
1. 中国电力科学研究院有限公司
2. 国家市场监督管理总局国家标准技术审评中心
Published:2025
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韦于思, 金璐, 高艳玲, et al. 大模型及相关技术在用电需求分析预测领域的应用[J]. 2025, 23(12): 89-100.
韦于思, 金璐, 高艳玲, et al. 大模型及相关技术在用电需求分析预测领域的应用[J]. 2025, 23(12): 89-100. DOI: 10.16543/j.2095-641x.electric.power.ict.2025.12.09.
当前,新型电力系统中的负荷预测正面临多重挑战,传统基于历史负荷规律统计与机器学习的负荷预测方法难以有效应对数据可用性瓶颈、多模态因素解耦、极端场景下的预测建模难题。面对现有负荷预测技术的不足,文章回顾了时序大模型、语义大模型、多模态大模型、检索增强生成技术、智能体技术、思维链技术的研究现状,并分析其在数据异常检测及修复、负荷影响因素分析、小样本及零样本场景下预测等方面的成效与应用前景。展望了大模型及相关技术的发展前景,未来随着技术创新与制度供给,构建智能预测体系将推动电力电量预测向精准、高效、智能化发展。
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