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Data & AI Use Cases in Operations

Optimising dynamic electricity prices with AI – intelligent pricing explained simply

Use Case Use Case Family: Automation, Predictive Analytics & Forecasting
Business Domain Business Domain: R&D
Process Processes: Dynamic pricing in energy management
Challenge:

Adjusting electricity prices to real-time conditions like grid load and generation capacity is difficult without data-based systems. Lack of transparency and delayed pricing responses result in inefficiencies and increased costs. Additionally, the opportunity to influence consumer behavior is often missed.

Solution:

A forecasting system based on real-time data continuously analyzes grid and consumption patterns to dynamically adjust electricity prices. This enables immediate response to demand fluctuations and supply bottlenecks while encouraging cost- and eco-conscious usage behavior.

Benefits:

  • Improved utilization of generation and grid infrastructure

  • Reduced peak loads and avoided grid congestion

  • Cost savings for both energy providers and end users

  • Promotes more sustainable energy consumption behaviors

Target Group Target Group:
Energy providers sustainability managers grid operators
Potential Industries Potential Industries:
Energy supply smart grids environmental tech
Limited Risk
Limited Risk systems Art. 50
with Transparency Obligations according Art. 50 EU AI Act
Disclaimer The information provided regarding the risk assessment is without guarantee. The complete classification of a use case according to the EU AI Act depends on numerous regulatory and company-specific factors. Therefore, the risk assessment is always case-specific. The risk assessment logic of Casebase is used for this purpose.