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Titel:

Monitoring Smart Energy Systems using Multi-timescale Nexting

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Vortrag / Präsentation
Autor(en):
Johannes Feldmaier, Dominik Meyer, Klaus Diepold
Abstract:
In today's energy grids the complexity increases and more and more autonomous control systems take over. But especially in energy systems the automatic control and decision making is critical and often human operators are required. Keeping an operator in the control-loop, good prediction algorithms can help to reduce work load and errors. Prediction algorithms supply the operator with additional information so that proactive commands can help to keep a system in an optimal state. But modeling la...     »
Stichworte:
reinforcement learning, temporal difference learning, nexting, smart energy systems
Kongress- / Buchtitel:
Integration of Sustainable Energy Conference (iSEneC)
Datum der Konferenz:
12.07.2016
Jahr:
2016
 BibTeX