Energy Forecasting: A Comprehensive Review of Techniques and Technologies

Energy Forecasting: A Comprehensive Review of Techniques and Technologies

Distribution System Operators (DSOs) and Aggregators benefit from novel energy forecasting (EF) approaches. Improved forecasting accuracy may make it easier to deal with energy imbalances between generation and consumption. It also helps operations such as Demand Response Management (DRM) in Smart G...

Full description

Bibliographic Details
Main Authors:	Aristeidis Mystakidis, Paraskevas Koukaras, Nikolaos Tsalikidis, Dimosthenis Ioannidis, Christos Tjortjis
Format:	Article
Language:	English
Published:	MDPI AG 2024-03-01
Series:	Energies
Subjects:	forecasting time-series analysis energy load machine learning artificial neural networks statistical methods
Online Access:	https://www.mdpi.com/1996-1073/17/7/1662

Similar Items

Optimizing Building Short-Term Load Forecasting: A Comparative Analysis of Machine Learning Models
by: Paraskevas Koukaras, et al.
Published: (2024-03-01)

Urban Traffic Congestion Prediction: A Multi-Step Approach Utilizing Sensor Data and Weather Information
by: Nikolaos Tsalikidis, et al.
Published: (2024-01-01)

A Tri-Model Prediction Approach for COVID-19 ICU Bed Occupancy: A Case Study
by: Nikolaos Stasinos, et al.
Published: (2023-03-01)

Integrating Blockchain in Smart Grids for Enhanced Demand Response: Challenges, Strategies, and Future Directions
by: Paraskevas Koukaras, et al.
Published: (2024-02-01)

Forecasting of Electric Load Using a Hybrid LSTM-Neural Prophet Model
by: Md Jamal Ahmed Shohan, et al.
Published: (2022-03-01)

Comparison of time series forecasting with artificial neural network and statistical approach
by: Michael Štencl, et al.
Published: (2011-01-01)

SmartBuild RecSys: A Recommendation System Based on the Smart Readiness Indicator for Energy Efficiency in Buildings
by: Muhammad Talha Siddique, et al.
Published: (2023-10-01)

A Methodology Integrating the Quantitative Assessment of Energy Efficient Operation and Occupant Needs into the Smart Readiness Indicator
by: Muhammad Talha Siddique, et al.
Published: (2023-10-01)

A Machine Learning Pipeline for Forecasting Time Series in the Banking Sector
by: Olga Gorodetskaya, et al.
Published: (2021-12-01)

Multi-Step Energy Demand and Generation Forecasting with Confidence Used for Specification-Free Aggregate Demand Optimization
by: Nikolaos Kolokas, et al.
Published: (2021-05-01)

Forecasting of hourly electric load in Colombia using artificial neural networks
by: Santiago Medina Hurtado, et al.
Published: (2012-11-01)

The method of residual-based bootstrap averaging of the forecast ensemble
by: Vera Ivanyuk
Published: (2023-01-01)

A Methodology for Energy Load Profile Forecasting Based on Intelligent Clustering and Smoothing Techniques
by: Jamer Jiménez Mares, et al.
Published: (2020-08-01)

A novel spatial electric load forecasting method based on LDTW and GCN
by: Minjie Wei, et al.
Published: (2024-02-01)

Exploratory Data Analysis Based Short-Term Electrical Load Forecasting: A Comprehensive Analysis
by: Umar Javed, et al.
Published: (2021-09-01)

Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings
by: Juan Prieto, et al.
Published: (2013-04-01)

Comprehensive review of load forecasting with emphasis on intelligent computing approaches
by: Hong Wang, et al.
Published: (2022-11-01)

A Data-Driven Model to Forecast Multi-Step Ahead Time Series of Turkish Daily Electricity Load
by: Kamil Demirberk Ünlü
Published: (2022-05-01)

NEURAL NETWORK FORECASTING OF ENERGY CONSUMPTION OF A METALLURGICAL ENTERPRISE
by: Anna Bakurova, et al.
Published: (2021-03-01)

Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead
by: Saima Akhtar, et al.
Published: (2023-05-01)

Bayesian Optimization-Based LSTM for Short-Term Heating Load Forecasting
by: Binglin Li, et al.
Published: (2023-08-01)

Towards Energy Efficiency: Forecasting Indoor Temperature via Multivariate Analysis
by: Juan Pardo, et al.
Published: (2013-09-01)

Short Term load forecasting by means of Load Time Series Decomposition and Neural Network
by: روح‌الله فیروزنیا, et al.
Published: (2008-05-01)

A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models
by: Abdullah Al Mamun, et al.
Published: (2020-01-01)

A Flexible Deep Learning Method for Energy Forecasting
by: Ihab Taleb, et al.
Published: (2022-05-01)

Heating Load Forecasting for Combined Heat and Power Plants Via Strand-Based LSTM
by: Junyu Liu, et al.
Published: (2020-01-01)

A Single Scalable LSTM Model for Short-Term Forecasting of Massive Electricity Time Series
by: Andrés M. Alonso, et al.
Published: (2020-10-01)

Short-Term Load Forecasting Using Neural Networks with Pattern Similarity-Based Error Weights
by: Grzegorz Dudek
Published: (2021-05-01)

Electricity price forecasting using artificial neural networks
by: Fernando Villada, et al.
Published: (2014-02-01)

Considering seasonal fluctuations on balancing time series with the use of artificial neural networks when forecasting US imports from the PRC
by: Vrbka Jaromír, et al.
Published: (2020-01-01)

Time series forecasting of airline passenger no-shows using fir neural network /
by: 603963 Muhammad Zaly Shah Muhammad Hussein
Published: (2002)

Examining the intricate relationships between forecasting errors, autocorrelation and total cost /
by: 410958 Lee, T. S., et al.

Systematic Development of Short-Term Load Forecasting Models for the Electric Power Utilities: The Case of Pakistan
by: Aneeque A. Mir, et al.
Published: (2021-01-01)

Electricity load forecasting using a deep neuralnetwork
by: Chawalit Jeenanunta
Published: (2019-03-01)

A Transformer-Based Multi-Entity Load Forecasting Method for Integrated Energy Systems
by: Zhiyu Wang, et al.
Published: (2022-07-01)

Time series forecasting of airline passenger no-shows using fir neural network [microfilm] /
by: 603963 Muhammad Zaly Shah Muhammad Hussein
Published: (2002)

Short-Term Load Forecasting of the Greek Electricity System
by: George Stamatellos, et al.
Published: (2023-02-01)

Improved Short-Term Load Forecasting Based on Two-Stage Predictions with Artificial Neural Networks in a Microgrid Environment
by: Jaime Lloret, et al.
Published: (2013-08-01)

A Method for the Monthly Electricity Demand Forecasting in Colombia based on Wavelet Analysis and a Nonlinear Autoregressive Model
by: Cristhian Moreno-Chaparro, et al.
Published: (2011-12-01)

A modified deep residual network for short-term load forecasting
by: V. Y. Kondaiah, et al.
Published: (2022-10-01)