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Energies 2017, 10(7), 885; doi:10.3390/en10070885

Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong

1
School of Business, Macao Polytechnic Institute, Macao, China
2
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong, China
*
Author to whom correspondence should be addressed.
Academic Editor: Susan Krumdieck
Received: 25 May 2017 / Revised: 20 June 2017 / Accepted: 23 June 2017 / Published: 30 June 2017
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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. View Full-Text
Keywords: modeling; forecasting; monthly electricity consumption; seasonal analysis; nonlinear model modeling; forecasting; monthly electricity consumption; seasonal analysis; nonlinear model
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MDPI and ACS Style

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.

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