基于预测可信度的多级协调空间负荷预测方法

提出了一种基于负荷预测可信度的多级协调SLF方法。该方法首先确定了元胞历史负荷数据的评价指标,并运用灰色关联度理论,计算出各元胞的负荷预测可信度。然后建立空间电力负荷多级协调模型,并将元胞负荷预测可信度应用到多级协调模型中,最后利用该模型调整元胞目标年的预测值。空间电力负荷多级协调模型以不同层级负荷之间的关系为基础,在一定程度上能够消除上下级电网的预测结果之间出现的不均衡、不协调的现象,从而提高了空间负荷预测结果的准确性,为进一步的电网规划打下了坚实的基础。选取了指数平滑作为预测方法,并对预测结果采用空间电力负荷多级协调模型进行优化调整,调整结果表明空间电力负荷多级协调模型具有实用性和有效性。

Multi-level Coordination of Spatial Load Forecasting Method Based on Prediction Reliability

This paper proposes a multi-level coordination of spatial load forecasting method based on prediction reliability. Firstly, this approach determines the cellular evaluation index of historical load data and calculates the prediction reliability for each cell using gray correlation theory. Secondly, it establishes a multi-level coordination model of spatial power load and applies cellular load prediction reliability to the multi-level coordination model. At last, use this model to adjust the forecasting results of cells which have different prediction reliability. The multi-level coordination model fully considers the association of the power load between different level. To a certain extent, it can eliminate the imbalance of the predicted results between different power level. It also improves the accuracy of spatial load forecasting results and lays a solid foundation for further network planning. This paper choses exponential smoothing forecasting method to predict and uses the multi-level coordination to adjust the forecasting results. In conclusion, numerical example is used to validate the effectiveness of this model.