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The month ahead monthly load forecasting accuracy is approximately 98%.
Hence, the advantage of forecasting the average daily electricity price profile directly instead of forecasting the hourly electricity prices and average the forecasts afterwards is clear due to the higher accuracy of monthly load forecasting and average fuel price forecasting.
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Among all load forecasting problems, long-term system load forecasting has its own characteristics.
Very short-term load forecasting (VSTLF) provides load forecasts up to one day ahead.
A probabilistic load forecasting method based on the statistics characteristic of load forecasting error is proposed for the field of short-term load forecasting [9].
Finally, the system load forecasting results are obtained by summing up all the ARIMA forecasting results.
Finally, the system load forecasting result is obtained by summing up all the ARIMA forecasts.
Literature on probabilistic load forecasting are relatively limited compare to traditional point forecasting.
Therefore, many load forecasting models would incorporate calendar information.
These structural breaks in the holiday pattern complicate load forecasting.
In [10] spatial electric load forecasting approaches are discussed comprehensively.
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