Artificial Neural Network Based Distribution Grids State Estimation

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The Artificial Neural Network based State Estimation (ANN-SE) provides local grid observability to the Distribution Systems Operator (DSO) in low voltage (LV) power grid areas, that are normally unobservable. The product performs the State Estimation at distribution level with a low number of available measurements. This enables the DSO to control normally un-observable LV grids. The tool leverages AI and simulation based techniques to carry out the grid monitoring task through the estimation of the network state

Countries:
Spain
Regions:
Catalonia
Centers:
UNIVERSITAT POLITECNICA DE CATALUNYA
Other entities:
Sectors:
Energy
Subsectors:
TRL Level:
TRL 3 – experimental proof of concept
BRL Level:
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Sustainable Development Goal:
Applications

Advantages: Solves the problem of unobservability in LV grid Low-cost monitoring with scarce measurements Leverage on AI tools Leverage on digital twin simulations of the power grid Application: Smart Grids, electrical industry and distribution grids

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