Ayesa predicts low-voltage network demand for i-DE using Artificial Intelligence

The company successfully meets the ‘Innovation Data Space Challenge’ launched by Iberdrola’s electricity distribution subsidiary, earning certification as a qualified provider capable of delivering advanced AI-based solutions.

The developed model enables more accurate energy supply adjustments and helps prevent overloads or service interruptions.

Ayesa, a global provider of technology and engineering services, has participated in Iberdrola’s open competition, the Innovation Data Space Challenge, aimed at developing Artificial Intelligence algorithms to forecast electricity demand in low-voltage networks. The company designed short- and medium-term demand prediction models using historical hourly load curve data, with the goal of estimating both demand and generation across more than 2,000 low-voltage lines.

Ayesa’s models were evaluated alongside those of other participants, and the company was recognized as one of only two to successfully meet all deliverables of the challenge. As a result, this initiative has allowed Ayesa to validate the effectiveness of its models against other competitors and achieve certification as a proven-capability provider for projects of this nature.

Managing power infrastructure is becoming increasingly complex, as electrical grids must handle not only traditional consumption and generation, but also fluctuations arising from factors such as the growing integration of renewable energy sources, which introduce significant uncertainty into the system. In this context, the availability of sophisticated demand forecasting models becomes a key factor for the efficient operation of the electrical grid.

These models allow for accurate forecasting of electricity demand trends, identifying consumption patterns in specific areas, accounting for seasonal factors, and helping to anticipate demand peaks or anomalies—crucial elements for adjusting energy supply more precisely and preventing overloads or service interruptions.

Moreover, medium- and long-term demand forecasting enables utility companies to make strategic decisions regarding network design, thereby improving the stability of the electrical system, optimizing energy usage, and reducing operational costs.