Modeling flexibility using artificial neural networks

Modeling flexibility using artificial neural networks

Abstract The flexibility of distributed energy resources (DERs) can be modeled in various ways. Each model that can be used for creating feasible load profiles of a DER represents a potential model for the flexibility of that particular DER. Based on previous work, this paper presents generalized pa...

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Bibliographic Details
Main Authors: Kevin Förderer, Mischa Ahrens, Kaibin Bao, Ingo Mauser, Hartmut Schmeck
Format: Article
Language:English
Published: SpringerOpen 2018-10-01
Series:Energy Informatics
Subjects:
Smart Grid
Modeling
Flexibility
Distributed energy resources
Demand side management
Machine learning
Online Access:http://link.springer.com/article/10.1186/s42162-018-0024-4

Internet

http://link.springer.com/article/10.1186/s42162-018-0024-4

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