A review on time series forecasting techniques for building energy consumption

C Deb, F Zhang, J Yang, SE Lee, KW Shah - Renewable and Sustainable …, 2017 - Elsevier
Energy consumption forecasting for buildings has immense value in energy efficiency and
sustainability research. Accurate energy forecasting models have numerous implications in …

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

MQ Raza, A Khosravi - Renewable and Sustainable Energy Reviews, 2015 - Elsevier
Electrical load forecasting plays a vital role in order to achieve the concept of next
generation power system such as smart grid, efficient energy management and better power …

Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm

A Heydari, MM Nezhad, E Pirshayan, DA Garcia… - Applied Energy, 2020 - Elsevier
Electricity price forecasting is a key aspect for market participants to maximize their
economic efficiency in deregulated markets. Nevertheless, due to its non-linearity and non …

Forecasting methods in energy planning models

KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …

A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with …

F He, J Zhou, Z Feng, G Liu, Y Yang - Applied energy, 2019 - Elsevier
Short-term load forecasting plays an essential role in the safe and stable operation of power
systems and has always been a vital research issue of energy management. In this …

Short term electricity load forecasting using a hybrid model

J Zhang, YM Wei, D Li, Z Tan, J Zhou - Energy, 2018 - Elsevier
Short term electricity load forecasting is one of the most important issue for all market
participants. Short term electricity load is affected by natural and social factors, which makes …

Electric vehicle charging load forecasting: A comparative study of deep learning approaches

J Zhu, Z Yang, M Mourshed, Y Guo, Y Zhou, Y Chang… - Energies, 2019 - mdpi.com
Load forecasting is one of the major challenges of power system operation and is crucial to
the effective scheduling for economic dispatch at multiple time scales. Numerous load …

Day-ahead load forecast using random forest and expert input selection

A Lahouar, JBH Slama - Energy Conversion and Management, 2015 - Elsevier
The electrical load forecast is getting more and more important in recent years due to the
electricity market deregulation and integration of renewable resources. To overcome the …

A data-driven strategy for short-term electric load forecasting using dynamic mode decomposition model

N Mohan, KP Soman, SS Kumar - Applied energy, 2018 - Elsevier
The electric load forecasting is extremely important for energy demand management,
stability and security of power systems. A sufficiently accurate, robust and fast short-term …

Meta-ANN–A dynamic artificial neural network refined by meta-learning for Short-Term Load Forecasting

X **ao, H Mo, Y Zhang, G Shan - energy, 2022 - Elsevier
In this paper a dynamic Artificial Neural Network (ANN) model called Meta-ANN is
developed for forecasting the short-term grid load. The primary ingredient of the model is a …