A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids

S Aslam, H Herodotou, SM Mohsin, N Javaid… - … and Sustainable Energy …, 2021 - Elsevier
Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …

Reinforcement learning techniques for optimal power control in grid-connected microgrids: A comprehensive review

EO Arwa, KA Folly - Ieee Access, 2020 - ieeexplore.ieee.org
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 …

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 …

A stacked GRU-RNN-based approach for predicting renewable energy and electricity load for smart grid operation

M Xia, H Shao, X Ma… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …

Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting

SU Khan, N Khan, FUM Ullah, MJ Kim, MY Lee… - Energy and …, 2023 - Elsevier
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 …

Internet of things energy system: Smart applications, technology advancement, and open issues

AH Mohd Aman, N Shaari… - International Journal of …, 2021 - Wiley Online Library
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 …

Energy management in power distribution systems: Review, classification, limitations and challenges

MS Alam, SA Arefifar - IEEE Access, 2019 - ieeexplore.ieee.org
Energy management in distribution systems has gained attention in recent years.
Coordination of electricity generation and consumption is crucial to save energy, reduce …

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 …

Microgrid energy management with energy storage systems: A review

X Liu, T Zhao, H Deng, P Wang, J Liu… - CSEE Journal of …, 2022 - ieeexplore.ieee.org
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 …

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 …