利用人工智能优化冷水机组管理

F. Al Qahtani, M. Muaafa
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引用次数: 0

摘要

在一个典型的设施中,冷冻厂(又名:区域供冷)占总能耗的50%。从区域供冷厂的中央控制及监察系统收集有关冷水机、冷却塔及水泵运作的实时数据,有助优化系统的运作,并找出节省能源的机会。这是由人工智能的机器学习能力实现的。对冷水机组各部件的特性和运行日志进行大数据分析,提出系统优化建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chiller Plant Management Optimization By Artificial Intelligence
Chiller plants (aka: district cooling) account for up to 50% of total energy consumption in a typical facility. Real-time data collected from the central control and monitoring system of a district cooling plant on the operation of chillers, cooling towers, water pumps would help optimize the operation of the system and identify energy saving opportunities. This is made possible by the machine learning capability of AI. It would conduct big data analysis on the characteristics and operation logs of different components of the chiller plant and would then make recommendations for system optimization.
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