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Title: Modeling of monthly residential and commercial electricity consumption using nonlinear seasonal models - the case of Hong Kong
Authors: To, WM
Lee, PKC 
Lai, TM
Issue Date: 2017
Source: Energies, July 2017, v. 10, no. 7, 885
Abstract: Accurate modeling and forecasting monthly electricity consumption are the keys to optimizing energy management and planning. This paper examines the seasonal characteristics of electricity consumption in Hong Kong-a subtropical city with 7 million people. Using the data from January 1970 to December 2014, two novel nonlinear seasonal models for electricity consumption in the residential and commercial sectors were obtained. The models show that the city's monthly residential and commercial electricity consumption patterns have different seasonal variations. Specifically, monthly residential electricity consumption (mainly for appliances and cooling in summer) has a quadratic relationship with monthly mean air temperature, while monthly commercial electricity consumption has a linear relationship with monthly mean air temperature. The nonlinear seasonal models were used to predict residential and commercial electricity consumption for the period January 2015-December 2016. The correlations between the predicted and actual values were 0.976 for residential electricity consumption and 0.962 for commercial electricity consumption, respectively. The root mean square percentage errors for the predicted monthly residential and commercial electricity consumption were 7.0% and 6.5%, respectively. The new nonlinear seasonal models can be applied to other subtropical urban areas, and recommendations on the reduction of commercial electricity consumption are given.
Keywords: Modeling
Forecasting
Monthly electricity consumption
Seasonal analysis
Nonlinear model
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Energies 
ISSN: 1996-1073
DOI: 10.3390/en10070885
Rights: © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
The following publication To, W.-M.; Lee, P.K.C.; Lai, T.-M. Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong. Energies 2017, 10, 885, 1-16 is available at https://dx.doi.org/10.3390/en10070885
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