AI models for green communications towards 6G

B Mao, F Tang, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

Distributed energy resources and the application of AI, IoT, and blockchain in smart grids

NM Kumar, AA Chand, M Malvoni, KA Prasad… - Energies, 2020 - mdpi.com
Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-
way flow of electricity and data between the peers within the electricity system networks …

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 …

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 …

Deep learning for time series forecasting: The electric load case

A Gasparin, S Lukovic, C Alippi - CAAI Transactions on …, 2022 - Wiley Online Library
Management and efficient operations in critical infrastructures such as smart grids take huge
advantage of accurate power load forecasting, which, due to its non‐linear nature, remains a …

A survey on electric power demand forecasting: future trends in smart grids, microgrids and smart buildings

L Hernandez, C Baladron, JM Aguiar… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
Recently there has been a significant proliferation in the use of forecasting techniques,
mainly due to the increased availability and power of computation systems and, in particular …

Energy models for demand forecasting—A review

L Suganthi, AA Samuel - Renewable and sustainable energy reviews, 2012 - Elsevier
Energy is vital for sustainable development of any nation–be it social, economic or
environment. In the past decade energy consumption has increased exponentially globally …

Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem

P Singh, P Dwivedi - Applied energy, 2018 - Elsevier
Due to the explosion in restructuring of power markets within a deregulated economy,
competitive power market needs to minimize their required generation reserve gaps …

Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique

F Zhang, C Deb, SE Lee, J Yang, KW Shah - Energy and Buildings, 2016 - Elsevier
Electricity load forecasting is crucial for effective operation and management of buildings.
Support Vector Regression (SVR) have been successfully used in solving nonlinear …

Forecasting with artificial neural networks:: The state of the art

G Zhang, BE Patuwo, MY Hu - International journal of forecasting, 1998 - Elsevier
Interest in using artificial neural networks (ANNs) for forecasting has led to a tremendous
surge in research activities in the past decade. While ANNs provide a great deal of promise …