Modern computerized distribution load forecasting methods, although accurate when applied to urban areas, give somewhat less satisfactory results when forecasting load grcwrth in sparsely populated d areas. This paper examines the differences between rural and urban load growth histories, identifying a major difference in the observed behavior of load growth. This difference is exploited in a new simulation forecasting algorithm. Tests show the new method is as accurate in forecasting rural load growth and as useful for analyzing DSM impacts than past methods, while requiring considerably lower computer resources and data than other simulation methods of comparable acaraacy.
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