A Fuzzy Rough Set-based Method for Risk Assessment in Electricity Billing
Ruobing Wu, Ye Yuan, Zhenchao Zhang · 2025
With the increasingly fierce competition in the electricity market, customer demand for electricity is constantly increasing, and risks such as billing fraud, inconsistent data, and illegal access are constantly increasing. On the basis of previous research, this article intends to conduct a preliminary analysis of electricity consumption behavior, electricity tariff history, electricity consumption situation, etc. in the electricity market, uses fuzzy logic methods to quantify various risk factors and constructs a data set based on membership functions to characterize the membership degree of each data point at different risk levels. Then, this article uses rough set theory to analyze the data in fuzzy sets and defines upper and lower approximation sets to determine whether each data point belongs to a certain type of risk. This indicator has increased from 73% to 89%. The research results will provide new ideas for solving large-scale uncertainty and fuzzy information problems, and improving the accuracy and efficiency of power grid risk management.