Barbara IoT develops edge computing-based trip analysis tool

Software startup Barbara IoT is developing a tool based on edge computing to characterise the state of electrical substation elements when a trip occurs.

The startup’s solution, a project in collaboration with Spanish TSO Red Eléctrica and tech platform Elewit, aims to improve insights into how and why trips occur in substations through real time data.

This, in turn, aims to improve connectivity and provide valuable information for the operation, maintenance and planning of the electrical grid.

Currently, when a trip occurs, technicians study the variables that characterise the state of the protection element and determine what has happened based on the data recorded at different points in the substations.

Based on this data, mitigation and correction plans are designed if necessary, so the network is reviewed and adjusted more precisely for each of these events to maintain its operation.

However, states Elewit, technicians require tools that allow them to analyse these events in a more agile way and in real time.

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Barbara IoT’s proposed solution will focus on the design and development of a tool to provide insight into these events.

Their solution is a small device that, once attached to the corresponding protection element, allows the behaviour of the voltage and intensity of the element to which it is connected to be displayed in a web application.

This small device, states Barbara IoT, is capable of graphing the three-phase current of the element with a sampling frequency of 0.25 milliseconds, 80 times the frequency at which the network oscillates.

With this speed, it will be possible to identify and analyse what may have triggered the trip.

The project aims to meet the needs of substation technicians since they will be able to have the data for both monitoring and analysis.

Barbara IoT and Elewit in a release detail some of the ways such a solution will improve grid operations:

• Improved system reliability: If the causes of a trip are identified, measures can be taken to prevent future failures and improve the reliability of the entire electrical system
• Predictive network maintenance: By analysing trip events, maintenance strategies can be implemented on components before failures occur
• Optimisation of substation operation: The information provided by the study of trip events can be used to optimise the operation of substations and improve efficiency in power transmission and distribution

The solution, according to Elewit, is based on edge computing, a type of in-situ computing that collects and processes data from the same hardware rather than sending it to the cloud for computation, as most IoT-based devices with a more passive character do.

The main advantage offered by edge computing is its nearly instantaneous processing and monitoring capabilities. This negates the need for post-processing in subsequent programmes when conducting analyses.

According to Elewit, the project has successfully passed laboratory tests and is in the process of validation to study its implementation in Red Eléctrica’s systems.