Industrial plants often face stringent agreements with utility providers that require precise short-term consumption predictions to avoid penalties. Managing energy consumption for different grids like electricity, water, and natural gas under varying production conditions poses significant challenges. Deviations from contractual thresholds can result in substantial financial penalties and inefficiencies, necessitating a robust solution for accurate demand forecasting and resource management.

Viridis Demand addresses these challenges by leveraging production scheduling to provide highly accurate and flexible energy consumption forecasts. The system offers different prediction horizons and granularities, utilizing planned production orders for short-term accuracy and production plans or sales orders for long-term predictions. This comprehensive approach ensures precise forecasting across various grids, helping plants stay within contractual limits and avoiding resources shortages or overloads.

By utilizing real-time production schedules, Viridis Demand provides forecasts that are directly aligned with current and upcoming production activities, leading to more accurate predictions compared to historical data that may not reflect current operational conditions.  Furthermore, the solution allows to detect potential deviations from contractual thresholds at an early stage, providing contextualized information for informed decision-making. By integrating advanced machine learning models and real-time data analysis, Viridis Demand ensures that steelmaking plants can efficiently manage their energy consumption,maintain compliance with utility agreements, avoid penalties – and ultimately drive operational efficiency which leads to cost savings.