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This video focuses on energy forecasting, particularly valuable for process industry customers aiming to manage and reduce energy costs. By integrating internal production forecasts from a historian with real-time weather data obtained from an external service, Crosser facilitates hourly updates to predict energy needs for the next 48 hours. Implemented through a Python module, this forecasting algorithm generates precise forecasts used by external energy providers, such as a pulp and paper mill, to optimize energy consumption, thereby minimizing unplanned energy expenses and enhancing cost-efficiency in production operations.
Watch the full video here to gain practical insights on implementations and benefits: info.crosser.i...