The DOI matches its Crossref record.
Stochastic evaluation of distribution network hosting capacity: Evaluation of the benefits introduced by smart grid technology
Abstract
The increasing share of renewables is creating new challenges for distribution grids and operators have to adopt more and more advanced tools for the evaluation of network investments, especially for scenarios in which distributed generation is expected to drastically grow. In particular, the maximum connectable power (Hosting Capacity) as well as the benefits that Smart Grid technology can bring to the distribution system have to be analyzed in detail and in multiple scenarios. The paper proposes a probabilistic approach for the calculation of the Hosting Capacity based on the random allocation of generation resources, which models the uncertainty related to their position within the network in the next future. Thanks to this approach, control solutions can be exhaustively evaluated and their performance can be compared in several possible scenarios of distributed generation expansion.
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“This is followed by the load flow simulation of the network and the determination of the HC based on the performance indices whose operational limits are violated [92].”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [92]
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No references could be resolved yet.
Research works printed but not linked: 9
- project, 0, Archivio TeLemAtico per il riferimento Nazionale di reTi di Distribuzione Elettrica
- 10.1049/oap-cired.2017.0316 · DOI
- 10.1049/oap-cired.2017.0178 · DOI
- stafford, 2006, Random Vectors with Fixed Sum, MathWorks Matlab Central
- dahlquist, 1974, Numerical Methods, Dover Books on Mathematics, 231
- 10.1109/AEIT.2015.7415234 · DOI
- 10.1109/ICCEP.2015.7177570 · DOI
- 10.23919/AEIT.2016.7892744 · DOI
- 10.1109/TPWRS.2012.2214406 · DOI · Paper page
Cited by
Sorted by citations
A Review of the Tools and Methods for Distribution Networks’ Hosting Capacity Calculation
Zain ul Abideen, M., Ellabban, O., & Al-Fagih, L. (2020) · Energies · doi:10.3390/en13112758 · Cited by 161
Umoh, V., Davidson, I., Adebiyi, A., & Ekpe, U. (2023) · Energies · doi:10.3390/en16083609 · Cited by 71
Metadata
- Authors
- Rossi, M., Vigano, G., Moneta, D., & Clerici, D.
- Affiliations
- Ricerca sul Sistema Energetico (Italy) (IT)
- Venue
- 2017 AEIT International Annual Conference
- Publisher
- IEEE
- Published
- 2017-09
- OpenAlex
- W2781306216
- Cited by
- 18
- References
- 0
- Citations by year
- 2024: 2 · 2023: 5 · 2022: 1 · 2021: 2 · 2020: 3 · 2019: 4 · 2018: 1
- FWCI
- 3.10
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- AEIT International Annual Conference (publishedVersion)
- 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 › Thermal Analysis in Power Transmission
- Keywords
- hosting capacity, distribution networks, smart grid, distributed generation, probabilistic analysis, renewable energy integration
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