Learning-based state estimation for low voltage distribution grids using neural networks
In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Universitat Politècnica de Catalunya's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted...
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| Format: | doctoral thesis |
| Publication Date: | 2026 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/457585 |
| Online Access: | https://hdl.handle.net/2117/457585 https://dx.doi.org/10.5821/dissertation-2117-457585 |
| Access Level: | Open access |
| Keyword: | Low-voltage distribution networks State estimation Distribution system state estimation (DSSE) Grid observability Grid monitoring Artificial neural networks (ANN) Probabilistic power flow Monte Carlo simulation Voltage estimation Voltage quality monitoring 621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions 004 - Informàtica Àrees temàtiques de la UPC::Enginyeria elèctrica Àrees temàtiques de la UPC::Informàtica |
| Summary: | In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Universitat Politècnica de Catalunya's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. |
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