Research and Application of a Hybrid Forecasting Model Based on Data Decomposition for Electrical Load Forecasting

Yuqi Dong, Xuejiao Ma, Chenchen Ma and Jianzhou Wang
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Yuqi Dong: College of Law, Guangxi Normal University, Guilin 541004, China
Xuejiao Ma: School of Statistics, Dongbei University of Finance and Economics, Dalian 116023, China
Chenchen Ma: School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, China
Jianzhou Wang: School of Statistics, Dongbei University of Finance and Economics, Dalian 116023, China

Energies, 2016, vol. 9, issue 12, 1-30

Abstract: Accurate short-term electrical load forecasting plays a pivotal role in the national economy and people’s livelihood through providing effective future plans and ensuring a reliable supply of sustainable electricity. Although considerable work has been done to select suitable models and optimize the model parameters to forecast the short-term electrical load, few models are built based on the characteristics of time series, which will have a great impact on the forecasting accuracy. For that reason, this paper proposes a hybrid model based on data decomposition considering periodicity, trend and randomness of the original electrical load time series data. Through preprocessing and analyzing the original time series, the generalized regression neural network optimized by genetic algorithm is used to forecast the short-term electrical load. The experimental results demonstrate that the proposed hybrid model can not only achieve a good fitting ability, but it can also approximate the actual values when dealing with non-linear time series data with periodicity, trend and randomness.

Keywords: electrical load forecasting; data decomposition; genetic algorithm; generalized regression neural network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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