frontcurve.

APPLIED AI · WEATHER + ENERGY

The weather moves.
The market follows.

We’re developing AI forecasting for Germany’s electricity market. Combining probabilistic weather intelligence with machine-learning price models.

Explore our approach See the connection
Weather pipeline operational.
Electricity price forecasting in development.
OUR FIRST FOCUSGermany / DE–LUProbabilistic weatherDay-ahead power markets Applied research

01 — THE APPROACH

Weather is a driver.
Uncertainty is the signal.

Wind and sunlight influence renewable generation. Temperature shapes demand. We’re developing the link between those weather scenarios and the electricity market.

01

Start with possibilities.

AI weather forecasts describe a range of outcomes. Our existing pipeline processes these forecasts and calibrates temperature probabilities against local observations.

WEATHER DISTRIBUTIONS
02

Connect weather to power.

Our next research step is to translate wind, solar, and temperature scenarios into estimates of renewable generation and electricity demand.

GENERATION + DEMAND · PLANNED
03

Build a market view.

We plan to train machine-learning models that combine weather signals with market fundamentals to estimate day-ahead electricity price distributions.

PRICE SCENARIOS · IN DEVELOPMENT

Weather is one part of the price picture. Fuel costs, plant availability, cross-border flows, and market conditions also matter.

02 — FOLLOW THE SIGNAL

A different forecast.
A different curve.

Explore a simplified example of how weather can change the shape of a power price scenario.

A reference scenario with a midday dip and an evening rise. The shaded area illustrates uncertainty around the central curve.

Concept illustration. Synthetic values, not a live forecast or validated model output. Weather effects are shown with other inputs held constant.

MARKET BACKGROUND · SMARDThe challenge of solar peaks

ILLUSTRATIVE DAY-AHEAD SCENARIO

Germany / DE–LU

EUR / MWh
Synthetic electricity price scenarioAn illustrative daily price curve and a shaded uncertainty band. Select a weather scenario to compare conceptual effects.1601208040000:0006:0012:0018:0023:00
Central scenario Illustrative rangeEurope / Berlin

03 — FROM RESEARCH TO PRODUCT

A working foundation.
A focused next step.

Frontcurve is an independent AI startup. We’re developing a subscription dashboard and API for weather-driven electricity market research, starting with Germany’s day-ahead market.

WORKING TODAY

The weather foundation

  • AI weather forecast processing
  • Local temperature calibration using observations
  • Scheduled forecast pipelines on Google Cloud
  • Validated, versioned forecast artifacts

We use existing AI weather models as inputs and develop our own calibration and processing layer. Electricity price forecasting performance remains to be evaluated.

WHAT WE’RE DEVELOPING

The power market application

  1. 01
    German market data

    Align weather inputs with generation, demand, and historical DE–LU prices.

  2. 02
    Forecast evaluation

    Test on unseen historical periods and compare against transparent baselines.

  3. 03
    A first commercial pilot

    Develop a research dashboard and API around a clearly defined customer need.

THE PEOPLE WE’RE BUILDING FOR

For decisions
exposed to the weather.

01

Power market analysts

Explore how changing weather assumptions affect generation, demand, and price scenarios.

02

Renewable energy teams

Understand the market context around periods of strong or weak wind and solar output.

03

Energy procurement teams

Investigate weather-related uncertainty when planning flexible electricity consumption.

FRONTCURVE / PROJECT OVERVIEW

From the atmosphere
to the electricity market.

Applied AI for weather forecasting, probabilistic modelling, and electricity market research.

Download the project brief