Comprehensive Review of Artificial Intelligence Applications in Smart Grid Operations
A Meydani, H Shahinzadeh… - … on Technology and …, 2024 - ieeexplore.ieee.org
The present electric power system is seeing a significant transition towards the adoption of
Smart Grids (SGs), which are viewed as a potential approach to improve grid stability and …
Smart Grids (SGs), which are viewed as a potential approach to improve grid stability and …
Wind Power Forecasting in the presence of data scarcity: A very short-term conditional probabilistic modeling framework
The uncertainty of wind power (WP) poses a significant challenge to power systems with a
high percentage of WP. Accurate WP forecasting is an important approach to mitigate this …
high percentage of WP. Accurate WP forecasting is an important approach to mitigate this …
Very short-term probabilistic prediction of PV based on multi-period error distribution
As the penetration rate of photovoltaic (PV) in the grid increases, enormous challenges have
been brought into power grid dispatcher's operation. Efficient and accurate PV power …
been brought into power grid dispatcher's operation. Efficient and accurate PV power …
Nonparametric probabilistic prediction of regional PV outputs based on granule-based clustering and direct optimization programming
Regional photovoltaic (PV) power prediction plays an important role in power system
planning and operation. To effectively improve the performance of prediction intervals (PIs) …
planning and operation. To effectively improve the performance of prediction intervals (PIs) …
Very short-term probabilistic prediction for regional wind power generation based on OPNPIs
Y Zhou, Y Sun, S Wang, RJ Mahfoud… - CSEE Journal of …, 2024 - ieeexplore.ieee.org
Due to the uncertainty and fluctuation of wind power generation, probabilistic prediction for
regional wind power generation is critical to accurately quantify the uncertainty of …
regional wind power generation is critical to accurately quantify the uncertainty of …
Research on a Deep Ensemble Learning Model for the Ultra-Short-Term Probabilistic Prediction of Wind Power
Y Zhou, F Wei, K Kuang, RJ Mahfoud - Electronics, 2024 - mdpi.com
An accurate method for predicting wind power is crucial in effectively mitigating wind energy
fluctuations and ensuring a stable power supply. Nevertheless, the inadequacy of the …
fluctuations and ensuring a stable power supply. Nevertheless, the inadequacy of the …
Machine learning application to power system forecasting
In recent days, analysis of renewable-rich power systems has shown greater interest as the
integration of renewable generations is encouraged nationwide both at transmission and …
integration of renewable generations is encouraged nationwide both at transmission and …
Improved quantile regression based approach for renewable power generation interval prediction on islands
Renewable power generation prediction plays an important role in power system control,
scheduling, and planning. The uncertain and fluctuating characteristics of island renewable …
scheduling, and planning. The uncertain and fluctuating characteristics of island renewable …
Short-term wind-PV-wave power probabilistic prediction based on an improved sequence-to-sequence attention model
Y Sun, H Chen, Y Xu, F Wang - CSEE Journal of Power and …, 2024 - ieeexplore.ieee.org
The misjudgment of power generation poses a potential threat to the secure and stable
operations of power systems. Probabilistic power prediction of renewable energies is …
operations of power systems. Probabilistic power prediction of renewable energies is …
Very short-term prediction for wind power based on BiLSTM-Attention
S Wang, Y Sun, J Wang, D Hou… - … Power and Energy …, 2021 - ieeexplore.ieee.org
With the increasing permeability of wind power (WP) in power systems, WP randomicity
bring enormous difficulty to the dispatching departments of power grid. Exact description of …
bring enormous difficulty to the dispatching departments of power grid. Exact description of …