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

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  • Wai-Ming To

    (School of Business, Macao Polytechnic Institute, Macao, China)

  • Peter Ka Chun Lee

    (Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong, China)

  • Tsz-Ming Lai

    (School of Business, Macao Polytechnic Institute, Macao, China)

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.

Suggested Citation

  • Wai-Ming To & Peter Ka Chun Lee & Tsz-Ming Lai, 2017. "Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong," Energies, MDPI, vol. 10(7), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:885-:d:103176
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    6. Shi, Changfeng & Zhao, Yi & Zhang, Chenjun & Pang, Qinghua & Chen, Qiyong & Li, Ang, 2022. "Research on the driving effect of production electricity consumption changes in the Yangtze River Economic Zone - Based on regional and industrial perspectives," Energy, Elsevier, vol. 238(PA).
    7. Angreine Kewo & Pinrolinvic D. K. Manembu & Per Sieverts Nielsen, 2020. "Synthesising Residential Electricity Load Profiles at the City Level Using a Weighted Proportion (Wepro) Model," Energies, MDPI, vol. 13(14), pages 1-28, July.
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