This article focuses on the abnormal detection method of electric meter load curve based on intelligent algorithms

explains the significance of abnormal detection of electric meter load curve

and points out the limitations of traditional detection methods. Then

the application principle and advantages of a variety of intelligent algorithms in the abnormal detection of electric meter load curves are introduced in detail. The results show that the detection method based on intelligent algorithms is significantly superior to traditional methods in terms of accuracy

recall rate and other indicators

which can effectively improve the efficiency and reliability of abnormal detection of electric meter load curve

and provide a strong guarantee for the stable operation of the power system. In the daily operation of the power system

the accurate monitoring and analysis of the meter load curve plays a vital role in ensuring the quality of power supply

preventing equipment failures and optimizing the allocation of power resources. However

traditional detection methods often rely on manual inspection or simple threshold judgment

which is not only inefficient

but also difficult to deal with complex and changing power load situations

which is easy to cause leakage and false detection. The abnormal detection method of electric meter load curve based on intelligent algorithm proposed in this paper realizes real-time and accurate monitoring of electric meter load curve through the introduction of advanced machine learning and deep learning technology

effectively overcomes the limitations of traditional methods

and provides new ideas and means for the intelligent management of the power system.