Design and Implementation of a Big Data-Supported Power Energy Information Collection System
The article designs and implements a big data-supported power and energy information collection system to improve the monitoring,analysis and management of power systems.Through the architecture of data acquisition layer,data transmission layer,data processing layer and application layer,the system is able to comprehensively and real-time monitor various key points of the power system,including power loads,renewable energy production and equipment operation status.In the data processing layer,the isolated forest algorithm is introduced to ensure the quality of collected power and energy information while realizing efficient data cleaning and anomaly detection.The system can provide power system managers with more comprehensive,real-time and reliable power energy information support,thus improving decision-making efficiency and system stability.
power systembig datainformation collectionreal-time analysis
NETL
NSTL
万方数据
