An overview of energy demand forecasting methods published in 2005–2015
The importance of energy demand management has been more vital in recent decades as
the resources are getting less, emission is getting more and developments in applying …
the resources are getting less, emission is getting more and developments in applying …
Bayesian forecasting in economics and finance: A modern review
The Bayesian statistical paradigm provides a principled and coherent approach to
probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting …
probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting …
A deep learning model for short-term power load and probability density forecasting
Accurate load forecasting is critical for power system planning and operational decision
making. In this study, we are the first to utilize a deep feedforward network for short-term …
making. In this study, we are the first to utilize a deep feedforward network for short-term …
Intrusion detection in SCADA based power grids: Recursive feature elimination model with majority vote ensemble algorithm
D Upadhyay, J Manero, M Zaman… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We propose an integrated framework for an intrusion detection system for SCADA
(Supervisory Control and Data Acquisition)-based power grids. Our scheme combines RFE …
(Supervisory Control and Data Acquisition)-based power grids. Our scheme combines RFE …
Machine learning ensembles for wind power prediction
J Heinermann, O Kramer - Renewable Energy, 2016 - Elsevier
For a sustainable integration of wind power into the electricity grid, a precise prediction
method is required. In this work, we investigate the use of machine learning ensembles for …
method is required. In this work, we investigate the use of machine learning ensembles for …
Enhanced ensemble structures using wavelet neural networks applied to short-term load forecasting
Load forecasting implies directly in financial return and information for electrical systems
planning. A framework to build wavenet ensemble for short-term load forecasting is …
planning. A framework to build wavenet ensemble for short-term load forecasting is …
Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks
Occupancy behaviour plays an important role in energy consumption in buildings. Currently,
the shallow understanding of occupancy has led to a considerable performance gap …
the shallow understanding of occupancy has led to a considerable performance gap …
Forecasting based on an ensemble autoregressive moving average-adaptive neuro-fuzzy inference system–neural network-genetic algorithm framework
F Prado, MC Minutolo, W Kristjanpoller - Energy, 2020 - Elsevier
This paper proposes a novel ensemble methodology comprising an auto regressive
integrated moving average, artificial neural network, fuzzy inference system model, adaptive …
integrated moving average, artificial neural network, fuzzy inference system model, adaptive …
An ensemble framework for day-ahead forecast of PV output power in smart grids
The uncertainty associated with solar photo-voltaic (PV) power output (PO) is a big
challenge to design, manage and implement effective demand response, and management …
challenge to design, manage and implement effective demand response, and management …
Towards novel deep neuroevolution models: chaotic levy grasshopper optimization for short-term wind speed forecasting
SMJ Jalali, S Ahmadian, M Khodayar… - Engineering with …, 2021 - Springer
High accurate wind speed forecasting plays an important role in ensuring the sustainability
of wind power utilization. Although deep neural networks (DNNs) have been recently …
of wind power utilization. Although deep neural networks (DNNs) have been recently …