Combined modeling for electric load forecasting with adaptive particle swarm optimization

Jianzhou Wang, Suling Zhu, Wenyu Zhang and Haiyan Lu

Energy, 2010, vol. 35, issue 4, 1671-1678

Abstract: Electric load forecasting is crucial for managing electric power systems economically and safely. This paper presents a new combined model for electric load forecasting based on the seasonal ARIMA forecasting model, the seasonal exponential smoothing model and the weighted support vector machines. The combined model can effectively count for the seasonality and nonlinearity shown in the electric load data and give more accurate forecasting results. The adaptive particle swarm optimization is employed to optimize the weight coefficients in the combined forecasting model. The proposed combined model has been compared with the individual models and the other combined model reported in the literature and its results are promising.

Keywords: Load forecasting; Combined model; Adaptive particle swarm optimization; Forecasting accuracy (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (50)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:35:y:2010:i:4:p:1671-1678

DOI: 10.1016/j.energy.2009.12.015

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