Bottom-up modeling of domestic appliances with Markov chains and semi-Markov processes

Rajmund Drenyovszki; Lóránt Kovács; Kálmán Tornai; András Oláh; István Pintér

Kybernetika (2017)

  • Volume: 53, Issue: 6, page 1100-1117
  • ISSN: 0023-5954

Abstract

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In our paper we investigate the applicability of independent and identically distributed random sequences, first order Markov and higher order Markov chains as well as semi-Markov processes for bottom-up electricity load modeling. We use appliance time series from publicly available data sets containing fine grained power measurements. The comparison of models are based on metrics which are supposed to be important in power systems like Load Factor, Loss of Load Probability. Furthermore, we characterize the interdependence structure of the models with autocorrelation function as well. The aim of the investigation is to choose the most appropriate and the most parsimonious models for Smart Grid simulation purposes and applications like Demand Side Management and load scheduling. According to our results most appliance types can be modeled adequately with two states (on/off model) and the semi-Markov process can reproduce the properties of an aggregate load well compared to the original time series. With the price of more parameters of the semi-Markov model compared to identically distributed random sequence and first order Markov chain, it gives better results when the autocorrelation function, Loss of Load Probability and Load Factor are considered.

How to cite

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Drenyovszki, Rajmund, et al. "Bottom-up modeling of domestic appliances with Markov chains and semi-Markov processes." Kybernetika 53.6 (2017): 1100-1117. <http://eudml.org/doc/294774>.

@article{Drenyovszki2017,
abstract = {In our paper we investigate the applicability of independent and identically distributed random sequences, first order Markov and higher order Markov chains as well as semi-Markov processes for bottom-up electricity load modeling. We use appliance time series from publicly available data sets containing fine grained power measurements. The comparison of models are based on metrics which are supposed to be important in power systems like Load Factor, Loss of Load Probability. Furthermore, we characterize the interdependence structure of the models with autocorrelation function as well. The aim of the investigation is to choose the most appropriate and the most parsimonious models for Smart Grid simulation purposes and applications like Demand Side Management and load scheduling. According to our results most appliance types can be modeled adequately with two states (on/off model) and the semi-Markov process can reproduce the properties of an aggregate load well compared to the original time series. With the price of more parameters of the semi-Markov model compared to identically distributed random sequence and first order Markov chain, it gives better results when the autocorrelation function, Loss of Load Probability and Load Factor are considered.},
author = {Drenyovszki, Rajmund, Kovács, Lóránt, Tornai, Kálmán, Oláh, András, Pintér, István},
journal = {Kybernetika},
keywords = {appliance modeling; bottom-up; Markov chain; semi-Markov process; smart grid},
language = {eng},
number = {6},
pages = {1100-1117},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Bottom-up modeling of domestic appliances with Markov chains and semi-Markov processes},
url = {http://eudml.org/doc/294774},
volume = {53},
year = {2017},
}

TY - JOUR
AU - Drenyovszki, Rajmund
AU - Kovács, Lóránt
AU - Tornai, Kálmán
AU - Oláh, András
AU - Pintér, István
TI - Bottom-up modeling of domestic appliances with Markov chains and semi-Markov processes
JO - Kybernetika
PY - 2017
PB - Institute of Information Theory and Automation AS CR
VL - 53
IS - 6
SP - 1100
EP - 1117
AB - In our paper we investigate the applicability of independent and identically distributed random sequences, first order Markov and higher order Markov chains as well as semi-Markov processes for bottom-up electricity load modeling. We use appliance time series from publicly available data sets containing fine grained power measurements. The comparison of models are based on metrics which are supposed to be important in power systems like Load Factor, Loss of Load Probability. Furthermore, we characterize the interdependence structure of the models with autocorrelation function as well. The aim of the investigation is to choose the most appropriate and the most parsimonious models for Smart Grid simulation purposes and applications like Demand Side Management and load scheduling. According to our results most appliance types can be modeled adequately with two states (on/off model) and the semi-Markov process can reproduce the properties of an aggregate load well compared to the original time series. With the price of more parameters of the semi-Markov model compared to identically distributed random sequence and first order Markov chain, it gives better results when the autocorrelation function, Loss of Load Probability and Load Factor are considered.
LA - eng
KW - appliance modeling; bottom-up; Markov chain; semi-Markov process; smart grid
UR - http://eudml.org/doc/294774
ER -

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