On the benefits of using metaheuristics in the hyperparameter tuning of deep learning models for energy load forecasting
An effective energy oversight represents a major concern throughout the world, and the
problem has become even more stringent recently. The prediction of energy load and …
problem has become even more stringent recently. The prediction of energy load and …
A comprehensive review on deep learning approaches for short-term load forecasting
Y Eren, İ Küçükdemiral - Renewable and Sustainable Energy Reviews, 2024 - Elsevier
The balance between supplied and demanded power is a crucial issue in the economic
dispatching of electricity energy. With the emergence of renewable sources and data-driven …
dispatching of electricity energy. With the emergence of renewable sources and data-driven …
A deep learning framework using multi-feature fusion recurrent neural networks for energy consumption forecasting
L Fang, B He - Applied Energy, 2023 - Elsevier
Accurate energy load forecasting can not only provide favorable conditions for ensuring
energy security but also reduce carbon emissions and thereby slow down the process of …
energy security but also reduce carbon emissions and thereby slow down the process of …
A new intelligent hybrid forecasting method for power load considering uncertainty
GF Fan, YY Han, JJ Wang, HL Jia, LL Peng… - Knowledge-Based …, 2023 - Elsevier
Accurate load forecasting plays an important role in promoting low-carbon energy and high-
quality utilization of electricity, as well as carbon reduction and safety in energy and power …
quality utilization of electricity, as well as carbon reduction and safety in energy and power …
An improved encoder-decoder-based CNN model for probabilistic short-term load and PV forecasting
M Jurado, M Samper, R Rosés - Electric Power Systems Research, 2023 - Elsevier
Integrating distributed energy resources (DER) such as distributed generation, demand
response, and plug-in electric vehicles is one of the major causes of fluctuating and …
response, and plug-in electric vehicles is one of the major causes of fluctuating and …
Multivariate Time-Series Forecasting: A Review of Deep Learning Methods in Internet of Things Applications to Smart Cities
V Papastefanopoulos, P Linardatos… - Smart Cities, 2023 - mdpi.com
Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …
conventional networks and services for sustainable growth, optimized resource …
[HTML][HTML] An enhanced CNN-LSTM based multi-stage framework for PV and load short-term forecasting: DSO scenarios
The importance of accurate forecasting in the electric sector has grown due to the increasing
demand and adoption of high volume of Renewable Energy Sources (RES). Short-term …
demand and adoption of high volume of Renewable Energy Sources (RES). Short-term …
Short-term load forecasting of electricity demand for the residential sector based on modelling techniques: a systematic review
In this paper, a systematic literature review is presented, through a survey of the main digital
databases, regarding modelling methods for Short-Term Load Forecasting (STLF) for hourly …
databases, regarding modelling methods for Short-Term Load Forecasting (STLF) for hourly …
Adaptive data decomposition based quantile-long-short-term memory probabilistic forecasting framework for power demand side management of energy system
W Yang, L Jia, Y Xu - Computers and Electrical Engineering, 2023 - Elsevier
Load management can improve the overall benefit of power system through peak cutting
and valley filling, whose performance depends on the accuracy of load forecasting …
and valley filling, whose performance depends on the accuracy of load forecasting …
Review of multiple load forecasting method for integrated energy system
Y Liu, Y Li, G Li, Y Lin, R Wang, Y Fan - Frontiers in Energy Research, 2023 - frontiersin.org
In order to further improve the efficiency of energy utilization, Integrated Energy Systems
(IES) connect various energy systems closer, which has become an important energy …
(IES) connect various energy systems closer, which has become an important energy …