Forecasting residential electricity demand in provincial China

Hua Liao*, Yanan Liu, Yixuan Gao, Yu Hao, Xiao Wei Ma, Kan Wang

*Corresponding author for this work

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    Abstract

    In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016–2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016–2020, and populous provinces such as Guangdong will be the main contributors to the increments.

    Original languageEnglish
    Pages (from-to)6414-6425
    Number of pages12
    JournalEnvironmental Science and Pollution Research
    Volume24
    Issue number7
    DOIs
    Publication statusPublished - 1 Mar 2017

    Keywords

    • China
    • Electricity demand
    • Forecast
    • Piecewise linear model
    • Provincial panel data
    • Residential sector

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    Liao, H., Liu, Y., Gao, Y., Hao, Y., Ma, X. W., & Wang, K. (2017). Forecasting residential electricity demand in provincial China. Environmental Science and Pollution Research, 24(7), 6414-6425. https://doi.org/10.1007/s11356-016-8275-8