Peak-load energy management
Avoid peak loads and reduce energy costs.
Peak-load management identifies critical periods from consumption curves and controls flexible loads, reducing expensive peak-load charges.
- Cost reduction
- Better sustainability balance
- Higher efficiency
peak loads
energy costs
payback
energy efficiency
Calculated from reduced peak-load charges and lower overall consumption.
- 01
Data integration
Consolidate data from ERP, MES and further sources for Peak-load energy management.
- 02
Data quality
Clean, harmonise and validate data for plausibility.
- 03
Model development
Train and validate the Peak-load energy management model on historical data.
- 04
Pilot
Pilot Peak-load energy management in one area and collect feedback.
- 05
Rollout
Scale the solution and integrate it into operational processes.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
Energy consumption
Electricity, gas, water and steam per area.
Sensor data
Real-time IoT and process sensors.
MES data
Production orders, feedback and machine data.
Weather data
Outside temperature, humidity and weather alerts.
ERP data
Master and transaction data from ERP.
Historian data
Time series from the process control level.
Sustainability lead
Captures and communicates sustainability metrics.
Production manager
Uses insights directly in daily operations.
Controlling
Quantifies effects and supports budgeting.
IT
Builds on a scalable and secure data infrastructure.
Cost reduction
Better sustainability balance
Higher efficiency
Better planning
Lower risk
With a solid data foundation this use case gets faster, cheaper and far more stable.
Central data platform
Real-time data integration
Scalable analytics pipelines
Reusable data products
Energy optimisation
Process data enables demand-based energy control.
OEE monitoring
Availability data complements process metrics.
Process parameter optimisation
Energy and process data enable continuous process optimisation.