Electrica announces the completion of the AIAE (Artificial Intelligence for Active Energy Management) project, developed in partnership with Romanian startup Renergia and the Technical University of Cluj-Napoca. The project marks the launch of Romania’s first intelligent energy management system for buildings and introduces a new model for managing energy consumption focused on data, automation, and advanced analytics.

The platform processed more than 48 million datasets, while its development involved over 1,000,000 lines of code, highlighting the complexity and maturity of the solution. At the same time, the initiative also included a research and professional training component, involving three PhD students and four researchers under the age of 30, thus contributing to the development of a new generation of specialists in the fields of energy and artificial intelligence.

Alexandru Chiriță, CEO of Electrica: “Digitalization is not a parallel activity. It is critical infrastructure for the energy system. Through AIAE, we moved from concept to implementation and demonstrated that artificial intelligence can deliver concrete results in building operations. We are talking about the ability to understand energy consumption in detail and intervene where optimization is needed. This translates into control, predictability, and operational performance. The next step is scaling the solution across the entire Electrica Group.”

The AIAE platform operates as a virtual energy manager, capable of analyzing energy consumption in real time and transforming large volumes of data into operational decisions. The system identifies consumption patterns, detects deviations, and generates automated recommendations to optimize energy performance.

The solution is built on a multi-agent AI architecture and integrates data from multiple sources: electricity consumption, weather information, building technical characteristics, and operational context. This approach enables a comprehensive understanding of energy behavior and supports fast and efficient interventions.

The platform’s main functionalities include:

• detecting anomalies in energy consumption;
  • forecasting energy consumption and production;
  • identifying energy efficiency measures;
  • generating alerts for critical technical parameters;
  • optimizing self-consumption and reducing carbon emissions.

An important feature of the solution is its ability to “break down” total energy consumption and understand how each building system contributes to it, without requiring individual monitoring of every piece of equipment. The platform uses artificial intelligence models to identify consumption patterns and show where and how energy efficiency can be improved.

As a result of the project, concrete energy efficiency measures have already been implemented, such as automating operating schedules for certain systems and introducing shutdown policies for non-essential equipment outside working hours. These measures demonstrate the system’s ability to generate practical results with a direct impact on reducing consumption and increasing operational efficiency.