[HTML][HTML] Uncovering wind power forecasting uncertainty sources and their propagation through the whole modelling chain
Wind power forecasting has supported operational decision-making for power system and
electricity markets for 30 years. Efforts of improving the accuracy and/or certainty of …
electricity markets for 30 years. Efforts of improving the accuracy and/or certainty of …
Heating and cooling loads forecasting for residential buildings based on hybrid machine learning applications: A comprehensive review and comparative analysis
A Moradzadeh, B Mohammadi-Ivatloo, M Abapour… - Ieee …, 2021 - ieeexplore.ieee.org
Prediction of building energy consumption plays an important role in energy conservation,
management, and planning. Continuously improving and enhancing the performance of …
management, and planning. Continuously improving and enhancing the performance of …
One dimensional convolutional neural network architectures for wind prediction
S Harbola, V Coors - Energy Conversion and Management, 2019 - Elsevier
This paper proposes two one-dimensional (1D) convolutional neural networks (CNNs) for
predicting dominant wind speed and direction for the temporal wind dataset. The proposed …
predicting dominant wind speed and direction for the temporal wind dataset. The proposed …
Hybrid binary grey wolf with Harris hawks optimizer for feature selection
Despite Grey Wolf Optimizer's (GWO) superior performance in many areas, stagnation in
local optima areas may still be a concern. Several significant GWO factors can be explored …
local optima areas may still be a concern. Several significant GWO factors can be explored …
A novel DWTimesNet-based short-term multi-step wind power forecasting model using feature selection and auto-tuning methods
C Zhang, Y Wang, Y Fu, X Qiao, MS Nazir… - Energy Conversion and …, 2024 - Elsevier
The share of wind power in global electricity generation is increasing year by year, and the
prediction of wind power is a practical and necessary scientific research. In this paper, the …
prediction of wind power is a practical and necessary scientific research. In this paper, the …
[HTML][HTML] Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems
Large scale integration of renewable energy system with classical electrical power
generation system requires a precise balance to maintain and optimize the supply–demand …
generation system requires a precise balance to maintain and optimize the supply–demand …
Hybrid binary whale with harris hawks for feature selection
R Alwajih, SJ Abdulkadir, H Al Hussian, N Aziz… - Neural Computing and …, 2022 - Springer
A tremendous flow of big data has come from the growing use of digital technology and
intelligent systems. This has resulted in an increase in not just the dimensional issues that …
intelligent systems. This has resulted in an increase in not just the dimensional issues that …
Exploring household emission patterns and driving factors in Japan using machine learning methods
Given by the ambitious GHG mitigation targets set by governments worldwide, household is
playing an increasingly important role for reaching listed reduction goals. Consequently, a …
playing an increasingly important role for reaching listed reduction goals. Consequently, a …
Privacy-preserving DDoS attack detection using cross-domain traffic in software defined networks
Existing distributed denial-of-service attack detection in software defined networks (SDNs)
typically perform detection in a single domain. In reality, abnormal traffic usually affects …
typically perform detection in a single domain. In reality, abnormal traffic usually affects …
Wind power prediction using ensemble learning-based models
Wind power is one of the most potential energies and the major available renewable energy
sources. Precisely predicting wind power production is essential for the management and …
sources. Precisely predicting wind power production is essential for the management and …