Industry
Energy
Work area
Load Forecasting & Energy Optimization
Optional
MVP in 3 months (for consumption and generation data)
Project duration
6–9 months
Initial Situation
Energy suppliers and grid operators are facing the challenge of having to increasingly control generation, consumption, and grid utilization in real time.
Volatile feed-in from renewable energies, weather-dependent consumption patterns, and growing regulatory requirements make precise planning difficult.
Traditional forecasting methods based on average values react too slowly to short-term changes and often lead to expensive control energy purchases or inefficiencies in procurement.
Objective
The goal is to implement an AI-supported load forecasting platform that uses predictive analytics to identify fluctuations in energy demand at an early stage, derive recommendations for action, and thus improve grid stability, security of supply, and economic efficiency.
Description of the Use Case
The solution uses modern AI and machine learning models to accurately predict energy consumption and generation patterns. It takes into account internal and external factors such as weather, holidays, industrial production, and price developments.
The platform helps energy suppliers dynamically adapt their production, storage, and procurement strategies to current demand and actively manage peak loads.
Key Components of the Project:
- Data collection & integration: Establishment of a central data platform for consolidating historical consumption data, real-time measurements, and external factors (e.g., weather data).
- AI/ML modeling: Development and training of forecasting models for detecting seasonal and short-term load fluctuations.
- Optimization logic: Automatic derivation of action strategies for procurement, storage operation, and grid feed-in.
- System integration: Connection to SCADA systems, IoT devices, smart meters, and energy trading platforms.
- Cloud architecture: Scalable platform with high availability and data security.
Value Proposition
- Increased planning reliability: Accurate forecasts enable demand-driven production planning.
- Cost reduction: Minimization of expensive reorders and opportunity costs through optimized deployment plans.
- Sustainability: Better integration of renewable energies reduces CO₂ emissions.
- Grid stability: Early detection of peak loads prevents overloads.
- Competitive advantage: Faster response to market and weather changes.
Required Services
- Project management & consulting: Control, requirements analysis, stakeholder management.
- Data platform & cloud infrastructure: Setting up a scalable data hub, connecting real-time and historical sources.
- AI/ML modeling: Development, training, and validation of prediction models.
- Interfaces & integration: Technical connection to IoT sensors, smart meters, and network control systems.
- Change management & training: Integration into operational processes and training of specialist departments.
Benefits
In short:
C4 Energy enables energy suppliers and grid operators to manage grids and procurement processes more precisely and sustainably using AI-based forecasts.
The result: lower costs, stable grids, and more efficient integration of renewable energies.
Future-proofing your company
