A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
Load forecasting techniques and their applications in smart grids
The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads
Z Zhang, WC Hong - Knowledge-Based Systems, 2021 - Elsevier
Accurate electric load forecasting is critical in guaranteeing the efficiency of the load
dispatch and supply by a power system, which prevents the wasting of electricity and …
dispatch and supply by a power system, which prevents the wasting of electricity and …
Forecasting short-term electricity load using hybrid support vector regression with grey catastrophe and random forest modeling
GF Fan, M Yu, SQ Dong, YH Yeh, WC Hong - Utilities Policy, 2021 - Elsevier
This paper develops a novel short-term load forecasting model that hybridizes several
machine learning methods, such as support vector regression (SVR), grey catastrophe (GC …
machine learning methods, such as support vector regression (SVR), grey catastrophe (GC …
A multi-energy load forecasting method based on parallel architecture CNN-GRU and transfer learning for data deficient integrated energy systems
C Li, G Li, K Wang, B Han - Energy, 2022 - Elsevier
In the integrated energy system with small samples, insufficient data limits the accuracy of
energy load forecasting and thereafter affects the system's economic operation and optimal …
energy load forecasting and thereafter affects the system's economic operation and optimal …
A review on time series forecasting techniques for building energy consumption
Energy consumption forecasting for buildings has immense value in energy efficiency and
sustainability research. Accurate energy forecasting models have numerous implications in …
sustainability research. Accurate energy forecasting models have numerous implications in …
Short-term electrical load forecasting using the Support Vector Regression (SVR) model to calculate the demand response baseline for office buildings
Demand Response (DR) aims at improving the operation efficiency of power plants and
grids, and it constitutes an effective means of reducing grid risk during peak periods to …
grids, and it constitutes an effective means of reducing grid risk during peak periods to …
Deep-learning forecasting method for electric power load via attention-based encoder-decoder with bayesian optimization
Short-term electrical load forecasting plays an important role in the safety, stability, and
sustainability of the power production and scheduling process. An accurate prediction of …
sustainability of the power production and scheduling process. An accurate prediction of …
Fastest‐growing source prediction of US electricity production based on a novel hybrid model using wavelet transform
W Qiao, Z Li, W Liu, E Liu - International Journal of Energy …, 2022 - Wiley Online Library
Electricity is an important indicator for economic development, especially electricity
production (EP), which is electricity industry managers making strategic decisions. There are …
production (EP), which is electricity industry managers making strategic decisions. There are …
Electric load forecasting by complete ensemble empirical mode decomposition adaptive noise and support vector regression with quantum-based dragonfly algorithm
Z Zhang, WC Hong - Nonlinear dynamics, 2019 - Springer
Accurate electric load forecasting can provide critical support to makers of energy policy and
managers of power systems. The support vector regression (SVR) model can be hybridized …
managers of power systems. The support vector regression (SVR) model can be hybridized …