The import of electricity at expensive tariffs is a problem usually coming from bad planning. Electric producers are challenged to timely detect deviations between produced and consumed electric energy in order to overcome their problems. Outdated data analysis prevents problem-solving models and fast reaction when a failure occurs.
Understanding the industry and its demands, we drafted the module that will provide predictive analytics with prompt anomaly detection. The result was a machine/deep learning system displaying the correlation between different parameters. Our product was Energy Consumption + Production Forecast (ECPF), an optimized AI model for predictive analytics based on an advanced correlation system.
ECPF provides advanced planning for electricity production and consumption and gives equipment time to failure prediction. It also contributes with near real-time monitoring.