AI-Energy
The application of Artificial Intelligence (AI) in the energy sector is transforming the way electricity networks are managed, improving: the efficiency, reliability and safety of infrastructure. This is particularly evident in MV/LV electrical substations and smart meters.
HV/MV and MV/LV Electrical Substations and Stations
HV/MV and MV/LV stations and substations play a crucial role in the distribution of electricity for industrial and residential use.
AI is used to optimize the operation of these stations/substations connected to the territorial distribution network:
Monitoring and Predictive Maintenance
AI can analyze data from sensors installed in substations to monitor the health of components (such as transformers, switches and other devices).
Machine learning algorithms can predict impending failures, allowing maintenance interventions before serious problems occur, reducing downtime and operating costs.
Optimizing Network Management
AI can help balance the load between different parts of the electricity network, preventing overloads and improving the efficiency of energy distribution.
This is particularly useful for managing fluctuations in energy demand and the integration of renewable energy sources, which can be intermittent.
Security and Protection
Advanced AI systems can detect anomalous behavior or cyber attacks on stations/substations, improving security against both physical and digital threats.
AI can analyze data patterns in real time and identify potential threats, triggering appropriate protection measures.
Smart Meters
Smart meters are devices that record detailed energy consumption and communicate it in real time to energy suppliers.
AI is being used in a variety of ways to improve the efficiency and use of these devices:
Consumption Data Analysis
AI can analyze data collected by smart meters to identify energy consumption patterns and provide personalized recommendations to users on how to reduce energy consumption and costs. It can also help suppliers better understand energy demand, improving supply management.
Fraud Detection
AI algorithms can identify anomalies in consumption data that could indicate attempts to tamper with meters or commit fraud, allowing for rapid interventions and preventing economic losses.
Integration with Renewable Energy
AI can help manage the intermittency of renewable sources (such as solar and wind) by optimizing the use of energy produced and stored in battery systems, based on consumption and production forecasts.
Dynamic Pricing
Using AI, providers can implement dynamic pricing models that vary based on time of day and demand, incentivizing consumers to use energy during periods of low demand, reducing the load on the grid.