Industrial research into new management and optimization models for self-consumption and energy storage using artificial intelligence

The project focuses on researching, based on the analysis of real-world data and using artificial intelligence techniques, an advanced management algorithm to optimize the charging and discharging of energy storage systems in industrial self-consumption, shared self-consumption and pumping installations, with the aim of improving their energy efficiency and economic profitability without requiring physical modifications to the installations.

Funding body:
Funding body Regional Ministry of Economy and Finance of the Government of Castilla y León, co-financed by the European Regional Development Fund, with the objective of “Building a more competitive and smarter Europe”.
Reference:
File: AEI/26/06
Funding:
€87,060.99
Dates:
-
Specific project objectives:
  • Analyze and structure real-world data on consumption, generation and storage operation in industrial self-consumption, shared self-consumption and pumping installations, identifying relevant behavioral patterns for energy and economic optimization.
  • Define representative energy profiles for each of the three study scenarios, with an appropriate time resolution, to provide a basis for the analysis and research of the management algorithm.
  • Research artificial intelligence-based energy storage management models capable of optimizing battery charging and discharging according to the actual behavior of the installations.
  • Evaluate the performance of the algorithm under different operating scenarios, analyzing its impact on the energy efficiency and economic profitability of the installations.
  • Fine-tune and validate the algorithm through an iterative trial-and-error process, incorporating the knowledge gained from each study scenario.
  • Develop technical criteria and recommendations to facilitate the future application of the results to similar installations and their transfer to the business sector.
Expected results:
  • Development of intelligent energy management models capable of analyzing generation, consumption and storage data to optimize the operation of self-consumption installations.
  • Optimization of the use of energy storage systems, improving battery charging and discharging strategies and their integration with photovoltaic generation.
  • Improved use of renewable energy, increasing self-consumption and reducing energy surpluses through coordinated management of generation, consumption and storage.
  • Application of artificial intelligence to anticipate system behavior, enabling more efficient energy management adapted to users' needs.
  • Development and validation of two proof-of-concepts, one linked to an energy community and another to a pumping installation, in order to test the performance of the solutions developed under real-world conditions.
  • Generation of knowledge and replicable solutions that can subsequently be applied to other self-consumption and energy storage installations.
Support

This action is carried out within the framework of the 2026 call for grants aimed at developing and improving the research and innovation capacities of the business sector through support for Innovative Business Associations (AAEEII) of the Regional Ministry of Economy and Finance of the Government of Castilla y León, co-financed by the European Regional Development Fund, with the objective of “Building a more competitive and smarter Europe”.

Socios