基于预测误差分布特性统计分析的概率性短期负荷预测

现有短期负荷预测方法一般只能给出确定性负荷预测结果，难以满足电力市场中不确定性风险分析决策的要求。文中提出了一种基于负荷预测误差特性的统计分析的概率性预测方法。该方法首先从时段与负荷水平2个联合维度上建立了对预测误差分布规律进行统计分析的模型，并提出了检验该统计规律有效性的原则和方法；将验证后的预测误差统计分布规律与确定性的负荷预测结果相结合，即可得到概率性的负荷预测结果。基于该结果，还能求取某一置信水平下的预测负荷曲线的包络线。结合实际电网数据验证了所提出方法的有效性和实用性，为概率性短期负荷预测提供了一条可行的新思路。

Short Term Probabilistic Load Forecasting Based on Statistics of Probability Distribution of Forecasting Errors

As the existing deterministic short-term load forecasting methods hardly meet the demands of uncertain risk analysis and decision-making in electricity market, a probabilistic load forecasting method based on the statistics of load forecasting errors' characteristic is presented at length. First, a statistic analysis model for the distribution regularities of forecasting error is established in two dimensions. The principle and method to verify the validity of statistical regularity is then proposed. At last, by combining the verified distribution regularity and the deterministic load forecasting result, the probability distribution of load forecasting can be gained. According to the result, envelopes of load forecasting curve under certain confidence level can also be obtained. The validity and practicability of the proposed method are tested with the actual data. It is expected that the proposed approach can provide a new feasible solution for the probabilistic short-term load forecasting.