
ADQ and ECP partner on $25 B+ data centre energy projects
The investments will be carried out through a 50-50 partnership across 25 GW worth of new-build power generation and energy infrastructure.
The investments will be carried out through a 50-50 partnership across 25 GW worth of new-build power generation and energy infrastructure.
Gorilla Technology Group has secured a $1.8 B agreement to lead an energy digitisation and smart grid initiative in Thailand.
The Ganz Intelligent Solutions Expert System provides a digital tool for condition assessment, diagnostics, and maintenance scheduling of power assets.
Microsoft to invest $1.6 billion to meet soaring energy demands for artificial intelligence (AI).
The fund aims to support power demand from the continued growth and development of AI technologies.
Oracle is currently building a 800 MW datacenter that will train one of the world’s largest AI models. They are already in the design phase for a datacenter that will require 1 GW.
Artificial Intelligence (AI) is transforming various industries, and the field of electrical work is no exception.
Traditional mechanical engineering, notably the power transformer industry, faces challenges such the need for higher efficiency and skilled labor shortages.
Tata Power has announced a partnership with AutoGrid to deploy an AI-enabled smart energy system in Mumbai.
The new Special Edition – ML & AI has is now here, bringing to you fourteen articles with relevant information on these two important and interconnected topics.
Germany: The German grid operators Schleswig Holstein Netz AG and Bayernwerk Netz GmbH have commissioned Siemens Energy to inspect almost 4,000 km of high-voltage overhead lines.
Egypt: Schneider Electric and US-headquartered Cisco are collaborating to build the largest smart grid in Egypt.
USA: Company eSmart Systems will work with Topeka, Kansas-headquartered Evergy, to digitize Evergy’s power transmission system.
Tom Rhodes and Dr. Tony McGrail: AI systems provide a lot of promise in the analysis and evaluation of power system data.
The machine learning algorithms have shown accuracy when analyzing complex power transformer data, but human judgment is crucial in their training process.