[HTML][HTML] A data-driven long-term metocean data forecasting approach for the design of marine renewable energy systems
Abstract The potential of Marine Renewable Energy (MRE) systems is usually evaluated
based on recent metocean data and assuming the stationarity of the MRE resource. Yet …
based on recent metocean data and assuming the stationarity of the MRE resource. Yet …
Review on evolution of intelligent algorithms for transformer condition assessment
Transformers are playing an increasingly significant part in energy conversion, transmission,
and distribution, which link various resources, including conventional, renewable, and …
and distribution, which link various resources, including conventional, renewable, and …
Effective IoT-based deep learning platform for online fault diagnosis of power transformers against cyberattacks and data uncertainties
The distribution of the power transformers at a far distance from the electrical plants
represents the main challenge against the diagnosis of the transformer status. This paper …
represents the main challenge against the diagnosis of the transformer status. This paper …
The future of management: DAO to smart organizations and intelligent operations
In the future, management in smart societies will revolve around knowledge workers and the
works they produce. This article is committed to explore new management framework …
works they produce. This article is committed to explore new management framework …
Reliable IoT paradigm with ensemble machine learning for faults diagnosis of power transformers considering adversarial attacks
Power transformer represents an important equipment in electric power systems.
Transformers are not only a source of power outages for electric utilities, but they also affect …
Transformers are not only a source of power outages for electric utilities, but they also affect …
ChatGPT-based scenario engineer: A new framework on scenario generation for trajectory prediction
The latest developments in parallel driving foreshadow the possibility of delivering
intelligence across organizations using foundation models. As is well-known, there are …
intelligence across organizations using foundation models. As is well-known, there are …
Influence of data balancing on transformer DGA fault classification with machine learning algorithms
The application of artificial intelligence algorithms for transformer incipient fault classification
using dissolved gas analysis (DGA) is an interesting engineering approach. However, there …
using dissolved gas analysis (DGA) is an interesting engineering approach. However, there …
[HTML][HTML] Probabilistic machine learning aided transformer lifetime prediction framework for wind energy systems
JI Aizpurua, R Peña-Alzola, J Olano, I Ramirez… - International Journal of …, 2023 - Elsevier
Accurate lifetime prediction of transformers operated in power grids with renewable energy
systems is a challenging task because it requires a large amount of data that is not usually …
systems is a challenging task because it requires a large amount of data that is not usually …
[HTML][HTML] Probabilistic forecasting informed failure prognostics framework for improved RUL prediction under uncertainty: A transformer case study
JI Aizpurua, BG Stewart, SDJ McArthur… - Reliability Engineering & …, 2022 - Elsevier
The energy transition towards resilient and sustainable power plants requires moving from
periodic health assessment to condition-based lifetime planning, which in turn, creates new …
periodic health assessment to condition-based lifetime planning, which in turn, creates new …
In‐Service Power Transformer Life Time Prospects: Review and Prospects
ET Mharakurwa - Journal of Electrical and Computer …, 2022 - Wiley Online Library
Power transformers are essential assets in power system networks that must be meticulously
monitored throughout their operational life cycle. Given that a substantial percentage of in …
monitored throughout their operational life cycle. Given that a substantial percentage of in …