即插即用能量组织日前负荷概率预测方法Day-ahead Probability Load Forecasting of Energy Tissues With Plug-and-play Function
王玥;张宇帆;李昭昱;艾芊;吕天光;
摘要(Abstract):
随着对利用新能源的迫切需求,分布式能源将以"能量细胞"的形式分布在用户侧,并具有即插即用的特点。受到利益的驱动或稳定性的要求,"能量细胞"将组成形态各异的"能量组织",而新形成的"能量组织"则存在历史数据较少的问题。针对"能量组织"中小样本日前负荷概率预测问题,提出基于pinball损失函数的深度长短时记忆(long short-term memory,LSTM)网络概率预测方法。为解决小样本下深度LSTM网络的过拟合问题,采用自底向上的层次聚类方法进行数据增强,并针对各个分位点进行并行预测。实验结果表明,所提方法能够获得较高的可靠性以及锐度较好的置信区间,可以为日前调度提供合理依据。
关键词(KeyWords): 能源细胞-组织;即插即用;日前负荷概率预测;分位点;pinball损失函数;深度LSTM;数据增强
基金项目(Foundation): 国家自然科学联合基金项目(U1866206)~~
作者(Author): 王玥;张宇帆;李昭昱;艾芊;吕天光;
Email:
DOI: 10.13335/j.1000-3673.pst.2019.0533
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