Monte Carlo-based assessment of PV impacts on real UK low voltage networks
Open accessAbstract
The penetration of residential photovoltaic (PV) panels is increasing particularly in those countries with special incentives. The total PV installed capacity in the UK has increased from negligible to 1.2 GW since the Feed-In Tariff scheme was created in 2010. As a result, Distribution Network Operators (DNOs) are already experiencing voltage issues in low voltage (LV) feeders were clusters have appeared. This work proposes a Monte Carlo-based technique to assess the impacts of different PV penetrations on LV networks in order to estimate their corresponding hosting capabilities. Three-phase models of two real LV networks in the North West of England are studied considering 5-min resolution synthetic data for domestic load and PV generation. Voltage-related impacts are measured using the European Standard EN50160. Additionally, the importance of data granularity on the impact assessment is analyzed. Results for the studied LV networks indicate that feeders with greater lengths and larger number of customers tend to experience voltage issues with lower PV penetration levels. In terms of the granularity, it was found that hourly resolution analyses underestimate the voltage impacts of residential PV.
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In all examined studies, the permissible violation probability was 5% or more.
“In the criteria of all examined studies, the permissible violation probability was 5% or more [41,42,60,61].”
From Stochastic Approach for Increasing the PV Hosting Capacity of a Low-Voltage Distribution Network (2022) · cites this paper as [61]
The Impact Assessment section states that EN50160 requires voltage to remain within 0.9–1.1 p.u. for at least 95% of weekly measurements, allowing up to 5% outside that range. That is a tolerance for measurements over time, not an explicit permissible probability of violations across Monte Carlo simulations; the section also specifies limits that must never be exceeded. This paper cannot establish the criterion used by the other cited studies. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe probability limitations chosen for analysis are significantly more conservative than the commonly used limit.
“The probability limitations chosen for analysis are significantly more conservative than the commonly used limit.”
From Stochastic Approach for Increasing the PV Hosting Capacity of a Low-Voltage Distribution Network (2022) · cites this paper as [61]
Section C (Impact Assessment; page not provided) describes the EN50160 voltage criterion, including its 95% requirement, and Section IV reports probabilities of voltage problems. Neither section says that the probability limits chosen for the analysis are more conservative than a commonly used limit. Searches for conservative probability thresholds and a comparison with the 95% criterion found no such statement in our copy. (LLM, conf=0.73)
Experimental — accuracy not yet measured
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Tonev, I., & Nikolaev, N. (2025) · Conference on Electrical Machines, Drives and Power Systems (ELMA) · doi:10.1109/elma65795.2025.11083459
- Authors
- Navarro, A., Ochoa, L. F., & Randles, D.
- Affiliations
- University of Manchester (GB)
- Electricity North West (United Kingdom) (GB)
- ORCID
- Ochoa, Luis F.
- Venue
- 2013 IEEE Power & Energy Society General Meeting
- Publisher
- IEEE
- Published
- 2013
- ISSN
- 1932-5517 (ISSN-L)
- OpenAlex
- W2143532846
- Cited by
- 93
- References
- 11
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 3 · 2022: 4 · 2021: 6 · 2020: 9 · 2019: 9 · 2018: 10 · 2017: 8 · 2016: 11 · 2015: 19 · 2014: 9 · 2013: 1
- FWCI
- 16.23
- Type
- conference paper
- Language
- en
- Open access
- Locations
- IEEE Power Engineering Society General Meeting (publishedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Funders
- Loughborough University
- Core Research for Evolutional Science and Technology
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power Quality and Harmonics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- low-voltage distribution networks, hosting capacity, voltage quality, Monte Carlo simulation, data resolution, feed-in tariffs, North West England
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