基于功率或电量预测的智能配电网统计线损同期化方法

智能配电网中电量采集数据缺失、遗漏导致按月线损统计不是严格意义上的自然月。为解决线损统计不同期问题，提出基于功率或电量预测的方法来改善配网线损统计。通过挖掘售电量数据，提出了一种基于年度售电量的灰色预测结果。再根据季度、月度层级占比得到月售电量的预测方法，与实际值的平均相对误差仅为1.94%，证明此方法简单有效适合电力各部门的广泛应用。将月售电量预测结果应用于线损统计，结合供电比例系数法，改善表计供、售电量不对应的问题，使得同期化，对按月实时分析网损有实际意义。

A method for synchronous line loss statistics of distribution network based on load or electricity consumption forecasting

Asynchronous line loss statistics of smart distribution network due to automatic meter failure and data missing are confusing. To solve this problem, a new method for synchronous line loss statistics based on power load or electricity consumption forecasting is put forward. Through data mining, this paper presents a monthly electricity forecasting method based on the result of annual electricity by grey model and quarterly and monthly hierarchic proportion. The average relative forecasting error is only 1.94% which indicates that this method is simple and effective and can be widely applied in electric department. And the forecasting results coupled with daily power supply ratio are applied in synchronous line loss statistic, which improves the inconsistency of power supply and electricity consumption and makes them synchronous. It has actual meaning for monthly line loss analysis.