Artificial intelligence evolution in smart buildings for energy efficiency
The emerging concept of smart buildings, which requires the incorporation of sensors and
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …
Artificial intelligence for management of variable renewable energy systems: a review of current status and future directions
This review paper provides a summary of methods in which artificial intelligence (AI)
techniques have been applied in the management of variable renewable energy (VRE) …
techniques have been applied in the management of variable renewable energy (VRE) …
A novel multi-time-scale modeling for electric power demand forecasting: From short-term to medium-term horizon
Short-term load forecasting is essential for reliable and economic operation of power
systems. Short-term forecasting covers a range of predictions from a fraction of an hour …
systems. Short-term forecasting covers a range of predictions from a fraction of an hour …
A novel electricity price forecasting approach based on dimension reduction strategy and rough artificial neural networks
An accurate electricity price forecasting (EPF) plays a vital role in the deregulated energy
markets and has a specific effect on optimal management of the power system. Considering …
markets and has a specific effect on optimal management of the power system. Considering …
A combined multivariate model for wind power prediction
The intermittent and fluctuation of wind power has a harmful effect on power grid. To direct
system operators to mitigate the harm, a combined multivariate model is proposed to …
system operators to mitigate the harm, a combined multivariate model is proposed to …
Prediction of li-ion battery state of charge using multilayer perceptron and long short-term memory models
Lithium-ion batteries are used in different applications such as electric vehicles and grid-
scale energy storage. These applications rely greatly on the accurate measurement and …
scale energy storage. These applications rely greatly on the accurate measurement and …
Ultra-short-term wind power combined prediction based on complementary ensemble empirical mode decomposition, whale optimisation algorithm, and elman …
A Zhu, Q Zhao, X Wang, L Zhou - Energies, 2022 - mdpi.com
Accurate wind power forecasting helps relieve the regulation pressure of a power system,
which is of great significance to the power system's operation. However, achieving …
which is of great significance to the power system's operation. However, achieving …
Using vegetation management and LiDAR-derived tree height data to improve outage predictions for electric utilities
The interaction of severe weather, overhead electric infrastructure and surrounding
vegetation contributes to power outages. Given that 90% of storm outages in Connecticut …
vegetation contributes to power outages. Given that 90% of storm outages in Connecticut …
Intelligent islanding detection of multi-distributed generation using artificial neural network based on intrinsic mode function feature
The integration of distributed energy resources (DERs) into distribution networks is
becoming increasingly important, as it supports the continued adoption of renewable power …
becoming increasingly important, as it supports the continued adoption of renewable power …
Predicting thunderstorm-induced power outages to support utility restoration
Strong thunderstorms have substantial impacts on power systems, posing risks and
inconveniences due to power outages. Develo** models predicting the outages before a …
inconveniences due to power outages. Develo** models predicting the outages before a …