Hitachi will help digital transition of Gansu power grid in supplying electricity: official

Hitachi will help digital transition of Gansu power grid in supplying electricity: official

23 Dec, 2021

Hitachi ABB Power Grids said it would partner with the Electric Power Research Institute of Gansu Electric Power Company, a subsidiary of the State Grid Corporation of China to help conduct intelligent performance management for the 750kV main transformers in Gansu province.

With its Lumada Asset Performance Management (APM), Hitachi ABB Power Grids said the cooperation would help accelerate digital transition of Gansu's power network.

The digital software will also enable the predictive maintenance of transformers and enhance the security level and digital transition for the local power grid, it said.

Gansu Electric Power Company currently supplies electricity to more than 9.6 million households in the province located in northwest China. Gansu power grid plays a critical role in the transmission of electricity, 41.9 percent of it being wind and solar, from western China to the eastern areas. It is also a key hub for power exchange in the northwest grid.

"The digitalization of the power grid will increase the flexibility, resilience and reliability of the entire power value chain, and can strongly support the move toward a carbon-neutral energy future," said Zhang Jinquan, executive vice-president of Hitachi ABB Power Grids.

"We are very pleased that we can help accelerate this digitalization effort with smart asset performance management solutions and services that can improve the stability of the power grid and support the utilization and transmission of large-scale clean energy in the area."

Transformers are vital components of a substation, essential to ensuring reliability of the power grid.

Hitachi ABB Power Grids said the digital platform will help Gansu Power Company move from a reactive to a proactive approach to asset maintenance planning, and the solution's accuracy continues to increase over time through its data-driven machine learning capabilities.

It will also help them extend the service life of equipment and ensure the stable operation of the power grid while minimizing financial losses associated with asset failure and unexpected outages, it said.

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