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^{GRID BALANCING}
The algorithmic grid

How flexibility tools and AI can help balance a stressed system

^{GRID BALANCING}

The algorithmic grid: how flexibility tools and AI can help balance a stressed system

For more than a century, power systems have run on one unforgiving rule: at every moment, the amount of electricity being generated must match the amount being used.

Historically, large dispatchable power stations, centralized networks and control rooms centered on frequency and voltage stability kept that balance. The energy transition is changing all that. Electrification, variable renewables, distributed energy resources, new consumption patterns and volatile markets are creating a faster, more uncertain and fragmented system.

The IEA estimates that meeting climate targets will require adding or replacing about 80 million kilometers of electricity networks by 2040 – roughly the entire global grid today – while investment needs to rise sharply. But physical infrastructure alone cannot solve such a complex problem. That’s why today’s grid is no longer balanced only by steel and copper, but by algorithms, data and distributed flexibility.

Who operates the grid is changing too: transmission system operators (TSOs) and distribution system operators (DSOs) used to coordinate this between them. Now, grid system operators are emerging, who balance the whole distributed system in real time and coordinate markets.

This shift reflects a deeper change in what balancing requires. The central question has changed from “How do we react to imbalance?” to “How do we anticipate and prevent problems before they happen, at the lowest cost to the system?”

Across advanced markets, demand is already growing faster than grids can connect and respond. The future balancing challenge is therefore also a speed challenge: the grid must plan, connect and operate faster than demand is growing.

Today’s grid is no longer balanced only by steel and copper, but by algorithms, data and distributed flexibility."

Navigating a complex system

The old model was straightforward: large, centralized and largely dispatchable power stations served predictable, stable demand. Reserve margins, hydro and thermal plants, interconnections and balancing mechanisms fixed any deviations. That model is being displaced by weather-dependent generation, two-way flows and consumers who also generate, store or shift energy.

Three forces are reshaping what balance looks like – and requires – today:

1. Fragmented supply

Millions of solar installations, wind farms, batteries, energy communities and industrial assets are already generating power. The IEA expects this renewable capacity to grow by more than 5,500 GW between 2024 and 2030, with solar and wind representing about 95% of that growth. By 2030, four in 10 new solar additions could be distributed – moving part of the balancing problem on to networks designed for one-way delivery.

What’s more, unlike synchronous machines in large power plants, electronics-based generation like solar and wind don’t naturally resist sudden changes in frequency. So advanced hardware and software are increasingly important for keeping the grid stable.

These changes have reduced the amount of direct control that grid system operators have over the resources that could support balance. TSOs are running their assets closer to dynamic limits. DSOs need to get much better at seeing what’s happening on their networks, as well as at forecasting, managing voltage and coordinating flexible assets. Meanwhile, decarbonization, permitting, economics, drought and climate variability are constraining traditional sources of flexibility – thermal and hydro energy. Curtailment, co-located storage, flexible networks and responsive demand must fill the gap. Put simply: as production becomes less dispatchable, demand must become more flexible.

As production becomes less dispatchable, demand must become more flexible."

2. Dynamic demand

Demand is no longer a stable, predictable curve. Electric vehicles, heat pumps, data centers, electrolyzers, industrial electrification, cooling and smart buildings are creating large, localized and weather-sensitive loads. Data centers alone consumed around 485 TWh in 2025 and are expected to almost double their consumption to 950 TWh by 2030. The global EV fleet could reach 250 million vehicles by 2030, while the IEA’s net-zero pathway depends on 600 million heat pumps being installed globally.

These flexible assets also represent a huge pool of potential flexibility. To unleash their value, they must be bundled together, signed up to contracts, accurately measured, predictable and controllable.

Achieving this requires interoperable platforms, market access, trusted baselines, attractive payment and consumer trust. But while advanced markets optimize flexibility, emerging markets are often still building the foundations on which flexibility will depend.

3. Market chaos

Negative electricity prices, grid congestion and rising emergency management costs aren’t anomalies. They’re signs that there isn’t enough flexibility, storage or coordination in the system. When renewable output is high and demand can't absorb it, prices fall – sometimes to below zero. When output drops or demand spikes, prices rise.

In response to this volatility, European platforms such as PICASSO and TERRE are starting to pool balancing resources across borders. But progress is slow. In the meantime, a well-designed market does more than price electricity. It considers how quickly an asset can respond, where it’s located and how reliably it can deliver.

Together, these three forces mean that keeping the grid balanced is no longer only the operator’s job. It involves coordinating across the whole system.

While advanced markets optimize flexibility, emerging markets are often still building the foundations on which flexibility will depend."

Keeping the grid balanced is no longer only the operator’s job. It requires coordination across the whole system."

The flexibility arsenal

There’s no silver bullet for reaching this goal. Instead, the grid will need a portfolio of complementary approaches, chosen based on how fast they can respond, where they are and what the system needs at any given moment. Flexibility is becoming both a set of physical technologies and a set of financial instruments and market mechanisms, all working together.

The main approaches are:

Storage: the system shock absorber
Lithium-ion batteries can respond very quickly, absorb solar power, relieve local congestion, and charge and discharge in response to supply and demand. Pumped hydro provides large-scale storage daily or weekly, but it’s limited by geography and long build times. Thermal storage shifts heating and cooling loads. Hydrogen and synthetic fuels could eventually cover prolonged or seasonal periods of low renewable output, though they’re less efficient overall. Smart EV charging lets car batteries draw power at times that suit the grid, while vehicle-to-grid may eventually allow them to feed it back when it’s needed (subject to business models, technical standards and customer acceptance).
Demand response: the least visible resource
Getting consumers to shift or reduce consumption when the grid needs it can reduce peaks, absorb surplus renewable power, avoid congestion and lower the amount of reserve needed. All without building new infrastructure. Industrial sites, buildings, EV fleets and homes can all participate, but industrializing this approach requires certification, aggregation, measurement, activation and settlement. Platforms like Equigy, Piclo and NODES show that standardized ways of procuring local flexibility have begun to emerge. Virtual power plants can also bundle large numbers of distributed assets into single, reliable market resources.
Enhanced grids: doing more with
existing assets
Dynamic line rating adjusts how much power transmission lines carry based on real-time weather conditions. Phasor Measurement Units (PMUs) and high-frequency sensors give operators a clearer picture of stability across the network. Grid-forming converters help maintain stability as electronics-based generation grows. These technologies don't replace physical investment. They help prioritize it, defer it when flexibility is more efficient and get the most out of assets.

To sum up: storage absorbs volatility. AI anticipates it. Markets reveal its value.

Storage absorbs volatility. AI anticipates it. Markets reveal its value."

From ‘forecast and react’ to ‘predict and prevent’: The role of AI and tech in grid balancing

The tools and approaches we’ve described provide the foundations of flexibility. But balancing the grid across distributed assets, markets and ever-changing conditions is already moving beyond human capability alone.

If, as ENTSO-E predicts, European flexibility needs double between 2025 and 2033, operators will need to forecast deviations, anticipate congestion, model load behavior and optimize assets across local and wholesale markets. AI will be essential, but it won’t replace operators or electrical engineers. It will expand what they can do by processing enormous volumes of data simultaneously: weather forecasts, market prices, asset conditions, customer behavior and physical network constraints.

Control rooms will become data-intensive environments, supported by probabilistic alerts – which predict the likelihood of congestion within a certain time span – automated recommendations and digital simulations. Supervised automation is a realistic goal: AI detects, predicts and recommends. Human operators validate, prioritize and intervene when conditions move outside normal parameters.

AI’s main uses include:

forecasting renewable output and demand in the very short term
optimizing assets across storage, demand response and interconnections
detecting anomalies and predicting risks before they happen
activating assets while being aware of constraints
simulating extreme scenarios and stress-testing plans in real time through digital twins
giving operators visibility and control over distributed assets through ADMS and DERMS platforms

The operating loop making this happen is easy to describe but hard to scale:

Sense what’s happening across the system and predict what’s coming
Optimize the use of flexible assets, within network constraints
Act automatically or semi-automatically under human supervision
Learn from the results and improve

As a result, the future grid won’t only be reinforced. It’ll be predicted, optimized
and automated.

The future grid won’t only be reinforced. It’ll be predicted, optimized and automated."

Modern grid balancing: who needs to do what?

Grid system operators (in the US, ISOs or RTOs): Align detailed load forecasting, large-load connections, capacity planning and real-time reliability tools. Accelerate the deployment of multi-duration storage. Deploy advanced forecasting, multi-asset optimization and anomaly detection and track the results in lower balancing costs, fewer outages and faster connection of new loads.

TSOs: Renew aging assets and build climate resilience into infrastructure. Deploy Dynamic Line Rating, digital twins and PMUs to get more out of existing infrastructure and simulate stress scenarios before they occur. Strengthen coordination with system operators and DSOs by sharing constraints and operational data across time horizons.

DSOs: Get a much clearer view of what's happening at a local level through ADMS, DERMS and low-voltage sensors. Open local flexibility markets, standardize products and make sure assets are fairly paid for how quickly they respond, where they are and how reliably they deliver. Ensure flexible connections and coordinate with the operators above in the chain. Local flexibility won't replace the need for network reinforcement, but it can target investment more precisely and make better use of what already exists.

Aggregators: Bundle thousands of small assets into tradeable portfolios that are dependable and measurable. Increasingly, value depends not just on owning an asset, but on being able to activate it at the right time, in the right place and in the right market. Producers and consumers can support this by combining generation, storage, demand response and smarter tariffs.

Flexibility is the new capacity

As the energy transition gathers pace, power system security will no longer depend only on how much generation capacity is installed, but on the ability to forecast, shift, store and orchestrate electricity across the system. Storage is the shock absorber. Demand is a resource. Digital platforms are the coordination layer. AI is the engine of anticipation.

This transformation means that operators are becoming conductors of a system that’s more distributed and volatile, but potentially more intelligent. And while it’s largely invisible to consumers, the shift will determine whether power systems can absorb electrification and renewable growth without compromising security of supply, competitiveness or stability.

^Sources

^{IEA, Electricity Grids and Secure Energy Transitions, 2023: grid investment needs, 80 million km of networks by 2040 and the role of grids in the transition.}
^{IEA, Renewables 2024: renewable capacity growth, more than 5,500 GW by 2030 and the dominant role of solar and wind.}
^{ACER, 2024 Market Monitoring Report: negative prices, congestion, flexibility and balancing market integration.}
^{ENTSO-E, Balancing Report 2024: European balancing platforms and TSO role.}
^{ENTSO-E, System Flexibility Needs for the Energy Transition: increasing flexibility needs and prolonged renewable shortfall events.}
^{European Commission, Electricity Market Design: storage, demand response and flexibility in market reform.}
^{ENTSO-E / EU DSO Entity, Network Code on Demand Response: integration of demand-side flexibility, aggregation and storage.}
^{MISO / OMS, 2025 Resource Adequacy Survey: load growth, data centers, seasonal reliability risks and capacity needs.}
^{ERCOT, 2025 Long-Term Load Forecast Update: large-load forecasting and data-center-driven planning challenges.}
^{NERC, 2025 State of Reliability: data centers, inverter-based resources, BESS reliability and operational modeling challenges.}
^{IEA, Energy and AI: data center electricity demand growth and supply implications.}
^{IEA, India cooling demand analysis: rising night-time electricity demand and cooling-driven peak implications}

Authors

Nicolas Carayon

Vice President, Global EDF/Enedis/Rte Delivery Partner, Innovation Director, Capgemini

Hariharan Krishnamurthy

Vice President, E&U Head of Industry ERD, Capgemini

Mercy Paul

Director, Lead Energy & Utilities Industry Platform, Capgemini