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Almena

For energy experts

Almena models the market. You make the move.

Almena ingests public data and transforming through a proprietary modeling layer built and validated inside the energy market itself.

"The inputs are public. What we've built on top of them isn't, and that's the part that took years and doesn't exist anywhere else."

, Luna Gutiérrez

Intelligence Models Suite

Models for 
Modern Power Markets

A portfolio of proprietary analytical engines covering forecasting, dispatch simulation, renewable forecasting, hybrid asset modelling and market regime identification, the analytical foundation for trading, asset optimisation and strategic decision-making.

 
QAOA

Market Regime Model

Electricity markets do not behave according to a single stable pattern, low-price hydro-driven hours, renewable-dominated periods and tight market conditions follow fundamentally different dynamics. Using a quantum-inspired classification approach, QAOA assigns every hour to a defined market regime and routes it to a specialised forecasting model, so the system adapts to market structure instead of forcing one model on every condition.

Sharper forecasts during the most volatile, valuable hours
PEKA

Price Forecasting Model

Electricity prices emerge from the interaction of demand, renewable generation, fuel markets, weather conditions and market behaviour. PEKA transforms these signals into reliable day-ahead and intraday price forecasts. Built as a production-grade engine, it combines historical market data with demand, renewables and calendar effects to generate forecasts ahead of every trading session, running continuously in production as the forecasting backbone for trading, bidding and portfolio optimisation.

Reliable price forecasts for trading and bidding decisions
AXAR

Hybrid Market Model

Pure statistical models perform well under normal market conditions but struggle during exceptional events. AXAR combines machine learning with the physical principles governing electricity market dispatch, embedding market mechanics into the forecasting process. The result is a forecasting architecture that adapts not only to historical data but to the structural behaviour of the electricity system, holding up during periods of market stress, scarcity and policy shocks.

Robustness during abnormal and stressed market conditions
NAGA

Dispatch  Model

Electricity prices ultimately depend on which power plants are dispatched to satisfy demand. NAGA simulates the electricity system itself, modelling which units start, stop and produce under different market conditions, reproducing the physical dispatch process that determines market outcomes. This enables detailed scenario analysis, market simulations and operational planning grounded in system behaviour rather than statistical pattern matching.

Transparent scenario analysis and market simulation
MALENA

Hybrid Asset Model

Hybrid energy assets introduce operational complexity that conventional forecasting models cannot capture. MALENA simulates the technical and economic behaviour of co-located systems such as solar + battery or wind + battery. Calibrated on real operational data, it estimates energy production, storage operation and expected revenues under different market conditions, a complete digital representation of hybrid asset operation for investors, developers and operators.

Asset optimisation and long-term revenue maximisation
CATEL

Renewable  Model

Renewable generation has become one of the primary drivers of electricity market behaviour. CATEL independently forecasts solar and wind generation at regional and national levels using meteorological information and renewable production models. These forecasts are critical inputs for market analysis and feed PEKA with high-quality renewable estimates, sharpening both renewable visibility and overall market forecasting accuracy.

Improved renewable visibility and forecasting accuracy

New models, same architecture.

Grid connection, flexibility, storage, green hydrogen, new engines plug into the same commercial and technical framework as the suite grows.

WHAT MAKES ALMENA DIFFERENT

Built for Spain. Ready for Europe.

Our models are built from inside the market, not applied to it from outside. That is why the depth, the architecture and the regulatory fit are different from generalist analytics platforms.

01

Market-built, not generalist

We adjust to the market, not the other way around. Our models are not general-purpose templates, they are deep analytical engines built specifically for electricity market problems: nodal systems, dispatch logic, grid constraints and regulatory structure.

Deeper analysis, fewer assumptions.

02

Spain-native intelligence

No global analytics provider builds from inside the Spanish market. Almena is Spain-native: REE PACADI grid intelligence, MIBEL market structure, CNMC regulatory insight, and restricciones técnicas nodal analysis that no international platform replicates.

Built from inside the system.

03

Every EU market, built independently

Each EU market is built independently, not adapted from a single model. Spain runs on MIBEL architecture. Italy will run on GME and MSD architecture. Germany will run on regelleistung.net and SMARD. One IOSCO-aligned methodology, applied market by market.

One framework. Local architecture.

OMIE
Market data
REE
Grid & system operations
ESIOS
Generation & demand data
ENTSO-E
European market data
BOE
Official bulletin
DOGC
Regional official documents
Weather
Numerical forecasts
Satellite
Earth observation
OMIE
Market data
REE
Grid & system operations
ESIOS
Generation & demand data
ENTSO-E
European market data
BOE
Official bulletin
DOGC
Regional official documents
Weather
Numerical forecasts
Satellite
Earth observation

Validated, not experimental.

Every figure Almena publishes traces back to real, sourced numbers: market data, grid records, and modelling validated against live outcomes.

See how to work with Almena
  • 95 nodes with a live constraint KPI.
  • 66.86% of Spain's constraint volume attributed to specific nodes.
  • 2,790 substations with capacity data.

FAQ

Frequently asked questions