How a Belgian National Grid Operator Uses Data & AI to Improve Electricity Load Balancing and Reliability

Background

Our client operates Belgium’s national high-voltage electricity grid, managing all infrastructure from 150 kV to 380 kV. As the backbone of cross-border energy flow, they play a critical role in transporting power across Belgium and connecting France—Europe’s largest electricity exporter—to major markets in Northern Europe. Their network ensures secure, reliable, and efficient electricity transmission for millions of consumers and businesses.

Challenge

One of the most critical challenges in operating a national electricity grid is maintaining real-time balance between power supply and demand—across consumers, producers, and increasingly, prosumers. When load distribution is not continuously optimised, the grid faces technical instability, increased risk of outages, and higher operational costs. Inefficient balancing not only strains infrastructure but also drives significant economic inefficiencies, making it essential for the operator to improve forecasting, monitoring, and decision-making across the network.

Approach

To address the load-balancing challenge, Keyrus deployed a structured, data-driven methodology. The first step involved identifying, assessing, and integrating all relevant operational data sources into a unified analytical foundation. Using historical data from a selected reference year, our team normalised load profiles for every network node, enabling accurate comparison and pattern detection across the grid. We then designed and built descriptive and predictive analytical models to uncover trends, pinpoint anomalies, and simulate future load scenarios. Finally, we implemented a robust normalisation and forecasting solution that delivers real-time, actionable insights—empowering grid operators to anticipate network stress, prevent potential disruptions, and optimise load distribution with confidence.

Key results

Gained a clear, data-backed understanding of the grid’s load-balancing drivers through a series of deep-dive workshops with business stakeholders and subject-matter experts—aligning operational knowledge with analytical insights to guide the optimisation strategy.

Successfully decomposed the overall power load signal into clear, measurable drivers, including time-based patterns and weather conditions — enabling more accurate insights and stronger predictive modelling.

Delivered a more reliable and resilient load-balancing framework, helping ensure a stable, uninterrupted electricity supply for the entire population.

Benefits

The solution enables faster, more accurate correction of load imbalances across the energy network, reducing the risk of outages and operational inefficiencies. By delivering high-resolution forecasting insights at the sub-station level, the organisation can anticipate demand shifts earlier, optimise grid performance proactively, and ensure a stable, reliable electricity supply for the entire population.