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International Conference on Software Technology and Engineering (ICSTE 2012)

Jianhong Zhou
Jianhong Zhou
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Accurate monthly electricity demand forecasting is the foundation of power system operation and planning. Grey Model (Short of “GM”) has been used to forecast widely in many domains, due to its effective prediction with little samples, incomplete information. Electricity demand of throughout society can be divided into the consumption of residents and the demand of three industries. Meanwhile, it can be regard as a grey system, so it makes sense to forecast it by GM(1,n) model. This paper proposes a novel approach to monthly electricity demand forecasting combining seasonal exponential transformation and residual error modified method with GM(1,n) model. Finally, apply the novel model to a real dataset in Guangzhou, the result shows that it performs well.

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