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The proposed load forecasting approach outperformed the currently available state-of-the-art techniques; namely root mean square error (RMSE), normalized root mean square error (NRMSE), and mean absolute error (MAE).

The innovations at different power system infrastructures’ levels facilitate the integration of new smart grid ideas.

Therefore, the aggregated load exhibits typically regular patterns and more accessible to predict.The first is to evade the uncertainty by clustering/classification techniques which gather comparable customers, days or weather in the hope of decreasing the variance of uncertainty within each cluster [10].However, the accuracy of this technique is heavily dependent on the amount of available data.Communications using, or data stored on, this IS are not private, are subject to routine monitoring, interception, and search, and may be disclosed or used for any USG-authorized purpose.This IS includes security measures (e.g., authentication and access controls) to protect USG interests--not for your personal benefit or privacy.

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