基于集合天气预报的新型能源概率预测技术研究

Han Wu, Yang Yuan, W. Yu, Chao Wu, Hao Huang, Annan Dong
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引用次数: 1

摘要

提出了一种基于多初始值、多模式、多物理过程、多算法扰动和BMA+EMOS统计建模的集合天气预报方法。在集合天气预报方法的基础上,提出了一种结合禁忌算法和BP神经网络算法的能源概率功率预测新方法。通过设计算例分析,所提方法能有效降低预测偏差,将概率预测的上下限带宽降低25%,克服功率分布肥尾和多模态异常,使功率预测结果更加稳定准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on New Energy Probability Prediction Technology Based on Ensemble Weather Forecast
In this paper, a ensemble weather forecasting method based on multi-initial value, multi-mode and multi-physical process, with multiple algorithm perturbations, and BMA+EMOS statistical modeling is proposed. Based on the ensemble weather forecasting method, a new energy probabilistic power prediction method combining taboo algorithm and BP neural network algorithm is proposed. Through the design example analysis, the proposed method can effectively reduce the prediction bias, reduce the upper and lower limit bandwidth of probability prediction by 25%, and overcome the power distribution fat tail and multimodal anomalies, making the power prediction results more stable and accurate.
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