结算参数的预测方法和装置、存储介质及电子设备
CN119941305BActive Publication Date: 2026-07-17HUANENG CLEAN ENERGY RES INST +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUANENG CLEAN ENERGY RES INST
- Filing Date
- 2024-12-31
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing methods for predicting electricity settlement parameters rely on short-term disclosed data, making it difficult to accurately capture parameter change trends over medium to long periods, resulting in inaccurate predictions.
Method used
A settlement parameter prediction network employing a two-layer convolutional sub-network and a two-layer feedforward sub-network is used to extract settlement time-series features and predict medium- and long-term settlement parameters by iteratively training on periodic attribute data.
Benefits of technology
It improves the accuracy of settlement parameter prediction, effectively addresses complex changes in energy in the medium and long term, enhances the accuracy of energy allocation decisions, and reduces energy waste.
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Abstract
本申请公开了一种结算参数的预测方法和装置、存储介质及电子设备。其中，该方法包括：获取待预测的目标结算周期的周期属性数据，其中，目标结算周期的周期时长大于或等于目标时长阈值；在结算参数预测网络中基于从周期属性数据中提取出的结算时序特征，预测出目标结算周期对应的目标结算参数，其中，结算参数预测网络中包括双层卷积子网络和双层前馈子网络，结算参数预测网络为利用结算数据样本进行多次迭代训练后直至达到收敛条件的神经网络，收敛条件指示训练中的结算参数预测网络输出的训练损失值已达到设定的损失条件值。本申请解决了由于短期时效的披露数据难以捕捉中长期的参数变化趋势造成的预测结果难以确保准确性的技术问题。
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