Research on Electricity Demand Combination Forecasting Model in Beijing-Tianjin-Hebei Region Based on Shapley Value

DOI

10.2991/iccia-16.2016.88How to use a DOI?

Keywords

Shapley value; Combined model; Electricity demand forecasting.

Abstract

Due to the electricity power is the foundation of economic development, reasonable and accurate electricity demand forecasting not only helps to develop electricity power planning scientifically, but also has important reference value to the economic development planning. In order to integrate different forecast models' strengths as well as improve the forecast accuracy, this paper puts forward the electricity demand forecasting model based on Shapley value. First, it chooses one-dimensional linear regression model, Holt two-parameter linear exponential smoothing model and ARIMA model for electricity demand forecasting respectively, and through the game theory Shapley value theory determines the weight of single model in the portfolio model, and then the combined forecasting result is obtained; Second, it analyzes the electricity demand data in Beijing-Tianjin-Hebei Region and the results show that the proposed method has high forecast accuracy; Finally, it forecasts electricity demand in Beijing-Tianjin-Hebei Region during "13th five-year" period and provides decision-making basis for the economic development planning of Beijing, Tianjin Hebei province during "13th five-year" period.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuqing Wang
AU  - Chenjun Sun
AU  - Lilin Peng
AU  - Yang Liu
AU  - Ming Zeng
PY  - 2016/09
DA  - 2016/09
TI  - Research on Electricity Demand Combination Forecasting Model in Beijing-Tianjin-Hebei Region Based on Shapley Value
BT  - Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
PB  - Atlantis Press
SP  - 481
EP  - 486
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-16.2016.88
DO  - 10.2991/iccia-16.2016.88
ID  - Wang2016/09
ER  -