AleaSoft Energy Forecasting, July 4, 2025. Control centres are the brain of the energy system. They manage in real time the energy production and the grid balance in an increasingly complex, renewable and decentralised environment. To anticipate potential disruptions and make strategic decisions, they need accurate forecasts and advanced tools based on artificial intelligence to provide visibility, robustness and stability to the system.
At the heart of any modern energy system, whether electricity or gas, quietly pulsate the control centres. These strategic nodes, located in TSO (Transmission System Operators) such as Red Eléctrica in Spain, but also in large utilities, retailers and even IPP (Independent Power Producers) of a certain size, are responsible for managing energy production and grid balance in real time.
Every second, control centres make critical decisions based on a huge volume of data. They decide how much to produce, with which technology, at which grid node and at what time. They manage ramps, reservations, ancillary services and control deviations. To do this, they need accurate forecasts of multiple variables: renewable energy production, electricity demand, market prices, expected demands for ancillary services, weather conditions and much more. And they need it all in advance: from real time to several days ahead.
The importance of forecasts
In an increasingly renewable, decentralised and volatile electricity system, forecasts have become an essential tool. Many of the decisions made by the control centres depend on their quality and reliability. An erroneous forecast of solar or wind energy production, for example, can cause serious imbalances in the grid, the need to activate reserves or even jeopardise the stability of the system.
A forecast that comes true: heat wave, extreme prices and production restrictions
The recent heat wave that has affected a large part of Europe is a clear example of how forecasts are key for anticipation and system management. AleaSoft Energy Forecasting had already warned that, in these extreme conditions, not only could a significant increase in electricity demand be expected, but also cooling problems in thermal power plants, especially nuclear power plants and combined cycle gas turbines, which could lead to production restrictions.
In recent days, the forecasts have come true: on July 1 at 20:00 the electricity price exceeded €500/MWh in some European markets and France has been forced to reduce the production of a nuclear power plant. Also in Switzerland, the Beznau nuclear power plant had to shut down one of its reactors because of the high temperature of the river water used to cool them. If the high temperatures continue into the summer, there could be further constraints on thermal generation, which would further increase the pressure on control centres.
Such episodes highlight the need for robust forecasting tools capable of anticipating stressful situations and providing visibility in decision‑making. It also highlights the urgency for sector players, especially European control centres, to be prepared to manage increasingly demanding scenarios.
April 28: Did the forecasts fail?
The blackout of April 28 tested the resilience of the Spanish electricity system and its grid infrastructures. Although the official investigation has not yet concluded, all previous events, from production scheduling to the activation, or not, of strategic reserves, passed through the control centres.
The key question is: Did the forecasts fail? Was demand underestimated or renewable energy production overestimated? Were there coordination problems between different actors in the system? Were the forecasting models adequate for the extreme conditions of that day?
Beyond technology, coordination
What happened in April shows that the challenge is not only technical, but also organisational and related to coordination. A modern electricity grid needs control centres that share information in real time, use high‑quality forecasts, and make decisions in a coordinated manner. Digitalisation, artificial intelligence and the use of integrated forecasting platforms are essential to avoid errors and ensure system stability.
The strategic role of control centres
Control centres are the brain of the energy system. But like any brain, their effectiveness depends on the quality of the information they receive and the level of coordination among their various parts. Improving forecasting and strengthening joint decision‑making mechanisms is not an option, it is a critical necessity to avoid further blackouts and ensure the energy transition.
In this context, it is essential to have forecasting and decision support tools, especially those that integrate artificial intelligence for the analysis and processing of large volumes of data. Solutions such as those offered by AleaSoft Energy Forecasting allow control centres to anticipate system volatility, optimise resources and act with greater precision in complex and dynamic environments. The combination of high‑quality forecasts, digitalisation and artificial intelligence is key to building a more robust, resilient energy system that is ready for the challenges of decarbonisation.
AleaSoft Energy Forecasting’s analysis on the prospects for energy markets in Europe, storage and project financing
A new edition, the 57th, of the monthly webinars organised by AleaSoft Energy Forecasting will be held on Thursday, July 10. On this occasion, the analysis will focus on the recent evolution of European energy markets, the prospects for PPA contracts from the point of view of large consumers, as well as the development of energy storage in the current context. The new IDAE’s call for aid for storage projects will also be addressed.
The meeting will be attended by Pedro González, Director‑General of AEGE, who will offer the vision of the electro‑intensive sector, and Roger Font, Managing Director Project Finance Energy at Banco Sabadell, who will address the main challenges and opportunities in the storage and renewable energy project financing.
Source: AleaSoft Energy Forecasting.
