Grid Line Impedance Sensitivity for Grid Characterization and Stability Assessment: From Analytics to Time Domain Illustration Article Swipe
Salma Bennai
,
Afef Bennani-Ben Abdelghani
,
Ilhem Slama‐Belkhodja
,
Mahrane Khalfoun
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s40866-024-00196-3
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s40866-024-00196-3
With the rising wave of decarbonization in the power and energy sector, a pressing surge in adopting renewable energy sources has been considered as a critical response to the imperative need for a transition toward cleaner and more sustainable alternatives. This research paper evaluates the impacts of decarbonization initiatives, with a specific focus on the integration of photovoltaic systems within the distribution network. The study introduces a sensitivity analysis methodology to address the challenges arising from power quality and grid stability. More specifically, this work conducts an analysis of power quality and assesses the stability of low voltage networks, considering the geographical location of customers along distribution lines. Built upon an analytical framework and a time domain illustration, the research showcases the sensitivity analysis of voltage level, short circuit ratio, and hosting capacity toward grid line impedance parameters. The contribution of this paper lies in its findings that provide practical insights and actionable recommendations for distribution system operators. These recommendations are based on the computed sensitivity coefficients and overall profiles and aim to assist in effectively managing power quality and system stability within the context of integrating renewable energy sources.
Related Topics
Concepts
Renewable energy
Context (archaeology)
Grid
Sensitivity (control systems)
Reliability engineering
Computer science
Electric power system
Systems engineering
Power (physics)
Environmental economics
Engineering
Electrical engineering
Electronic engineering
Economics
Geometry
Quantum mechanics
Physics
Mathematics
Paleontology
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s40866-024-00196-3
- https://link.springer.com/content/pdf/10.1007/s40866-024-00196-3.pdf
- OA Status
- hybrid
- Cited By
- 2
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391879968
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391879968Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s40866-024-00196-3Digital Object Identifier
- Title
-
Grid Line Impedance Sensitivity for Grid Characterization and Stability Assessment: From Analytics to Time Domain IllustrationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-16Full publication date if available
- Authors
-
Salma Bennai, Afef Bennani-Ben Abdelghani, Ilhem Slama‐Belkhodja, Mahrane KhalfounList of authors in order
- Landing page
-
https://doi.org/10.1007/s40866-024-00196-3Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s40866-024-00196-3.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://link.springer.com/content/pdf/10.1007/s40866-024-00196-3.pdfDirect OA link when available
- Concepts
-
Renewable energy, Context (archaeology), Grid, Sensitivity (control systems), Reliability engineering, Computer science, Electric power system, Systems engineering, Power (physics), Environmental economics, Engineering, Electrical engineering, Electronic engineering, Economics, Geometry, Quantum mechanics, Physics, Mathematics, Paleontology, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2Per-year citation counts (last 5 years)
- References (count)
-
22Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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