[HTML][HTML] The advance of digital twin for predictive maintenance: The role and function of machine learning
The recent advance of digital twin (DT) has greatly facilitated the development of predictive
maintenance (PdM). DT for PdM enables accurate equipment status recognition and …
maintenance (PdM). DT for PdM enables accurate equipment status recognition and …
Sustainable energies and machine learning: An organized review of recent applications and challenges
In alignment with the rapid development of artificial intelligence in the era of data
management, the application domains for machine learning have expanded to all …
management, the application domains for machine learning have expanded to all …
Deep learning versus gradient boosting machine for pan evaporation prediction
In the present study, two innovative techniques namely, Deep Learning (DL) and Gradient
boosting Machine (GBM) models are developed based on a maximum air temperature …
boosting Machine (GBM) models are developed based on a maximum air temperature …
Operational reliability evaluation of urban multi-energy systems with equivalent energy storage
With the coordination of multiple energies at the city level, the complexity of the urban
energy system is ever-increasing. Securing the reliable operation of the urban multi-energy …
energy system is ever-increasing. Securing the reliable operation of the urban multi-energy …
Multi-objective optimization of economic emission load dispatch incorporating load forecasting and solar photovoltaic sources for carbon neutrality
In this paper, the future load condition is predicted by proposing an effective single-layer
Black Widow Optimization based Functional Link Artificial Neural Network (BWO-FLANN) …
Black Widow Optimization based Functional Link Artificial Neural Network (BWO-FLANN) …
A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks
Z Yang, Z Liu, J Zhou, C Song, Q Xiang, Q He, J Hu… - Energy, 2023 - Elsevier
Calorific value metering offers unique advantages in the natural gas industry. Based on a
graph neural network (GNN), this study proposes a method for metering the gas calorific …
graph neural network (GNN), this study proposes a method for metering the gas calorific …
A systematic framework for the assessment of the reliability of energy supply in Integrated Energy Systems based on a quasi-steady-state model
The reliability analysis of IESs (Integrated Energy Systems) is a complicated task because of
the complex characteristics of different subsystems and the multi-scale dynamics that …
the complex characteristics of different subsystems and the multi-scale dynamics that …
Two-stage configuration optimization of a novel standalone renewable integrated energy system coupled with hydrogen refueling
J He, Y Wu, M Wu, M Xu, F Liu - Energy Conversion and Management, 2022 - Elsevier
Two-stage optimization framework of a novel hybrid renewable integrated energy system is
proposed. Firstly, system topological structure and corresponding behaviors are constructed …
proposed. Firstly, system topological structure and corresponding behaviors are constructed …
Reliability evaluation of community integrated energy systems based on fault incidence matrix
Reliability evaluation is essential for the planning, operation, and analysis of community
integrated energy systems (CIESs). However, it is still challenging to quantify the reliability of …
integrated energy systems (CIESs). However, it is still challenging to quantify the reliability of …
Deterministic and probabilistic wind power forecasts by considering various atmospheric models and feature engineering approaches
This study proposed a model for deterministic and probabilistic wind power generation
forecasting and its corresponding procedures. The main contents include numerical weather …
forecasting and its corresponding procedures. The main contents include numerical weather …