The wind and solar forecasting software that reduces imbalance costs for market operators

Imbalance costs are a direct hit to margins: when day‑ahead or intraday schedules diverge from actual wind or solar output, electricity market operators pay settlement penalties or miss trading opportunities. Renewcast positions itself as a specialist wind and solar forecasting software that lowers those errors, and therefore imbalance costs, by combining AI models, digital‑twin corrections and multi‑source weather inputs.

The imbalance‑cost problem in Italy and Europe

Imbalance costs have become a material business risk across European markets because intraday prices and imbalance settlements can swing dramatically as renewable output changes. For traders, utilities and other market operators, this means forecast errors translate into settlement charges and lost trading upside; studies and market reports show balancing charges remain a persistent line‑item in P&L for 2024–2026 market designs.

How forecast errors translate into real losses

Even modest forecast errors on a large fleet produce significant euro exposure: market analyses and vendor reporting quantify imbalance exposure as several euros per MWh in many use cases, and improvements in accuracy metrics directly reduce that exposure. Renewcast’s public materials report achievable improvements that can be translated into concrete imbalance savings for operators.

How Renewcast fixes the problem

Renewcast’s SaaS platform blends advanced deep‑learning, per‑asset digital twins and multi‑model weather fusion to improve day‑ahead and intraday forecasts, update forecasts hourly, and deliver APIs and dashboards that integrate with trading and SCADA systems, producing measurable reductions in imbalance costs and more reliable scheduling.

Why day‑ahead and intraday forecasting is critical now

• Market structure: day‑ahead commitments set positions that are later fine‑tuned intraday; as intraday volatility grows, the cost of being wrong at either horizon rises.
• Revenue impact: better short‑term forecasts enable operators to optimize nominations and capture intraday arbitrage while limiting imbalance exposure.
• Operational planning: accurate intraday updates improve dispatching, reserve decisions and maintenance windows for wind farm operations and solar operations.
  

How Renewcast works

Renewcast delivers a cloud SaaS platform that combines:

• AI & deep‑learning base models trained on historical production and meteorological data, plus turbine‑level digital twins to correct plant‑specific behaviour.
• Hourly forecast updates covering intraday, day‑ahead and up to 15 days for planning.
• Performance‑tied commercial model (pricing linked to forecast improvements) to align vendor incentives with client ROI.
• Weather data integration: models, frequency, resolution

Renewcast fuses multiple meteorological sources and models to reduce single‑model bias; the platform ingests global NWP outputs and local observations, applies point‑level correction and updates forecasts hourly to reflect the latest model runs and on‑site telemetry. This multi‑source approach (multi‑model, multi‑source weather data integration) improves both short‑term responsiveness and day‑ahead stability.

Technical architecture: accuracy, speed, reliability

• Cloud‑native SaaS with API access and client UI for parametric reports and downloads, designed for high availability and rapid forecast refresh every hour.
• Digital‑twin layer that maps machine‑level behaviour to forecast outputs, improving per‑asset correction and reducing site‑specific bias.
• Performance metrics and SLAs focused on NMAE/RMSE/skill scores rather than vanity metrics, enabling clients to quantify forecast value.

Support for trading and operations

• High‑accuracy day‑ahead and intraday forecasts reduce imbalance exposure and enable tighter positions before settlement, improving ROI on trading strategies.
• API access and frequent updates allow automated trading systems to ingest corrected positions and exploit intraday arbitrage.

For Wind and Solar operations

• Improved short‑term forecasts reduce penalties.
• Digital twin per turbine/plant allows operators to detect anomalies and adjust operational plans with higher confidence.

Comparison with traditional solutions and other wind and solar forecasting platforms

• Traditional single‑model or purely statistical forecast services often rely on a single NWP and limited site correction, which tends to produce higher bias and slower adaptation to real‑time plant behaviour.
• Renewcast’s multi‑model fusion, deep‑learning corrections and digital‑twin approach aim to reduce systematic bias and lower NMAE index of error, at both day‑ahead and intraday horizons, translating into measurable imbalance‑cost reductions versus legacy forecasting approaches.

References

Prospeo company profile — Renewcast overview and contact

Redstone VC — Renewcast

How energy retailers reduce imbalance costs in real time. Podero Insights

Electricity Balancing Cost Report 2025. ENTSO‑E

A simulation model for imbalance costs of renewable energy aggregators: The case of Greek balancing market. Energy Economics (Elsevier).

2025 Annual Balancing Costs Report (sector report). Neso Energy

Startup‑News article — Renewcast funding and AI for energy forecasts