AleaSoft Energy Forecasting, March 26, 2026. Artificial Intelligence is ceasing to be merely an operational tool and is becoming a structural factor within the electricity system. Its impact is not limited to improving forecasting or grid management; it is also reshaping demand patterns, the integration of renewable energy and, consequently, investment and financing decisions in the energy sector.
A structural shift in the electricity system
Recent advances in weather forecasting using Artificial Intelligence, such as those developed by the European Centre for Medium‑Range Weather Forecasts (ECMWF), make it possible to generate multiple scenarios with greater accuracy and lower computational cost. However, their relevance goes beyond technical improvements.
In electricity systems with high penetration of renewable energy, the variability of generation is no longer purely an operational issue but becomes a structural factor influencing price formation and the profitability of investments.
The ability to anticipate renewable energy generation across different scenarios and time horizons enables more accurate modelling of the supply‑demand balance, a key element in increasingly complex markets.
Growth in electricity demand driven by Artificial Intelligence
At the same time, Artificial Intelligence is driving structural growth in electricity demand through data centers. According to the International Energy Agency (IEA), the electricity consumption of these centers could more than double before 2030.
This growth introduces new dynamics into the electricity system. The consumption of data processing centers is characterised by intensive, continuous and highly localised demand, which places greater pressure on transmission and distribution networks and increases competition for grid access in certain areas. This new demand places the accelerated need for new renewable capacity and energy storage capacity at the centre of the evolution of the electricity system.
In Europe, this phenomenon is already influencing investment decisions, project location and electricity infrastructure planning.
Storage as a strategic element: the role of AleaStorage
In this new environment, energy storage is no longer a complementary solution but a fundamental pillar of the electricity system. Increasing price volatility, renewable energy generation saturation during certain hours and the emergence of new flexibility services are positioning batteries as an asset capable of capturing value in the market. The value of storage does not lie solely in its operation, but in its ability to adapt to an increasingly dynamic electricity system and capture opportunities in different markets.
In this context, AleaStorage, the specialised energy storage division of AleaSoft Energy Forecasting, focuses on the strategic analysis of batteries and hybridisation projects, providing revenue estimation for stand‑alone batteries in energy and balancing services markets, analyses of hybridisation with renewable energy (solar photovoltaic and wind energy) to maximise revenues and reduce risks, assessment of capacity market revenues, and long‑term modelling of price and volatility scenarios.
From operation to investment: the real shift
The combination of greater renewable energy penetration, structural demand growth and the development of storage is transforming the electricity system into a more complex and uncertain environment. In this context, efficient operation remains relevant, but investment decisions are becoming the critical factor.
Aspects such as asset location, the configuration of hybrid projects, market exposure or revenue structure increasingly depend on the ability to anticipate the future behaviour of the electricity system.
Alea’s methodology: Artificial Intelligence applied to decision‑making
In this new environment, Artificial Intelligence is a technological tool that constitutes the basis for building models capable of anticipating the evolution of electricity markets. The methodology developed by AleaSoft, with more than 27 years of track record, is based on a hybrid approach combining Machine Learning techniques, recurrent neural networks, statistical and econometric models (Box‑Jenkins, SARIMA), multivariable regression and fundamental models based on the supply‑demand balance. This approach makes it possible to capture both non‑linear relationships and structural changes in the electricity system, providing coherent forecasts across the short, medium and long term.
The application of these models has a direct impact on multiple key decisions in the energy sector. For stand‑alone batteries, it enables revenue assessment in spot, intraday and balancing services markets. In renewable energy hybridisation projects, both solar photovoltaic and wind energy, it estimates revenue increases and risk reduction. For data centers, it analyses electricity costs and their reduction. These models are also applied to asset valuation and to support investment decisions by funds and investors. Energy retailers and large consumers use the forecasts for risk management and energy procurement strategies.
The role of AleaSoft as a strategic adviser
In this new energy sector landscape, AleaSoft Energy Forecasting positions itself as a strategic adviser in energy markets, providing price, demand and renewable energy generation forecasts, battery and hybridisation revenue analyses and support for the financing of renewable energy projects. All of this is supported by coherent and bankable models for decision‑making.
With more than 27 years of experience in applying Artificial Intelligence to the energy sector, the company has developed models capable of anticipating the structural evolution of the electricity system and supporting investment decisions across multiple European markets.
Artificial Intelligence as a decisive factor
The electricity system is entering a new phase characterised by greater complexity, volatility and investment needs. In this context, Artificial Intelligence not only improves the accuracy of forecasts, but also defines which players will be able to anticipate the market and make the best strategic decisions.
Source: AleaSoft Energy Forecasting