A hybrid framework for forecasting power generation of multiple renewable energy sources
The accurate power generation forecast of multiple renewable energy sources is significant
for the power scheduling of renewable energy systems. However, previous studies focused …
for the power scheduling of renewable energy systems. However, previous studies focused …
Review on automated condition assessment of pipelines with machine learning
Y Liu, Y Bao - Advanced Engineering Informatics, 2022 - Elsevier
Pipelines carrying energy products play vital roles in economic wealth and public safety, but
incidents continue occurring. Condition assessment of pipelines is essential to identify …
incidents continue occurring. Condition assessment of pipelines is essential to identify …
A hybrid deep learning framework for predicting daily natural gas consumption
Conventional time-series prediction methods for natural gas consumption mainly focus on
capturing the temporal feature, neglecting static and dynamic information extraction. The …
capturing the temporal feature, neglecting static and dynamic information extraction. The …
Detection of faults in subsea pipelines by flow monitoring with regression supervised machine learning
This study investigates the relationship between pressure change, velocity change, and
temperature of crude oil through a pipeline and presents a method of using a regression …
temperature of crude oil through a pipeline and presents a method of using a regression …
[HTML][HTML] Review on the transport capacity management of oil and gas pipeline network: Challenges and opportunities of future pipeline transport
Pipelines are the essential transportation infrastructure of the energy system, undertaking
most transportation tasks of oil and gas on land. In a critical period of the energy transition, it …
most transportation tasks of oil and gas on land. In a critical period of the energy transition, it …
[HTML][HTML] Innovations of carbon-neutral petroleum pipeline: A review
As one of the major energy-intensive industries, petroleum pipelines are facing with huge
pressure from carbon-neutral policies. Conforming to green development, the traditional …
pressure from carbon-neutral policies. Conforming to green development, the traditional …
Deeppipe: A deep-learning method for anomaly detection of multi-product pipelines
The multi-product pipeline is the main way of refined oil transportation to ensure the safety of
the energy supply. Considering that abnormal conditions of the pipeline will cause huge …
the energy supply. Considering that abnormal conditions of the pipeline will cause huge …
A knowledge-enhanced graph-based temporal-spatial network for natural gas consumption prediction
The accurate prediction of natural gas consumption plays a central role in long-distance
pipeline system production and transportation planning, and it becomes even more …
pipeline system production and transportation planning, and it becomes even more …
Deep learning identifies leak in water pipeline system using transient frequency response
Pipeline leak identification method using transient frequency response (TFR) has been
researched in the past two decades. To extend this method to a more general water pipeline …
researched in the past two decades. To extend this method to a more general water pipeline …
Deeppipe: An intelligent framework for predicting mixed oil concentration in multi-product pipeline
Accurately predicting mixed oil concentration distribution exerts a core effect on the
optimization of pipelines and the quality of oil. Due to the neglect of mechanism features …
optimization of pipelines and the quality of oil. Due to the neglect of mechanism features …