Improved integration of renewables in the energy system


Denmark has an official goal to use no fossil fuels by 2050, with an intermediate 70% CO2 reduction by 2030. To accommodate this, it is on one hand important to introduce huge amounts of renewable energy from wind and solar sources, and on the other hand integrate the renewable energy production with production of hydrogen and other fuels (so called P2X).

Due to their high time variability, precise forecasts of the wind and solar power production are essential to maintain grid stability, to optimize planning of operation, maintenance, and energy consumption, and to energy trading as well as production of hydrogen and other green fuels. In recent time, the expansion of wind and solar has already exhausted all Danish grid ancillary services on several occasions, showing a need to act now.

Renewable energy sources are increasingly looked to as the main solution to ongoing climate challenges. As a result, the penetration of renewable energy sources has increased dramatically in recent years and is expected to increase even further in the coming years. This presents a new challenge as wind and solar only produce power when the wind blows and the sun shines. This shift towards power generation from intermittent sources like wind and solar is challenging because it disrupts conventional methods for trading and operating energy systems.

Renewable power production varies and fluctuates on multiple spatial and temporal scales, forcing grid operators and balance responsible parties to adjust their operation and trading day-ahead, hour-ahead, minute-ahead, and real-time. Consequently, in areas with a high penetration of renewables, reliable forecasts are needed on all relevant temporal scales to ensure safe and economic operation of the power system. Forecasts are also needed for several spatial aggregation levels, e.g., for planning of network operation and use of storage and P2X solutions.

The purpose of this project is to accommodate the demand for more accurate and detailed forecasts for power production, and more specifically make use of such improved forecasts for the optimization of hydrogen (P2X). This is done by a consortium that include all necessary players along the value chain and with a so far unseen collaboration and availability of data. This project will show how the industry can work together across the value chain, and increase innovation and collaboration between metrological offices and large utilities, facilitated by a SMV with innovative methodologies.


The consortium of DTU, ENFOR and AI-Energy aims at increasing accuracy of renewable power forecast by an ambitious 10%, and to utilize those improved production forecast in the optimization of P2X.

This will result in decreased imbalance and ancillary services cost and make way for additional expansion of renewable energy. The project aims at doing this by including the whole value chain from metrological data, power forecast companies (ENFOR and AI-Energy), and the solutions will be tested out with renew-able power production companies.

The expected improvements are furthermore made possible by end-users providing hitherto unshared wind and solar data to improve current weather models and furthermore develop new power forecasts models with higher resolution and frequency customized to the current and future electricity markets.

The project will introduce new components into the power forecast with focus on:

  • Adding more data sources to improve weather forecasts and power forecasts
  • Customizing data for the purpose of wind and solar power production
  • Increase the time and geographical resolution of the models
  • Analyse improvements of the inclusion of wind farms directly in the weather models

The expected outcome is an estimated 10% improvement in renewable power production forecast accuracy which ultimately will increase security of supply, reduce the cost of integrating renewables (by reducing balancing costs), and improve the business case of P2X facilities, by enabling a more optimized operation (production) of hydrogen and other green fuels, and create value for the end-users and at project end, most of the new component will be operational and available on a commercial scale.

In this project all stakeholders of the value chain will work closely together to ensure a focus on a development and testing of methods which can ensure improvements for trading and real-time production environments.

Partners in the project

  • AI-Energy
  • DTU

Financed by


Project period: 

Start: July 2023

Completion: November 2024

Total budget: DKK 3,200,000

Contact person

Marie Vedel Lauridsen

Marie Vedel Lauridsen
Project Manager
Tlf: +45 2265 4600