A survey on information communication technologies in modern demand-side management for smart grids: Challenges, solutions, and opportunities
D Said - IEEE engineering management review, 2022 - ieeexplore.ieee.org
The energy transition-revolution paradigm is coming with a new vision of interaction models
to smartly manage the energy and data exchanged between all participants in the whole …
to smartly manage the energy and data exchanged between all participants in the whole …
Microgrid energy management with energy storage systems: A review
Microgrids (MGs) are playing a fundamental role in the transition of energy systems towards
a low carbon future due to the advantages of a highly efficient network architecture for …
a low carbon future due to the advantages of a highly efficient network architecture for …
Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting
Due to global warming and climate changes, buildings including residential and commercial
are significant contributors to energy consumption. To this end, net zero energy building …
are significant contributors to energy consumption. To this end, net zero energy building …
Optimal scheduling of isolated microgrids using automated reinforcement learning-based multi-period forecasting
Y Li, R Wang, Z Yang - IEEE Transactions on Sustainable …, 2021 - ieeexplore.ieee.org
In order to reduce the negative impact of the uncertainty of load and renewable energies
outputs on microgrid operation, an optimal scheduling model is proposed for isolated …
outputs on microgrid operation, an optimal scheduling model is proposed for isolated …
A stacked GRU-RNN-based approach for predicting renewable energy and electricity load for smart grid operation
Predictions of renewable energy (RE) generation and electricity load are critical to smart grid
operation. However, the prediction task remains challenging due to the intermittent and …
operation. However, the prediction task remains challenging due to the intermittent and …
Reinforcement learning techniques for optimal power control in grid-connected microgrids: A comprehensive review
Utility grids are undergoing several upgrades. Distributed generators that are supplied by
intermittent renewable energy sources (RES) are being connected to the grids. As RES get …
intermittent renewable energy sources (RES) are being connected to the grids. As RES get …
Energy management in power distribution systems: Review, classification, limitations and challenges
Energy management in distribution systems has gained attention in recent years.
Coordination of electricity generation and consumption is crucial to save energy, reduce …
Coordination of electricity generation and consumption is crucial to save energy, reduce …
Internet of things energy system: Smart applications, technology advancement, and open issues
The internet of things (IoT) is a distributed heterogeneous network of lightweight nodes with
very minimal power and storage. The IoT energy system for smart applications such as smart …
very minimal power and storage. The IoT energy system for smart applications such as smart …
Forecasting energy generation in large photovoltaic plants using radial belief neural network
Y Natarajan, S Kannan, C Selvaraj… - … : Informatics and Systems, 2021 - Elsevier
Forecasting the energy generation from the solar power is considered challenging due to
inaccuracies in forecasting, reliability issues and substantial economic losses in power …
inaccuracies in forecasting, reliability issues and substantial economic losses in power …
Adaptive and predictive energy management strategy for real-time optimal power dispatch from VPPs integrated with renewable energy and energy storage
Virtual power plants (VPPs) have become a driving force for the decentralized energy
industry, due to their efficient management and control of distributed energy resources. Most …
industry, due to their efficient management and control of distributed energy resources. Most …