| 沈聪,艾芊,李晓露,高扬,陶伟健,赵晨阳.基于MPA-CNN-LSTM融合模型与置信区间修正的行业用户负荷潜力评估[J].电力需求侧管理,2026,28(1):8-16 |
| 基于MPA-CNN-LSTM融合模型与置信区间修正的行业用户负荷潜力评估 |
| Industry user load potential assessment based on MPA-CNN-LSTM fusion model and confidence interval correction |
| 投稿时间：2025-09-26 修订日期：2025-11-08 |
| DOI：10.3969/j.issn.1009-1831.2026.01.002 |
| 中文关键词: 负荷削减特性 MPA算法优化 CNN-LSTM 置信区间修正 潜力评估 |
| 英文关键词: load shedding characteristics MPA algorithm optimisation CNN-LSTM confidence interval correction potential assessment |
| 基金项目:国家重点研发计划(2021YFB2401203)；国家自然科学基金(52407127)；上海浦江人才计划(24PJA045) |
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| 中文摘要: |
| 随着"双碳"目标提出,新能源装机容量增大,且用户用电负荷特性变化及负荷量增加,电网供需平衡压力日益严峻,为支撑电网运行平衡,充分挖掘行业用户负荷可调节潜力,提出了基于MPA-CNN-LSTM融合模型与置信区间修正的行业用户负荷潜力评估策略。首先,在原有负荷特性基础上提出负荷削减特性表征同一行业不同用户负荷削减类别及方式作为MPA-CNN-LSTM预测模型输入;其次,依据响应用户实际调节潜力基于MPA算法优化的CNN-LSTM神经网络进行训练并预测行业用户可调节潜力;最后,通过置信区间修正法修正行业用户可调节潜力,提高预测准确性。 |
| 英文摘要: |
| Against the backdrop of "dual-carbon" goals, growing installed capacity of new energy, changes in user load characteristics and increased load demand have intensified pressure on grid supply-demand balance. To maintain grid stability and fully tap the adjustable load potential of industrial users, an industrial user load potential assessment strategy based on a hybrid MPA-CNN-LSTM model combined with confidence interval correction is proposed. First, building on existing load characteristics, load reduction characteristics are introduced—describing the types and methods of load reduction among different users in the same industry—as inputs to the MPA-CNN-LSTM prediction model. Second, the MPA-optimized CNN-LSTM neural network is trained using actual adjustable potential data from responsive users to predict industrial users' adjustable potential. Finally, the confidence interval correction method is applied to refine the predicted adjustable potential, enhancing accuracy. |
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