Home / Blockchain / The Energy Department awards $ 4.8 million to research technology areas, including Blockchain

The Energy Department awards $ 4.8 million to research technology areas, including Blockchain

The US Department of Energy announced the allocation of $ 4.8 million for research and development in four specific areas, including the Cybersecure sensors for the production of fossil energy, which has & # 39; application of blockchain technology. The idea behind this funding is to prepare the next line of science and technology professionals in the field of fossil energy. This according to the Department will contribute to reducing the carbon footprint and the total cost related to the production of fossil energy. It is not the first time that the Department of Energy has invested in blockchain technology as in July last year; had granted $ 95 million to various states including Colorado, which had proposed to develop the Grid7 startup based on blockchain technology.

Blockchain and energy sector

The announcement of the financing mentions the blockchain technology and its ability to improve the overall potential of the energy sector. The Department specifically mentioned that the use of blockchain and peer-to-peer protocol could help to ensure a secure signal as well as facilitate the flow of information without interruption within the distributed network of sensors for generation of uninterrupted energy.

The Department of Energy has stated that it is anticipating the selection of a maximum of 12 projects for the allocation of the funds mentioned above. Acciona Energia – a renewable energy company based in Spain that is also considered one of the largest renewable energy operators in the world – is ready to use blockchain technology to track electricity generation. The South Korean government also announced in December last year that it would spend $ 3.5 million to create a blockchain-based virtual power plant in its city of Busan, Korea's second-most populous city. This plant was developed with the aim of optimizing energy production by integrating the time of autonomy of the inactive capacity of the various energy sources involved in the generation of energy.

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