The evaluation of advanced AI-based algorithms in real time plays a key role in improving the performance, stability, and control of smart grids, hybrid energy storage systems, electrical systems, motors, and power converters. This service enables companies to validate and optimise their control strategies under realistic operating conditions, reducing risks before deployment.
This activity assesses the stability, efficiency, and robustness of advanced algorithms using artificial intelligence techniques, including machine learning and predictive control approaches. These algorithms are applied to optimise energy management, enhance system reliability, and improve the integration of renewable energy sources and storage systems.
The advanced algorithms are tested using a predefined set of measurable indicators tailored to energy systems, such as response time, stability margins, energy efficiency, power quality, and system reliability. The evaluation is carried out under realistic scenarios emulated in the Zero-Emission Lab grid, which integrates renewable energy sources, hybrid storage systems, and representative loads from buildings and industrial plants.
The testing environment combines digital twins of energy processes with real hardware, including electronic loads and power systems, to reproduce diverse operational conditions. This allows the validation of algorithms in scenarios such as fluctuating renewable generation, variable demand, and grid disturbances.
The service follows a structured process:
The output report provides detailed and quantified insights into algorithm performance, including metrics such as efficiency improvements, reduction in response times, enhanced stability, and optimisation of energy usage. Where applicable, results can demonstrate measurable improvements in system performance compared to baseline strategies.
To carry out the evaluation, customers are expected to provide access to their control algorithms, system models or interfaces (e.g. control logic, communication protocols), and relevant operational data. ITA provides the testing infrastructure, including the Zero-Emission Lab, as well as expertise in AI, power systems, and hybrid energy storage technologies.
This service is designed for:
Typical applications include optimisation of hybrid energy storage management, real-time control of renewable energy integration, and performance improvement of power electronics systems.
To start a project, companies can contact ITA to define their use case and technical requirements. This initial step includes a feasibility assessment and KPI definition, followed by a tailored proposal, testing phase, and delivery of results.