Machine learning driven smart electric power systems: Current trends and new perspectives
MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
Taxonomy research of artificial intelligence for deterministic solar power forecasting
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …
stochastic and volatile nature of solar power pose significant challenges to the reliable …
Short-term photovoltaic power forecasting using an LSTM neural network and synthetic weather forecast
MS Hossain, H Mahmood - Ieee Access, 2020 - ieeexplore.ieee.org
In this paper, a forecasting algorithm is proposed to predict photovoltaic (PV) power
generation using a long short term memory (LSTM) neural network (NN). A synthetic …
generation using a long short term memory (LSTM) neural network (NN). A synthetic …
Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction …
J Qu, Z Qian, Y Pei - Energy, 2021 - Elsevier
Accurate forecasting of photovoltaic power plays a pivotal role in the integration, operation,
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
Day-ahead photovoltaic power forecasting approach based on deep convolutional neural networks and meta learning
The outputs of photovoltaic (PV) power are random and uncertain due to the variations of
meteorological elements, which may disturb the safety and stability of power system …
meteorological elements, which may disturb the safety and stability of power system …
Reviewing the peer-to-peer transactive energy market: Trading environment, optimization methodology, and relevant resources
Y Xia, Q Xu, S Li, R Tang, P Du - Journal of Cleaner Production, 2023 - Elsevier
With the high penetration of renewable energy resources on the demand side, peer-to-peer
(P2P) energy sharing has emerged as a promising method for consuming the surplus …
(P2P) energy sharing has emerged as a promising method for consuming the surplus …
Integrating model-driven and data-driven methods for power system frequency stability assessment and control
With increase of practical power system complexity, power system online stability
assessment and control is more and more important. Application of the traditional model …
assessment and control is more and more important. Application of the traditional model …
An improved moth-flame optimization algorithm for support vector machine prediction of photovoltaic power generation
GQ Lin, LL Li, ML Tseng, HM Liu, DD Yuan… - Journal of Cleaner …, 2020 - Elsevier
With the expansion of grid-connected solar power generation, the variability of photovoltaic
power generation has become increasingly pronounced. Accurate photovoltaic output …
power generation has become increasingly pronounced. Accurate photovoltaic output …
Solar irradiance forecasting based on direct explainable neural network
As the penetration of solar energy into electrical power and energy system expands in
recent years over the world, accurate solar irradiance forecasting is becoming highly …
recent years over the world, accurate solar irradiance forecasting is becoming highly …
Ultra-short-term spatiotemporal forecasting of renewable resources: An attention temporal convolutional network-based approach
J Liang, W Tang - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
The rapid increase in the penetration of renewable energy resources characterized by high
variability and uncertainty is bringing new challenges to the power system operation. To …
variability and uncertainty is bringing new challenges to the power system operation. To …