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rebase.energy

Stockholm, Sweden · 2-10
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Domain (max 1) Analytics & Forecasts
Technology (max 3) Renewable power forecastingConsumption & load forecastingWeather & resource assessment

AI AnalysisClassification & Focus Areas

AI Insights

"Renewable power & load forecasting platform with multi-model NWP ensembles and icing loss modelling — reduces imbalance exposure for energy traders and utilities."

Domain Affinity

Analytics & Forecasts 85%
Markets & orchestration 10%
Monitoring & control 5%

Technology Breakdown

Renewable power forecasting
95%
Consumption & load forecasting
90%
Weather & resource assessment
85%

Offerings Products & Services

Weather API

An AI-ready weather API tailored for energy applications, offering operational and historical forecasts from over 10 global weather models. It includes full-length historical model runs for ML training and backtesting, with both free and enterprise plans.

Product details

Rebase Forecasting Platform

A Python-first platform for creating, deploying, and monitoring energy forecasting models at scale. It provides APIs, multi-model weather ensembles, and integrates with asset management systems like Bazefield and Greenbyte, as well as data warehouses like Google BigQuery.

Product details

Case StudiesReferences & Success Stories

How Modity Reduces Trading Risk with Icing Forecasts for Wind

Modity integrates rebase.energy's icing forecasts into its trading risk management for a growing renewables portfolio. The partnership, initiated in 2021, has resulted in a tailored decision support system that visualizes weather-related risks and enables faster, data-driven trading decisions compared to traditional weather institutes.

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How Jämtkraft Stays Ahead in a Fast-Changing Electricity Market

Jämtkraft adopted rebase.energy's icing forecasts to predict production losses on wind turbines in cold climates, starting in late 2024. The forecasts led to higher revenues and reduced imbalance costs by enabling more proactive trading and operational decisions. The company plans to expand the use to general wind trading forecasts.

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Why SFE Chose rebase.energy

SFE employs rebase.energy for aggregated load forecasting across its nationwide retail portfolio, replacing a manual and slow third-party system. The platform delivers automated, transparent daily forecasts via API, and adapts to dynamic portfolio changes, improving efficiency in spot billing and reducing manual intervention. SFE reports high confidence in the forecasts and values the responsive support.

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Why Tibber Relies on rebase.energy

Tibber uses rebase.energy's weather data to forecast customer consumption and support electricity trading. The collaboration provides a stable source of high-resolution data and has evolved through close cooperation, including workshops and tailored model recommendations. The well-documented API backend facilitates seamless integration into Tibber's daily operations.

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Why Repowered Moved All Assets to rebase.energy

Repowered moved all its wind and solar asset forecasting to rebase.energy, achieving a fully automated workflow. The API-based platform delivers updated forecasts every few hours and supports trading and asset optimization, while also enabling feasibility studies for potential clients. Repowered cites the platform's performance in benchmarking, ease of integration, and high level of support as key reasons for the transition.

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