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A city-level assessment of residential PV hosting capacity for low-voltage distribution systems considering rooftop data and uncertainties
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Civil Engineering and Built Environment.ORCID iD: 0000-0003-0226-1282
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Civil Engineering and Built Environment.ORCID iD: 0000-0001-8343-3327
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Civil Engineering and Built Environment.ORCID iD: 0000-0003-3757-6815
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Civil Engineering and Built Environment.ORCID iD: 0000-0003-0051-4098
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2024 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 371Article in journal (Refereed) Published
Abstract [en]

The increasing trend of small-scale residential photovoltaic (PV) system installation in low-voltage (LV) distribution networks poses challenges for power grids. To quantify these impacts, hosting capacity has become a popular framework for analysis. However, previous studies have mostly focused on small-scale or test feeders and overlooked uncertainties related to rooftop azimuth and tilt. This paper presents a comprehensive evaluation of city-level PV hosting capacity using data from over 300 real LV systems in Varberg, Sweden. A previously developed rooftop azimuth and tilt model is also applied and evaluated. The findings indicate that the distribution systems of the city, with a definition of PV penetration as the percentage of houses with 12 kW installed PV systems, can accommodate up to 90\% PV penetration with less than 1\% risk of overvoltage, and line loading is not a limiting factor. The roof facet orientation modeling proves to be suitable for city-level applications due to its simplicity and effectiveness. Sensitivity studies reveal that PV size assumptions significantly influence hosting capacity analysis. The study provides valuable insights for planning strategies to increase PV penetration in residential buildings and offers technical input for regulators and grid operators to facilitate and manage residential PV systems.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 371
Keywords [en]
PV hosting capacity, Low voltage system, Rooftop solar photovoltaic, Uncertainty modeling
National Category
Energy Systems Energy Engineering
Research subject
Engineering Science with specialization in Civil Engineering and Built Environment
Identifiers
URN: urn:nbn:se:uu:diva-509203DOI: 10.1016/j.apenergy.2024.123715ISI: 001260532400001OAI: oai:DiVA.org:uu-509203DiVA, id: diva2:1788724
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage, FPS8SOLVEAvailable from: 2023-08-16 Created: 2023-08-16 Last updated: 2024-07-12Bibliographically approved
In thesis
1. Uncertainty modeling for load flow and hosting capacity analysis of urban electricity distribution systems
Open this publication in new window or tab >>Uncertainty modeling for load flow and hosting capacity analysis of urban electricity distribution systems
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Urban demographics are changing, with more than half of the global population currently residing in urban areas. Traditionally, cities are often seen as passive energy consumers relying on external centralized systems. Motivated by the need to mitigate climate change, a shift is underway as cities actively shape energy systems. This shift involves decentralized power generation, electric vehicle (EV)-related electricity usage shifts, enhanced building energy efficiency, and increasing interaction between local power generation and load. This poses some challenges to distribution grid operation such as voltage violation, decreased power quality, equipment damage, power losses, and reliability issues. Addressing these issues requires load flow analysis, and to quantify the impacts based on load flow analysis, the hosting capacity concept has been introduced. Although traditional load flow analysis lacks uncertainty consideration, the growth of distributed photovoltaics (PV) generation and EVs demands enhanced accuracy through uncertainty modeling.

This thesis contributes to the knowledge of how uncertainty and correlation models can improve the quality of load flow and hosting capacity analysis for urban electricity distribution systems with high penetration of residential PV systems and EVs through the combination of methodological and case studies. Methodological studies propose uncertainty models for input variables and investigate their impact on load flow and hosting capacity assessment. Case studies demonstrate enhanced hosting capacity analysis quality through applied uncertainty models.

Results show that concentrated allocation of PV systems and EVs had more severe impacts, in particular at lower penetration levels, and smart charging in concentrated allocation had more significant benefits to reduce peak load and voltage drop. Results regarding residential building roofs show that the inclusion of more residential buildings when the PV penetration increases will require including a lot of less-optimal facets, and, hence, a novel method has been proposed to proportionally include less optimal roofs at every penetration level. The smart charging scheme, which has as its main objective to reduce the net-load variability, improves the electricity distribution system performance, and combined with PV curtailment, can further increase the hosting capacity. An increase in correlations between nodes is also observed due to this smart charging scheme. The city-level simulations show that the distribution system of the city can accommodate a 90% penetration level of PV with less than 1% risk of overvoltage and line loading does not limit the hosting capacity. The method used to model roof facet orientation proves effective for city level applications, given its simplicity and effectiveness.

In summary, this thesis concludes that the quality and knowledge of load flow and hosting capacity analysis for urban electricity distribution systems can be improved by several methods, including: the probabilistic model of PV power generation and EV charging profiles, the inclusion of EMS, the consideration of spatial allocation methods of PV and EV, the assessment of the correlation between PV and EV, and the consideration of rooftop tilt and azimuth uncertainties.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2023. p. 90
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 2296
Keywords
Uncertainty model, Photovoltaics, Electric vehicle, Residential buildings, Hosting capacity, Probabilistic load flow, Electricity distribution systems, Urban Energy Systems
National Category
Energy Systems Energy Engineering
Research subject
Engineering Science with specialization in Civil Engineering and Built Environment
Identifiers
urn:nbn:se:uu:diva-509205 (URN)978-91-513-1876-9 (ISBN)
Public defence
2023-10-06, Heinz-Otto Kreiss, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 13:15 (English)
Opponent
Supervisors
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage, FPS8
Available from: 2023-09-13 Created: 2023-08-16 Last updated: 2023-09-13

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Ramadhani, Umar HanifJohari, FatemehLindberg, OskarMunkhammar, JoakimWidén, Joakim

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