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.
Highlights
The modeling and forecasting of electricity consumption are crucial to a country’s or city’s energy management and planning, as well as to its economic development
Following the classification of the Hong Kong Census and Statistics Department [30], the electricity consumption of Hong Kong is divided into residential electricity consumption, commercial electricity consumption, industrial electricity consumption, and the electricity used by public services, such as street lighting [30]
This paper explores Hong Kong’s residential and commercial electricity consumption using monthly electricity consumption data between January 1970 and December 2014
Summary
The modeling and forecasting of electricity consumption are crucial to a country’s or city’s energy management and planning, as well as to its economic development. Previous research has shown that the growth of energy consumption is related to the increase in population and economic growth of a country or city [1,2,3,4,5,6,7], and the demand for more electricity is expected to continue [4,5,6]. Niu et al [6] studied the association between electricity consumption and human development level. Reported that, generally, higher incomes lead to a greater demand in electricity and a higher level of human development. Li et al [8] explored the use of a least squares support vector
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