Short-term load prediction method and system based on long short-term memory network, and terminal

• Main Authors: PENG JIAO, KANG CHUNTING, MU QUN, YANG TIANGUANG, WEI XIAOJING, SHEN ZIQI, YANG HUIFENG, CHEN XI, ZHU JINHUI, XIN RUI, SONG JIMENG, ZHAO XIAOMENG, WANG ZHAOHUI, LU XIN, FAN TAO, LU YANYAN, LI SHOUCHAO, JIANG DAN, ZHANG YU, LI YISONG, KANG ZHIZENG, SONG JINWEI, WU HAIHAN
• Format: Patent
• Language: Chinese; English
• Published: 24.02.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a short-term load prediction method and system based on a long short-term memory network, and a terminal, mainly relates to the technical field of short-term load prediction, and is used for solving the problem that an existing method is difficult to fit a load rule. Comprising the following steps: acquiring an original power data set from power transformation equipment, and determining an occurrence frequency value to create an FP tree; obtaining a sample data set based on the FP tree and a preset node threshold; and taking the sample data set as the input of an LSTM network algorithm, and obtaining a prediction result. According to the method, the prediction result can be quickly and effectively obtained. 本申请公开了一种基于长短期记忆网络的短期负荷预测方法、系统及终端，主要涉及短期负荷预测技术领域，用以解决现有的方法难以拟合负荷规律的问题。包括：从变电设备中获取原始电力数据集，确定出现频次值，以创建FP树；基于FP树和预设节点阈值，获得样本数据集；将样本数据集作为LSTM网络算法的输入，获取预测结果。本申请通过上述方法实现了快速有效地获得预测结果。