Alice explained: the intelligence behind Tibo EMS

The energy world is moving faster than ever. Companies are electrifying, energy prices fluctuate hourly, and grid congestion limits growth. In this playing field, one thing has become clear: energy management can no longer be manual, slow, or reactive.

Yet many Energy Management Systems (EMS) still operate according to old principles — with fixed rules and static schedules. They only adjust when things go wrong and lack an overview of what is happening now, later today and in the future.

That is why Tibo Energy developed something fundamentally different: Alice — the real-time algorithm that controls our EMS.

Alice thinks ahead, continuously learns and makes decisions within seconds about the smartest use of energy.

In this article, you will discover:

• why traditional EMS systems are no longer sufficient,
• what makes real-time energy management with Alice so unique,
• and what that means in concrete terms for costs, CO₂ and control.

But today’s energy world is anything but simple.

Companies operate in shared networks with multiple assets, users and market signals. Network congestion, dynamic pricing and CO₂ control make energy management different every second.

And that’s where traditional EMS systems get stuck.

They respond too slowly, control assets individually rather than network-wide, and lack the intelligence to decide what is most valuable now, later and tomorrow.

That is exactly where Tibo EMS and Alice, our real-time algorithm, make the difference.

1. Standard EMS systems use basic optimisation

Many traditional EMS systems rely on heuristics or simple rule-based methods to control energy consumption.

These approaches work in predictable environments with a limited number of variables. But in more complex settings—such as an EnergyHub with multiple businesses and competing strategies—these methods quickly reach their limits.

Why?

• Rule-based EMS systems follow fixed patterns, such as: “Charge the battery whenever solar energy is available.” But this approach doesn’t account for external factors like energy prices or demand peaks.
• Heuristics offer more flexibility, but they don’t necessarily produce an optimised outcome and lack the ability to efficiently manage complex, dynamic environments.

Tibo EMS takes a fundamentally different approach.

Instead of relying on fixed rules, Alice, our AI-driven engine, applies microeconomic principles and real-time data to continuously optimise energy assets.

This means the system doesn’t just focus on what seems best right now—it also evaluates what will generate the most value in a few hours, or even days ahead.

2. No network-wide optimisation

In a shared energy network—such as an industrial site or an EnergyHub—each business follows its own strategy. Some prioritise cost savings, others focus on reducing emissions, and some actively trade energy.

A standard EMS optimises at the asset or individual company level, whereas Tibo EMS treats the entire network as a single, interconnected system.

3. Slow response to market signals and disruptions

Large-scale energy networks are influenced by external signals that demand immediate action, such as:

• Grid operators sending BRP or BSP signals indicating grid congestion.
• Energy price fluctuations that create opportunities for cost-effective purchasing or strategic selling.
• Energy price fluctuations that create opportunities for cost-effective purchasing or strategic selling.

Traditional EMS systems can’t process these factors in real time and often require manual adjustments.

Tibo EMS responds automatically, recalculating an optimised strategy within seconds.

What does this mean in practice?

• A standard EMS performs well in simpler environments, but struggles as soon as multiple businesses, assets, and market dynamics interact.
• Tibo EMS is specifically designed for environments where fast decision-making, flexible strategies, and complex collaboration are essential.

The two biggest challenges in EMS: complexity and speed

The energy transition is not only about sustainability, but also about data and decision-making speed.

True optimisation requires a system that:

• continuously learns from new data, and
• makes decisions in seconds rather than minutes.

That is why we developed Alice: a real-time, self-learning algorithm that controls complex energy networks as a single smart entity.

• Multiple assets, such as batteries, EV chargers, and heat pumps, requiring energy simultaneously.
• Diverse strategies, from cost reduction and emissions control to energy trading.
• Dynamic market conditions, including fluctuating energy prices and grid congestion.

A traditional EMS makes decisions in the moment, optimising at the asset or individual company level.

This means it doesn’t account for what might happen later in the day—or even later in the week.

Tibo EMS works differently. Our system looks ahead and predicts:

• When demand peaks will occur, ensuring assets are prepared.
• When solar or wind generation will fluctuate, so batteries charge or discharge at the right time.
• When energy prices will rise or fall, so the cheapest and most sustainable power is used.

By taking this forward-looking approach, networks stay balanced without the need for manual intervention.

2. The challenge of speed and why real-time makes all the difference

Beyond complexity, speed plays a crucial role in energy management. External triggers, such as a grid operator requesting reduced load via a BRP signal, require immediate action. An EMS must respond in seconds, not minutes.

Many traditional EMS solutions rely on fixed schedules and manual adjustments. This means valuable opportunities are lost, for example:

• A grid operator requests flexibility, but the EMS responds too late to take advantage.
• The battery charges at the wrong time, leading to unnecessarily high costs.
• An unexpected demand peak causes grid instability, even though it could have been predicted.

Tibo EMS uses real-time optimisation and machine learning.

Since the latest Alice update, the system not only calculates a complete optimisation plan every few minutes, but also continuously adjusts it — every few seconds.

This allows Alice to respond immediately to sudden price changes, grid restrictions or unexpected peaks, without manual intervention.

As a result, companies always benefit from the best energy price, the most stable grid balance and the highest flexibility.

Thanks to this real-time approach, Tibo EMS is not only predictive, but also adaptive — an essential difference for complex, rapidly changing energy networks.

What does this mean in practice?

• Tibo EMS does not just react to what is happening now—it anticipates what will happen next.
• The system processes market signals and grid impulses in real time and adjusts accordingly.
• Businesses can use energy more efficiently, reducing costs and making better use of their assets.

Why Tibo EMS works in complex networks

While traditional EMS solutions struggle with speed and scalability, Tibo EMS is designed to turn complexity into optimal decisions.

This is made possible by Alice, the algorithm within Tibo EMS that approaches energy management based on microeconomic principles rather than static rules or fixed optimisation paths.

1. Alice makes decisions based on economic value, not just mathematical models

Many EMS solutions rely on fixed rules (rule-based approaches) or mathematical models such as MILP to optimise energy usage. These methods work well in predictable environments but fall short in today’s dynamic landscape.

Why?

Fixed rules are designed for stable conditions where energy demand and supply remain largely constant. They cannot adapt to highly volatile prices, grid congestion, or shifting market demand.

Mathematical models like MILP can theoretically calculate an optimal solution, but in practice, they are rarely applicable in complex energy networks such as EnergyHubs. As the number of assets, variables, and strategic interests increases, these models struggle to scale effectively.

Alice works fundamentally differently. Instead of following a single fixed method, Alice combines economic optimisation with real-time data to continuously make the best decision.

This means:

2. Alice looks ahead and prevents waste

The biggest difference between Tibo EMS and traditional systems is that Alice doesn’t just react—she anticipates.

A conventional EMS charges a battery whenever there is excess solar energy, without considering future price fluctuations or demand peaks. Alice takes a different approach:

• She predicts when energy will be most valuable and adjusts asset usage accordingly.
• She minimises unnecessary curtailment of solar energy by aligning production with consumption.
• She leverages flexible flexibility, dynamically allocating assets to the most valuable application.

As a result, batteries and other energy assets are not used based on fixed rules but in a way that continuously adapts to real-world conditions.

3. Tibo EMS operates at the network level, not per asset

A traditional EMS optimises per asset—a battery, an EV charger, or a heat pump. While this might seem logical, it leads to inefficiencies across the entire network.

Tibo EMS takes a broader approach. In a shared energy network, such as a business park or campus, this means:

• A sudden spike in energy demand at Company A can be balanced by flexibility at Company B.
• A battery is not just used for cost savings but also to take advantage of price fluctuations in the energy market.
• Solar energy is not wasted but optimally distributed across all connected businesses.

By optimising energy across the entire network rather than per individual asset, Tibo EMS ensures that businesses not only save energy but also create additional value.

What does this mean in practice?

• Alice thinks ahead, ensuring businesses get the most out of their energy assets.
• Energy is used at the right time, not according to fixed schedules.
• The entire network is optimised instead of just isolated components.

Summary: what makes Tibo EMS unique?

With Tibo EMS, businesses gain full control over their energy management without the need for manual adjustments or inefficiencies. Thanks to Alice, assets are optimally deployed, and energy usage is planned ahead rather than simply reacting to real-time events.

This delivers tangible benefits:

Instead of simply managing energy, Tibo EMS enables businesses to deploy energy strategically—always in the right place, at the right time, at the lowest cost.

Curious to see how this works in practice? Request a demo and experience the intelligence firsthand.