A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation

A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation

The study of the behavior of smart distribution systems under increasingly dynamic operating conditions requires realistic and time-varying load profiles to run comprehensive and accurate simulations of power flow analysis, system state estimation and optimal control strategies. However, due to the...

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Bibliographic Details
Main Authors: Enrico Dalla Maria, Mattia Secchi, David Macii
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Energies
Subjects:
load modeling for smart grid applications
time series clustering
Aggregate Load Models
Gaussian Mixture Models
time-inhomogeneous Markov chain
power systems
Online Access:https://www.mdpi.com/1996-1073/15/1/269

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https://www.mdpi.com/1996-1073/15/1/269

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