Daily load profile modeling considering residential consumers' routine activities

Marven E. Jabian, Ryohei Funaki, Junichi Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Power consumption forecasts are among the vital data used by Distribution Utilities (DUs) in daily power supply procurement. The most inconsistent load profile among the consumer types are from residential consumers due to fluctuations in their power consumptions. This is due to a wide variation of daily routine and non-routine activities performed by every household member at varied times of the day. The routine activities contribute largely to the consumer's daily load profile and power consumption. Consequently, determining consumers routine activities enables the DUs to have a more precise day-ahead forecast. This paper proposes a method that identifies consumers' routine activities and reconstructs their corresponding daily load profiles using the historical power consumption data. This is accomplished by finding the power consumption curves appearing regularly in many of consumers' data to identify candidates of routine activities and further evaluating probabilities that a specific consumer performs those activities to determine whether each of them is actually a routine activity. Probabilistically, the daily load profile is reconstructed using the determined routine activity. Attributing to the probabilistic nature of the analysis, a 95% confidence limit is calculated for every 15-minute power consumption so that DUs have a reliable data on residential consumers' daily power demand.

Original languageEnglish
Title of host publication2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages793-796
Number of pages4
ISBN (Electronic)9781728198026
DOIs
Publication statusPublished - Oct 13 2020
Event9th IEEE Global Conference on Consumer Electronics, GCCE 2020 - Kobe, Japan
Duration: Oct 13 2020Oct 16 2020

Publication series

Name2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020

Conference

Conference9th IEEE Global Conference on Consumer Electronics, GCCE 2020
CountryJapan
CityKobe
Period10/13/2010/16/20

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Media Technology
  • Instrumentation
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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