Predictive Maintenance 4.0 Applied in Electrical Power Systems

Righetto, Sophia Boing; Martins, Marcos Aurélio Izumida; Carvalho, Edgar Gerevini; Hattori, Leandro Takeshi; Francisci, Silvia de

doi:10.1109/isgt49243.2021.9372230

Cited by 14 publications

(7 citation statements)

References 37 publications

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“…The company also starts to prevent possible theft of electricity and illegal connections by monitoring distribution transformers. Finally, much of the data generated by all these solutions will be used as inputs in the predictive maintenance system that has been developed by ENEL Distribution São Paulo [25], making maintenance less costly for the company, since the performance of predictive maintenance, in a planned way, generates less expenses for the utility.…”

Section: Discussionmentioning

confidence: 99%

Development of an Automated Distribution Grid With the Application of New Technologies

Chaves

Martins

Martins³

et al. 2022

IEEE Access

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With the advancement of technology and the application of new sensors in the electric distribution grid, in order to increase its automation, meeting the idea of smart grids, a concept that has been expanding through the years. This article describes some of the solutions and results that ENEL Distribution São Paulo has achieved, through its R&D (Research and Development) Urban Futurability project, to make its electricity distribution grid automated and in line with trends and future technologies. The project includes the installation of sensors for monitoring and protecting both the overhead and underground electricity distribution grid and medium and low voltage, digitalization of the primary substation and improvements in the communication infrastructure, seeking their complete automation. The project was applied in one of the largest urban centers in the world, the city of São Paulo, Brazil, with a diversity of load profiles, both residential and commercial, being a great place to test new technologies in different scenarios. With the increased application of automation in the electricity distribution grid, ENEL Distribution São Paulo seeks to provide its customers with a better service, with a safer and more reliable electricity distribution grid, monitored practically in real time and with state-of-the-art technologies. Therefore, the end consumers benefit from an electric distribution grid with greater availability and decreased number of interruptions.INDEX TERMS Distribution transformer sensing, fiber optic communication, fuse sensing, grid automation, primary substations digitalization, protection in the low voltage grid, underground fault tracking.

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Section: Discussionmentioning

confidence: 99%

Development of an Automated Distribution Grid With the Application of New Technologies

Chaves

Martins

Martins³

et al. 2022

IEEE Access

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“…In the near future, the information provided by the distribution transformer monitoring equipment will be used as input data for the predictive maintenance system under development by ENEL SP [32].…”

Section: Discussionmentioning

confidence: 99%

Application Study in the Field of Solutions for the Monitoring Distribution Transformers of the Overhead Power Grid

Chaves

Martins

Martins³

et al. 2021

Energies

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This paper will present the development and application of overhead transformers of the distribution grid, as well as the different technologies used for the gathering of electrical quantities, in the field of a monitoring solution. The solution reports the values of the quantities and alarms of operation remotely and almost in real-time. The development of this solution seeks to provide an electrical grid with greater reliability, proposing the reduction of KPIs (Key Performance Indicator), such as SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index), through more transparent monitoring of the behavior of the electrical distribution grid and its equipment. Through the research and development (R&D) project Urban Futurability, ENEL (Ente nazionale per l’energia elettrica) Distribution São Paulo seeks to apply the solution by implementing the concept of smart grids, an idea that has been growing each year by virtue of technological developments and the employment of new sensors in electrical distribution grids. Urban Futurability seeks to innovate the automation area, digital twin, and construction enhancement in the Vila Olímpia neighborhood of São Paulo, Brazil.

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“…Following the above developments, the PdM system is being applied to various fields, such as Smart IoT platform [9], nuclear power plant [10], Motor [11], Boilers [12], and Electrical Power Systems [13].…”

Section: Introductionmentioning

confidence: 99%

AI-Based PdM Platform in Deciding Failure of Automobile SCU Equipment

Oh,

Kim

2024

JAIT

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Recently, factory automation has been implemented using sensor networks. In general, the equipment deployed in automated factories is expensive. Due to the huge maintenance expenses associated with manufacturing plant equipment, there is a growing need for technology that can predict the lifespan of equipment consumables. Real-time fault prediction technology is essential because downtime in a process can led to substantial financial losses for a factory. Predictive Maintenance (PdM), which predicts replacement cycles instead of relying on Preventive Maintenance (PM) following equipment failure, can enhance productivity. Hence, this paper developed a predictive maintenance technology based on Industrial Internet of Things (IIoT). The developed platform can predict and verify the state of equipment in real time. To predict faults, we generated virtual voltage and frequency data for the inspection equipment of the Shift-by-wire Control Unit (SCU). We then applied this data to three models: the Recurrent Neural Network (RNN), the Long Short-Term Memory (LSTM), and the Gated Recurrent Unit (GRU), and compared their performance. Among them, the GRU model achieved the highest prediction speed and accuracy, with an R 2 -score of 0.992. We utilized this platform to develop a real-time AI prediction management system with the goal of improving productivity.

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Predictive Maintenance 4.0 Applied in Electrical Power Systems

Cited by 14 publications

References 37 publications

Development of an Automated Distribution Grid With the Application of New Technologies

Development of an Automated Distribution Grid With the Application of New Technologies

Application Study in the Field of Solutions for the Monitoring Distribution Transformers of the Overhead Power Grid

AI-Based PdM Platform in Deciding Failure of Automobile SCU Equipment

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