] provides improved accuracy compared to other studies that mostly use the same installed power of the solar PV for all simulated PVs.
“The result obtained show that the approach provides improved accuracy compared to other studies that mostly use the same installed power of the solar PV for all simulated PVs.”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [100]
In [100], the authors presented improved modeling of PV using actual roof data of the building for the stochastic HC calculation.
“In [100], the authors presented improved modeling of PV using actual roof data of the building for the stochastic HC calculation.”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [100]
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- Authors
- Grabner, M., Souvent, A., Suljanović, N., Košir, A., & Blažič, B.
- Affiliations
- University of Ljubljana (SI)
- Milan Vidmar Electric Power Research Institute (SI)
- Corresponding author
- Grabner, Miha
- Venue
- Energies
- Publisher
- MDPI AG
- Published
- 2019-10-25
- Volume
- 12
- Issue
- 21
- Pages
- 4086
- ISSN
- 1996-1073 (ISSN-L)
- OpenAlex
- W2981597479
- Cited by
- 21
- References
- 36
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 6 · 2022: 3 · 2021: 1 · 2020: 3
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Energies (publishedVersion, cc-by)
- Repository of the University of Ljubljana (University of Ljubljana) (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Control and Systems Engineering › Thermal Analysis in Power Transmission
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- photovoltaic hosting capacity, low-voltage distribution networks, photovoltaic integration, solar energy potential, stochastic modeling, Monte Carlo simulation, stochastic load modeling, power flow analysis, voltage constraints
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