Forecasting residential electricity demand in provincial China

Area of Science:

• Energy Economics
• Econometrics
• Environmental Science

Background:

• China's electricity generation heavily relies on coal, contributing significantly to CO2 emissions.
• Accurate residential electricity demand forecasting is crucial for infrastructure planning and energy policy in developing nations.
• Existing models often struggle with unreliable functional form assumptions.

Discussion:

• A robust piecewise linear model was employed to analyze the relationship between income and residential electricity consumption.
• Panel data analysis was used for provincial-level forecasting in China during the 13th Five-Year-Plan (2016-2020).
• This approach overcomes limitations of traditional models requiring prior knowledge of functional forms.

Key Insights:

• Developed Chinese provinces are projected to experience slower growth in residential electricity demand.
• Less developed provinces are expected to maintain high growth rates in electricity consumption.
• National residential electricity demand is forecasted to increase by 6.6% annually from 2016 to 2020.

Outlook:

• Populous provinces, like Guangdong, will be primary drivers of increased electricity demand.
• The findings inform energy policy and infrastructure development strategies for China's evolving energy landscape.
• Understanding regional disparities in electricity consumption is vital for sustainable energy planning.