Model: DU-2/MKIII
Origin: USA
Warranty: One year

Marketable location: Nationwide

Application: Various spare parts such as branded PLCs, DCS modules, cards, drivers, etc

If there is a certain relationship between power data on the timeline, then grey analysis can be used to predict and analyze power data. In data mining of power dispatching systems, grey analysis method has been widely used. Even if the data integrity is not strong, grey analysis method can still analyze it. However, compared with fuzzy analysis method, this method cannot fully utilize the big data function. In power dispatching, short-term power load forecasting is an important task. Taking a power dispatching automation system in China that applies grey analysis method as an example, the system can be divided into data processing module, load forecasting module, and data display module, and its system structure

In the data processing module, raw load data, forecast data, and meteorological data can be imported. The forecast data is in text format, and the system mainly handles two types of abnormal data: data missing and data jumping. The data cleaning module can ensure the running speed of system programs, and short-term load forecasting data is maintained within 5 years. Proper cleaning of historical data can ensure query efficiency. In the load forecasting module, the main approach is to combine the situation of the city and use ordinary grey models, multivariate grey models, and manual experience models for load forecasting. The ordinary grey model is suitable for predicting ordinary dates, while the multivariate grey model predicts based on meteorological data. The manual experience model predicts holidays based on relevant data from the power bureau< br />6ES5925-3SA11 SIEMENS Simatic S5 6ES59253SA11 CPU 925

PM550-412 TEXAS INSTRUMENTS PM550 PM550412 TCAM

7MT 200 TEXAS INSTRUMENTS 7MT 7MT200 TEXAS INSTRUMENT

6ES7963-1AA00-0​AA0, in box sealed, SIMATIC S7 PLC’

DOM51, in box, PHILIPS P8 compactline DOM51