| 江明,邹云峰,徐超,倪巍伟.基于行业用电模式的企业电费逾期风险预测[J].电力需求侧管理,2019,21(5):79-83 |
| 基于行业用电模式的企业电费逾期风险预测 |
| Research on risk screening model for tariff recovery of high voltage power customers by integrating social data |
| 投稿时间：2019-06-05 修订日期：2019-06-28 |
| DOI：DOI:10.3969/j.issn.1009-1831.2019.05.016 |
| 中文关键词: DBSCAN 用电模式 风险预测 等级标注 |
| 英文关键词: DBSCAN power pattern risk prediction risk level |
| 基金项目:国家自然科学基金项目（61772131） |
|
| 摘要点击次数: 1756 |
| 全文下载次数: 847 |
| 中文摘要: |
| 我国经济进入新常态，传统产业面临诸多挑战，企业客户电费回收风险不断加大，对企业用电逾期风险进行预测，最大限度地减小影响公司经营的被动风险变得日益迫切。目前电费回收逾期风险管控手段主要依靠企业历史欠费情况进行风险判断，缺乏对用户用电量趋势及缴费历史的深入挖掘，导致企业逾期风险判断准确性与及时性存在不足。针对上述问题，基于企业历史用电与逾期数据记录，聚焦行业用电典型模式挖掘，提出基于聚类的行业典型用电模式库构建方法。在此基础上，采用k 近邻的思想，定义模式距离度量函数，引入风险等级概念，提出一种基于行业用电模式的企业电费逾期风险预测模型PEORPM，实现具有自演化能力的企业偏离度4级逾期风险等级标注以及风险预测。理论分析和实验结果验证了所提方法的有效性。 |
| 英文摘要: |
| China’s economy has entered a new normal, supply side reform and the battle for environmental protection have continued to advance, international trade unilateralism has risen,traditional industries are facing many challenges, and the risk of electricity tariff recovery for enterprise customers is increasing.Therefore, predicting the overdue risk of power consumption of enterprises and minimizing the impact on the company's operations are becoming more and more urgent. At present, overdue risk management and control methods can only rely on the historical arrears of enterprises to conduct risk judgments, and lack of deep exploration of user power consumption trends and payment historyleads to the lack of accuracy and timeliness of enterprise overdue risk judgment. To solve the above problems, from the single perspective of enterprise electricity data, based on DBSCAN clustering algorithm,constructing the typical electricity consumption mode of the industry, and adopting the idea of k nearest neighbor, defining the pattern distance measurement function, introducing the concept of risk level, and proposing a power pattern based electricity overdue risk prediction model for enterprises to realize the self evolving electrical deviation based on overdue risk level with degree 4 and risk prediction. Theoretical analysis and experimental results verify the effectiveness of the proposed method. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |