Power and renewables

Insights for the manufacturers sector

We take pride in delivering independent insights based on facts and data. Discover below some of our most recent reports, podcasts and opinions from experts across the energy value chain.

  • Article
  • Manufacturers

A world first for HVDC gas-insulated system

Nowadays, HVDC systems have become a common solution for long distance power transmission. But the application of gas-insulated technologies to HVDC has not. For the first time, long-term testing has commenced to independently verify and demonstrate that this technology is ready for real-life application. The recommended test will be performed on a complete 320kV HVDC GIS, designed and assembled by ABB in KEMA’s HVDC laboratory.

  • Article
  • Manufacturers

Offshore wind: The time is now

In recent years, the world has taken major steps towards a lower-carbon energy system. However, we still have some way to go to meet internationally agreed emissions targets for combatting climate change. The good news is that, after years of impressive progress, offshore wind is now ready to become a major contributor to global energy production as well.

  • Article
  • Manufacturers

Choosing the right battery storage solution

Variable renewable energy sources like wind and solar need energy storage to help balance production and demand. Battery-based systems are fast emerging as an ideal solution, but with big differences between batteries; how can manufacturers provide performance assurance and how do project developers choose the right storage solution?

  • Topic
  • Manufacturers

Disruptive innovation and the traditional energy company

Wouter van Wersch, VP of General Electric, looks at the energy and technology transition from the perspective of a traditional energy business and focuses on the specific needs of Asia.

  • Article
  • Manufacturers

Data science & machine learning

There are already emerging success stories in which data-driven modelling has contributed to significant efficiency gains, but for applications where the consequences of wrong decisions are large, many industrial data science or machine learning (ML) projects still fall short of expectations.

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