| 黄华胜,闫富荣,赵 璐,程少华,彭新宇,张 文,陈 雁,欧阳红.基于行业发展趋势的回归模型在电费回收风险预测中的应用研究[J].电力需求侧管理,2023,25(5):98-103 |
| 基于行业发展趋势的回归模型在电费回收风险预测中的应用研究 |
| Research on risk prediction of electric charge recycling using regression model based on the industry development trend |
| 投稿时间：2023-05-03 修订日期：2023-06-13 |
| DOI：10. 3969 / j. issn. 1009-1831. 2023. 05. 016 |
| 中文关键词: 电费回收 售电量 行业发展趋势预测 分类回归算法 风险概率 |
| 英文关键词: electric charge recycling electricity sales industry development trend prediction classification and regression algorithm risk probability |
| 基金项目:国家电网有限公司科技项目（52680021N00Q） |
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| 中文摘要: |
| 近年来,受电力体制改革、经济转型升级、环保力度加大、极端天气频发以及新冠疫情等影响,一些用电客户面临产量下降、销售困难等问题,进一步增加了电费回收的难度。针对此问题,提出了一种基于行业发展趋势的回归模型,对电费回收风险进行预测。首先利用季节调整算法提取行业历史售电量发展的趋势项,然后对影响售电量趋势的因素进行综合、定量分析。在此基础上构建行业发展趋势预测模型对行业发展态势进行感知,利用感知结果,结合用户缴费行为以及容量变化等数据,通过分类回归算法构建电费回收风险预警模型,客观量化用户电费回收的风险概率,识别存在电费回收风险的用户。最后通过实例验证,所提模型具有较好的预测能力。 |
| 英文摘要: |
| In recent years, influenced by reforms of electric power system, economic transformation and upgrading, increased environmental protection efforts, frequent extreme weather events,and coronavirus pandemic, customers face problems such as declining output and difficult sales that increases the electric charge recycling risk. A regression model based on industry development trend is proposed to predict the electric charge recycling risk. Firstly, the seasonal adjustment algorithm is used to extract the trend item of the historical industry electricity sales, and then the affecting factors are comprehensively and quantitatively analyzed. On this basis, a prediction model is built to perceive the industry development trend. Using the perception result, combined with data such as user’s payment behavior and capacity change, an early-warning model for the electric charge recycling risk is built. The model objectively quantifies the risk probability of user’s electric charge recycling. Finally, the example verification result shows that the model has good predictive ability. |
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