Cooling tower working condition prediction and consumption reduction method based on intelligent calculation

Cooling tower working condition prediction and consumption reduction method based on intelligent calculation

The invention discloses a cooling tower working condition prediction and consumption reduction method based on intelligent calculation. An environment temperature prediction model, an environment humidity prediction model, a working condition prediction model and a system energy consumption model ar...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: KOU TENGYUE, ZHAO JIEYING, ZHANG WENQIANG, ZHANG ZHOUYANG, YANG HO-TAEK, JIA LIFANG
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The invention discloses a cooling tower working condition prediction and consumption reduction method based on intelligent calculation. An environment temperature prediction model, an environment humidity prediction model, a working condition prediction model and a system energy consumption model are established and trained through machine learning; then, the trained environment temperature and humidity prediction model is used for predicting environment temperature and humidity changes in the future period, the trained working condition prediction model is used for predicting the working condition of the cooling tower based on the environment temperature and humidity changes in the future period, and the working demand of the cooling tower system in the future period is determined through the working condition and the environment temperature and humidity changes; and finally, establishing a corresponding objective function and an optimization model by taking the working demand and the energy consumption mini