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Deployment of forecasting tools in diverse demonstration ar..:

, In: 27th International Conference on Electricity Distribution (CIRED 2023),

Turk, A. ; Kahraman, A. ; Yang, G.... - p. None , 2023

Link: https://doi.org/10.1049/icp.2023.1199

RT 
T1 <cTitle>27th International Conference on Electricity Distribution (CIRED 2023)</cTitle>: T1 <Title>Deployment of forecasting tools in diverse demonstration areas to improve energy scheduling of microgrids</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10267310&Exemplar=1&LAN=DE
				
A1 Turk, A.
A1 Kahraman, A.
A1 Yang, G.
A1 Sideratos, G.
A1 Paspatis, A.
A1 Kotsampopoulos, P.
A1 Shahare, K.
A1 Mitra, A.
A1 Naware, D.
YR 2023
K1 convolutional neural nets
K1 distributed power generation
K1 learning (artificial intelligence)
K1 photovoltaic power systems
K1 power engineering computing
K1 power grids
K1 radial basis function networks
K1 recurrent neural nets
K1 renewable energy sources
K1 wind power
K1 Bornholm island
K1 Denmark
K1 different forecasting algorithms
K1 energy scheduling
K1 entire island
K1 fluctuations
K1 forecasting renewable generation
K1 forecasting tools
K1 fuzzy-RBF-CNN
K1 Gaidouromandra microgrid
K1 Greece
K1 human behaviour
K1 hybrid LSTM-convolutional neural network
K1 Kythnos
K1 Kythnos island
K1 long-short term memory auto-encoder
K1 machine learning approaches
K1 measurement data
K1 operational aspects
K1 real-time operation
K1 scheduling purposes
K1 solar photovoltaic power
K1 specific characteristic
K1 weather conditions
SP None
LK http://dx.doi.org/https://doi.org/10.1049/icp.2023.1199
DO https://doi.org/10.1049/icp.2023.1199
SF ELIB - SuUB Bremen

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