Products M 5
Energy source selection and efficient energy management
The proposed energy distribution solution is designed to supply the required amount of energy from available sources. The method enables real-time energy source selection, ensuring an effective balance between supply and demand.
Objective
A real-time, data-driven intelligent system that selects optimal energy sources to balance production and demand with maximum efficiency and reliability.
Key features
Dynamic load distribution
The module continuously selects the optimal combination of energy sources (e.g., boilers) in real time based on current and forecasted energy demand.
Continuous learning
Improves over time by learning from historical performance data, enabling self-tuning and continuous optimization accuracy enhancement.
Scalability
Supports integration from small systems with 2-3 sources to large industrial networks.
Performance monitoring
Continuous tracking of key performance indicators (KPIs).
User-friendly interface
Provides intuitive dashboards with real-time process visualization and scenario analysis capabilities.
Application Areas
01
Intelligent boiler source selection for steam generation
Optimization of superheated steam production across multiple boilers. Through intelligent control based on real-time consumption data, the software ensures efficient energy utilization while respecting operational constraints of each boiler.
Expected results
5–10% increase in efficiency per individual source
Achieved through optimal load distribution and operation near each boiler’s best performance point.
Up to 10% reduction in fuel costs
By minimizing inefficient boiler operation.
Enhanced stability and reliability
Steam/energy supply stability ensured through automatic load redistribution in case of source unavailability.
Examples of use
Intelligent boiler optimization
The «Energy source selection and efficient energy management» module helps balance steam generation and consumption across multiple boilers. It analyzes real-time and forecasted demand, as well as the operational characteristics of each boiler, to determine the most efficient operating configuration. When forecasted demand exceeds available capacity, it schedules the activation of an additional boiler while accounting for startup delay.