电力需求侧管理2024，Vol.26Issue(1)：9-15,7.DOI:10.3969/j.issn.1009-1831.2024.01.002
基于数据融合的中长期概率性负荷预测方法研究
Research on medium and long-term probabilistic load forecasting method based on data fusion
摘要
Abstract
Monthly load forecasting is the basis for medium and long-term operation of power system and development of marketing work,and probabilistic power load forecasting can portray medium and long-term uncertainty,and better support the new type of power system load assessment and regulation strategy development.In this context,the medium and long-term probabilistic forecasting method is stud-ied with the system load as the research object,and the medium and long-term probabilistic forecasting method based on fine-grained data fusion is proposed.Firstly,an hourly multiple linear regression model is established to model the fine-grained loads based on the influenc-ing factors,and then the fine-grained forecasts under different scenarios are generated based on the different predicted values of the influ-encing factors.Secondly,according to the"bottom-up"temporal hierarchy coordination strategy,monthly aggregation is performed for each scenario,and monthly load forecasts are generated for different hierarchical regions to form probabilistic forecasts.Finally,the effectiveness of the method is verified by taking load data of a region in eastern China and its subordinate areas as an example.关键词
中长期负荷预测/细粒度/数据融合/概率性预测Key words
medium and long-term load forecasting/fine-grained/data fusion/probabilistic forecasting分类
信息技术与安全科学引用本文复制引用
龙禹,阮文骏,刘梅,周雨奇..基于数据融合的中长期概率性负荷预测方法研究[J].电力需求侧管理,2024,26(1):9-15,7.基金项目
国家电网有限公司科技项目(5108-202218 280A-2-0-XG) （5108-202218 280A-2-0-XG）
