Open AccessResearch on the Cause Analysis and Improvement Measures of Measurement Error Based on Model Forecast
Author(s) -
Ning Li,
Haiyang Liu,
Yongchao Wang,
Li Qiaoya
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1750/1/012005
Subject(s) - observational error , power (physics) , computer science , reliability engineering , econometrics , performance measurement , measure (data warehouse) , risk analysis (engineering) , data mining , economics , engineering , business , marketing , physics , quantum mechanics
The accuracy of power measurement affects the economic benefits and operating costs of power supply companies, and even affects corporate decision-making. Analyzing the causes of errors in measurement data and making improvements to reduce errors is of great significance to both power companies and users. The article analyzes the causes of power measurement errors, and proposes improvement measures to reduce the errors.