A Semi-Parametric Time Series Approach in Modelling Hourly Electricity Loads

Jun Liu

A Semi-Parametric Time Series Approach in Modelling Hourly Electricity Loads

Information Systems & Analytics

Research output: Contribution to conference › Presentation

Abstract

A semi-parametric approach is developed to model nonlinear time series. This approach is used on hourly electricity load data, it considers the effect of temperature combined with those of time and day type. The temperature effect is modelled by nonparametric smoothing. An ARIMA model is used to model the serial correlation. An iterative backfitting algorithm is proposed for estimation. The post sample forecasting performance and comparative results show good potential of this approach.

Original language	American English
State	Published - Nov 16 2005
Event	INFORMS Annual Meeting - Phoenix, AZ Duration: Oct 14 2012 → …

Conference

Conference	INFORMS Annual Meeting
Period	10/14/12 → …

Keywords

ARIMA
Hourly electricity load data
Nonlinear
Nonparametric smoothing
Semi-parametric approach
Time series

DC Disciplines

Business

Cite this

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title = "A Semi-Parametric Time Series Approach in Modelling Hourly Electricity Loads",

abstract = " A semi-parametric approach is developed to model nonlinear time series. This approach is used on hourly electricity load data, it considers the effect of temperature combined with those of time and day type. The temperature effect is modelled by nonparametric smoothing. An ARIMA model is used to model the serial correlation. An iterative backfitting algorithm is proposed for estimation. The post sample forecasting performance and comparative results show good potential of this approach.",

keywords = "ARIMA, Hourly electricity load data, Nonlinear, Nonparametric smoothing, Semi-parametric approach, Time series",

author = "Jun Liu",

year = "2005",

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language = "American English",

note = "INFORMS Annual Meeting ; Conference date: 14-10-2012",

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T1 - A Semi-Parametric Time Series Approach in Modelling Hourly Electricity Loads

AU - Liu, Jun

PY - 2005/11/16

Y1 - 2005/11/16

N2 - A semi-parametric approach is developed to model nonlinear time series. This approach is used on hourly electricity load data, it considers the effect of temperature combined with those of time and day type. The temperature effect is modelled by nonparametric smoothing. An ARIMA model is used to model the serial correlation. An iterative backfitting algorithm is proposed for estimation. The post sample forecasting performance and comparative results show good potential of this approach.

AB - A semi-parametric approach is developed to model nonlinear time series. This approach is used on hourly electricity load data, it considers the effect of temperature combined with those of time and day type. The temperature effect is modelled by nonparametric smoothing. An ARIMA model is used to model the serial correlation. An iterative backfitting algorithm is proposed for estimation. The post sample forecasting performance and comparative results show good potential of this approach.

KW - ARIMA

KW - Hourly electricity load data

KW - Nonlinear

KW - Nonparametric smoothing

KW - Semi-parametric approach

KW - Time series

UR - https://informs.emeetingsonline.com/emeetings/formbuilder/clustersessiondtl.asp?csnno=4072&mmnno=141&ppnno=15593

M3 - Presentation

T2 - INFORMS Annual Meeting

Y2 - 14 October 2012

ER -

A Semi-Parametric Time Series Approach in Modelling Hourly Electricity Loads

Abstract

Conference

Keywords

DC Disciplines

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