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Enea to use deep predictive AI for grid management

Polish power company Enea announced on Thursday (29 February) that it is testing a pilot project on using deep predictive AI models to improve the management of the distribution network load.

The main element of the project involves the application of three proprietary algorithms developed by Polish software company Affexy, based on deep learning techniques, Enea said in a press release.

Another modern mechanism used in the project enables the created models to focus on the most relevant data. As a result, experiences gained in one task are utilised to enhance another, Enea said. This kind of system “learning” is expected to increase the precision of forecasts and their better adjustment to dynamically changing network conditions.

The AI pilot is said to be the company’s response to the need to adopt Poland’s power networking amid THE increasing capacity of renewables and regulations regarding energy efficiency.

The project focuses on three areas, with data analysis being the primary one. It enables understanding network loads and identifying factors influencing their variability. The second area is the processing of acquired data, preparing them for efficient analysis by advanced artificial intelligence (AI) models. The project’s activities culminate in a report and recommendations, drawing conclusions from the analysis and suggesting actions to optimise the data collection process and forecast quality.

The project aims to, above all, provide a better understanding of network loads and the patterns guiding them, critical for effective network management.

The project also enables the use of advanced AI techniques, piloting, and testing the effectiveness of innovative algorithms in real conditions, Enea noted. The results and experiences gained in the project would be applied when implementing a full-scale system, providing initial information on its effectiveness and areas requiring further development.

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