A review of power distribution test feeders in the United States and the need for synthetic representative networks
Open accessAbstract
Under the increasing penetration of distributed energy resources and new smart network technologies, distribution utilities face new challenges and opportunities to ensure reliable operations, manage service quality, and reduce operational and investment costs. Simultaneously, the research community is developing algorithms for advanced controls and distribution automation that can help to address some of these challenges. However, there is a shortage of realistic test systems that are publically available for development, testing, and evaluation of such new algorithms. Concerns around revealing critical infrastructure details and customer privacy have severely limited the number of actual networks published and that are available for testing. In recent decades, several distribution test feeders and US-featured representative networks have been published, but the scale, complexity, and control data vary widely. This paper presents a first-of-a-kind structured literature review of published distribution test networks with a special emphasis on classifying their main characteristics and identifying the types of studies for which they have been used. This both aids researchers in choosing suitable test networks for their needs and highlights the opportunities and directions for further test system development. In particular, we highlight the need for building large-scale synthetic networks to overcome the identified drawbacks of current distribution test feeders.
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IEEE test feeder models are less suitable for EV impact studies because their design and data were published for specific issues.
“These models are less suitable for EV impact studies as the overall design and data available were published for specific issues [14].”
From Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids (2019) · cites this paper as [14]
The paper’s limitations discussion (page unavailable) says some test feeders were designed for a single issue and can be unsuitable for other applications because relevant information is missing. It does not apply that limitation to IEEE test feeders as a group or specifically conclude that they are less suitable for EV impact studies; its example is a feeder for DG protection analysis. (LLM, conf=0.85)
Experimental — accuracy not yet measuredLow-voltage grids have large variations in their design.
“Low-voltage grids have large variations in their design [18].”
From A large-scale high-resolution geographic analysis of impacts of electric vehicle charging on low-voltage grids (2022) · cites this paper as [18]
The size of the network should be considered for reliable results because small-scale networks miss heterogeneity.
“The size of the network should be considered in order to have reliable results because small-scale networks miss heterogeneity [14].”
From Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids (2019) · cites this paper as [14]
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- Authors
- Postigo Marcos, F., Mateo Domingo, C., Gómez San Román, T., Palmintier, B., Hodge, B.-M., Krishnan, V., De Cuadra García, F., & Mather, B.
- Affiliations
- Institute for Research in Technology (IIT), Comillas Pontifical University, Madrid 28015, Spain
- National Laboratory of the Rockies (US)
- ORCID
- Venue
- Energies
- Publisher
- MDPI AG
- Published
- 2017-11-18
- Volume
- 10
- Issue
- 11
- Pages
- 1896
- ISSN
- 1996-1073 (ISSN-L)
- OpenAlex
- W2768772793
- Cited by
- 106
- References
- 53
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 7 · 2023: 14 · 2022: 24 · 2021: 19 · 2020: 18 · 2019: 9 · 2018: 2
- FWCI
- 3.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Energies (publishedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- CU Scholar (University of Colorado Boulder) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Energy (DE-AC36-08GO28308)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power System Optimization and Stability
- Keywords
- distribution networks, test system design, distributed energy resources, distribution automation, control data, network classification, distribution utilities
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