Research on Power Demand Forecasting of Beijing Based on Regression Analysis
Shuyu Dai, Yan Li, Dongxiao Niu
Available Online December 2017.
- https://doi.org/10.2991/mcei-17.2017.56How to use a DOI?
- Electricity demand forecast; Unitary regression; Multiple regression
- With the continuous development of the national economy, people's demand for electricity is increasing day by day, and the power industry plays an increasingly important role in the social development. Power demand forecasting is the basic work of power management, planning, programming and other management departments in power system. Improving the technical level of power demand forecasting can provide a strong basis for power system scheduling and long-term planning. This paper analyzes the influencing factors of electricity demand in Beijing, analyzes the influence of GDP, industrial structure, population and urbanization level on the electricity consumption of Beijing, and then uses the regression analysis method based on the collected economic data and power data to forecast the electricity consumption of the whole society in Beijing from 2017 to 2022.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Shuyu Dai AU - Yan Li AU - Dongxiao Niu PY - 2017/12 DA - 2017/12 TI - Research on Power Demand Forecasting of Beijing Based on Regression Analysis BT - 2017 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/mcei-17.2017.56 DO - https://doi.org/10.2991/mcei-17.2017.56 ID - Dai2017/12 ER -