School of Management and Economics, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing, 100081, China.
Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology (BIT), Beijing, 100081, China.
Environ Sci Pollut Res Int. 2017 Mar;24(7):6414-6425. doi: 10.1007/s11356-016-8275-8. Epub 2016 Dec 30.
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.
在中国，超过 80%的电力来自于煤炭，这主导了二氧化碳的排放。住宅电力需求预测在电力基础设施规划和能源政策设计中起着重要作用，但对于发展中国家来说，进行准确的预测具有挑战性。本文使用面板数据预测了中国“十三五”规划（2016-2020 年）期间的省级住宅用电量。为了克服广泛使用的预测模型在函数形式上缺乏可靠先验知识的局限性，利用简化形式的稳健分段线性模型来捕捉收入与住宅用电量之间的非确定性关系。预测结果表明，发达省份的增长率将会放缓，而欠发达省份仍将保持快速增长。2016-2020 年期间，中国住宅电力需求将以每年 6.6%的速度增长，广东等人口大省将是增长的主要贡献者。
