Real-World Examples Of The Role Of Big Data And Machine Intelligence in Optimizing Energy Systems, TAPPICon25

The integration of big data and machine intelligence (MI) in steam header controls and power systems can increase energy efficiency by optimizing consumption, increasing sustainability by reducing emissions, and reducing downtime with greater operating stability. This paper explores the application of these technologies with real-world examples, using data to demonstrate their effectiveness. By harnessing large-scale datasets and advanced methods, like fuzzy logic, a framework has been created that allows predictive analytics, dynamic load balancing, and real time optimization of energy resources.

A few examples will be presented to illustrate how a data driven steam header control and load shed management can benefit a mill. The considerations for the case study will be discussed including venting, contractual terms, and other limitations. The results show significant improvements in energy use patterns, cost savings, and reduced emissions, highlighting the transformative potential of data-driven approaches to energy management.

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