AI models for green communications towards 6G
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 …
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
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 …
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 …
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 …
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
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 …
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
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 …
mainly due to the increased availability and power of computation systems and, in particular …
Energy models for demand forecasting—A review
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 …
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
Due to the explosion in restructuring of power markets within a deregulated economy,
competitive power market needs to minimize their required generation reserve gaps …
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
Electricity load forecasting is crucial for effective operation and management of buildings.
Support Vector Regression (SVR) have been successfully used in solving nonlinear …
Support Vector Regression (SVR) have been successfully used in solving nonlinear …
Forecasting with artificial neural networks:: The state of the art
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 …
surge in research activities in the past decade. While ANNs provide a great deal of promise …