Spanish TSO Red Eléctrica’s (Redeia) subsidiary Elewit announced today its ASUMO project, which aims to enhance data collection across electrical substations through the use of AI and digital twin technologies.
Elewit, a tech platform for the country’s transmission operator, announced the project in response to the need for automated efficiency in the lifecycle of grid assets.
The Advanced Substation Monitoring Project (ASUMO) was described by the company in a release issued today as a “cross-sectional initiative within Redeia that promotes the digitisation and real-time management of substation assets”.
The project’s goal, they add, is to improve response times to incidents and significantly reduce the presence of personnel at facilities.
To coordinate this, the project will make use of IOT, AI and data analytics, as well as technology such as digital twins, to automate and improve procedures across maintenance, engineering and construction of substation assets.
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Data collection
Core to the project is the opportunity to enhance data collection of critical variables associated with electrical substation assets and real-time images.
Once this collection has been processed through advanced data analysis tools and artificial intelligence, the company states, electrical installation and asset status and condition can then be calculated in real time, improving availability and allowing forecasting of potential incidents.
Additionally, ASUMO aims to optimise the remote operation and maintenance of electrical assets by visualising and processing images in real time, creating a digital twin using systems that analyse the data and provide recommendations on preventive and corrective maintenance actions.
This way, different notifications and alarms are obtained in real time, which are needed to avoid major affections on the assets of the transmission network.
Project scope and phases
According to Elewit, ASUMO is divided into five phases:
- Defining and investigating affected areas, including engineering, construction and maintenance of electrical substation assets.
- Analysing technical information needed by asset typology and technology to define an asset monitoring strategy and specify the needed activities to implement it.
- Identifying critical variables per asset as well as their analysis and segregation for real-time management and degradation models.
- Data processing creating the required algorithms and alarm logics.
- Necessary developments for the integration of this new information flow in the corporate information systems.
The company also lays out five areas of the project’s scope, extending to:
- Primary switchgear and ancillary services sensorisation in AIS/GIS installations.
- Real-time automatic monitoring and management of precursor variables.
- Data lake integration for later use in AI applications.
- Digitisation of assets, creation of digital twins and 3D modeling.
- Real-time visualisation of substation assets with fixed and mobile cameras using AGV (Automatic Guided Vehicle).
