摘要
针对电力市场需求,构建了一种用电检查风险评估模型,并进行了实证分析。该模型融合了大数据分析、机器学习等技术,全面评估了用户特征、用电行为和设备状况等多维度数据,以提升用电风险评估的精确度。实证结果显示,该模型在预测电力用户用电风险方面具有较高的有效性和准确性,为电力企业优化用电检查策略、提高供电可靠性提供了重要参考。强调了用户用电行为差异性和设备状况对风险评估的影响,并提出了相应的管理建议,以促进电力市场的安全稳定运行。
This study constructs a risk assessment model for electricity inspection based on the demand of the electricity market and conducts empirical analysis.The model integrates technologies such as big data analysis and machine learning to comprehensively evaluate multidimensional data such as user characteristics,electricity consumption behavior,and equipment conditions,in order to improve the accuracy of electricity risk assessment.The empirical results show that the model has high effectiveness and accuracy in predicting electricity consumption risks of power users,providing important reference for power enterprises to optimize electricity inspection strategies and improve power supply reliability.The study emphasizes the impact of differences in user electricity usage behavior and equipment conditions on risk assessment,and proposes corresponding management recommendations to promote the safe and stable operation of the electricity market.
作者
王振刚
WANG Zhengang(State Grid Yixing Power Supply Company,Yixing 214200,China)
出处
《电工技术》
2025年第S1期331-333,共3页
Electric Engineering
关键词
电力市场
用电检查
风险评估
需求侧管理
实证分析
electricity market
electricity inspection
risk assessment
demand side management
empirical analysis
