Electricity usage type selection and model validation based on electricity usage measurements

Teemu Mutanen, Tomi Sorasalmi, Robert Weiss

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

In a smart gird environment, the hourly electricity consumption measurements are used for detection of user segments and of a possible underlying distribution. Electricity usages are segmented according to the daily behaviour. The resulted segments indicate that electricity consumption is distributed differently in different segments. The results show that the electricity consumption is distributed based on a log-normal distribution in some segments and in some subsamples inside the segment. The information can be used as the basis when training other models
Original languageEnglish
Title of host publicationAdvances in Data Mining, Poster and Industry Proceedings 2012
Pages52-60
Publication statusPublished - 2012
MoE publication typeA4 Article in a conference publication
Event12th Industrial Conference on Advances in Data Mining, ICDM 2012 - Berlin, Germany
Duration: 13 Jul 201220 Jul 2012

Conference

Conference12th Industrial Conference on Advances in Data Mining, ICDM 2012
Abbreviated titleICDM 2012
CountryGermany
CityBerlin
Period13/07/1220/07/12

Fingerprint

Electricity
Normal distribution

Keywords

  • high frequency data
  • electricity measurements
  • classication
  • log-normal distribution
  • model validation

Cite this

Mutanen, T., Sorasalmi, T., & Weiss, R. (2012). Electricity usage type selection and model validation based on electricity usage measurements. In Advances in Data Mining, Poster and Industry Proceedings 2012 (pp. 52-60)
Mutanen, Teemu ; Sorasalmi, Tomi ; Weiss, Robert. / Electricity usage type selection and model validation based on electricity usage measurements. Advances in Data Mining, Poster and Industry Proceedings 2012. 2012. pp. 52-60
@inproceedings{016c738dd5a34a23a5d139fca698eebf,
title = "Electricity usage type selection and model validation based on electricity usage measurements",
abstract = "In a smart gird environment, the hourly electricity consumption measurements are used for detection of user segments and of a possible underlying distribution. Electricity usages are segmented according to the daily behaviour. The resulted segments indicate that electricity consumption is distributed differently in different segments. The results show that the electricity consumption is distributed based on a log-normal distribution in some segments and in some subsamples inside the segment. The information can be used as the basis when training other models",
keywords = "high frequency data, electricity measurements, classication, log-normal distribution, model validation",
author = "Teemu Mutanen and Tomi Sorasalmi and Robert Weiss",
note = "Project code: 78244",
year = "2012",
language = "English",
isbn = "978-3-942952-17-0",
pages = "52--60",
booktitle = "Advances in Data Mining, Poster and Industry Proceedings 2012",

}

Mutanen, T, Sorasalmi, T & Weiss, R 2012, Electricity usage type selection and model validation based on electricity usage measurements. in Advances in Data Mining, Poster and Industry Proceedings 2012. pp. 52-60, 12th Industrial Conference on Advances in Data Mining, ICDM 2012, Berlin, Germany, 13/07/12.

Electricity usage type selection and model validation based on electricity usage measurements. / Mutanen, Teemu; Sorasalmi, Tomi; Weiss, Robert.

Advances in Data Mining, Poster and Industry Proceedings 2012. 2012. p. 52-60.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

TY - GEN

T1 - Electricity usage type selection and model validation based on electricity usage measurements

AU - Mutanen, Teemu

AU - Sorasalmi, Tomi

AU - Weiss, Robert

N1 - Project code: 78244

PY - 2012

Y1 - 2012

N2 - In a smart gird environment, the hourly electricity consumption measurements are used for detection of user segments and of a possible underlying distribution. Electricity usages are segmented according to the daily behaviour. The resulted segments indicate that electricity consumption is distributed differently in different segments. The results show that the electricity consumption is distributed based on a log-normal distribution in some segments and in some subsamples inside the segment. The information can be used as the basis when training other models

AB - In a smart gird environment, the hourly electricity consumption measurements are used for detection of user segments and of a possible underlying distribution. Electricity usages are segmented according to the daily behaviour. The resulted segments indicate that electricity consumption is distributed differently in different segments. The results show that the electricity consumption is distributed based on a log-normal distribution in some segments and in some subsamples inside the segment. The information can be used as the basis when training other models

KW - high frequency data

KW - electricity measurements

KW - classication

KW - log-normal distribution

KW - model validation

UR - http://ibai-publishing.org/html/proceeding2012.php

M3 - Conference article in proceedings

SN - 978-3-942952-17-0

SP - 52

EP - 60

BT - Advances in Data Mining, Poster and Industry Proceedings 2012

ER -

Mutanen T, Sorasalmi T, Weiss R. Electricity usage type selection and model validation based on electricity usage measurements. In Advances in Data Mining, Poster and Industry Proceedings 2012. 2012. p. 52-60