[HTML][HTML] Highly accurate peak and valley prediction short-term net load forecasting approach based on decomposition for power systems with high PV penetration
The increasing penetration of photovoltaic has been resha** the electricity net load curve,
which has a significant impact on power system operation and short-term dispatch …
which has a significant impact on power system operation and short-term dispatch …
[HTML][HTML] Short-term electric net load forecasting for solar-integrated distribution systems based on Bayesian neural networks and statistical post-processing
The increasing integration of variable renewable technologies at distribution feeders, mainly
solar photovoltaic (PV) systems, presents new challenges to grid operators for accurately …
solar photovoltaic (PV) systems, presents new challenges to grid operators for accurately …
Quantile-mixer: A novel deep learning approach for probabilistic short-term load forecasting
As the power grid becomes more complex and dynamic, accurate short-term load
forecasting (STLF) with probabilistic information is a prerequisite for various smart grid …
forecasting (STLF) with probabilistic information is a prerequisite for various smart grid …
Short-term electricity-load forecasting by deep learning: A comprehensive survey
Short-Term Electricity-Load Forecasting (STELF) refers to the prediction of the immediate
demand (in the next few hours to several days) for the power system. Various external …
demand (in the next few hours to several days) for the power system. Various external …
Data driven net load uncertainty quantification for cloud energy storage management in residential microgrid
Residential communities are increasingly adopting renewable energy sources (RES) to
minimize energy consumption costs. However, these RES are weather-dependent and …
minimize energy consumption costs. However, these RES are weather-dependent and …
Probabilistic multi-energy load forecasting for integrated energy system based on Bayesian transformer network
Probabilistic multi-energy load forecasting in an integrated energy system is very complex,
because it needs to consider the following three aspects simultaneously: 1) Complex …
because it needs to consider the following three aspects simultaneously: 1) Complex …
Direct short-term net load forecasting based on machine learning principles for solar-integrated microgrids
Accurate net load forecasting is a cost-effective technique, crucial for the planning, stability,
reliability, and integration of variable solar photovoltaic (PV) systems in modern power …
reliability, and integration of variable solar photovoltaic (PV) systems in modern power …
Residential net load interval prediction based on stacking ensemble learning
In response to the high uncertainty associated with residential net load due to the coupling
of distributed photovoltaic generation and user demand, this paper proposed a novel cluster …
of distributed photovoltaic generation and user demand, this paper proposed a novel cluster …
Metaprobformer for charging load probabilistic forecasting of electric vehicle charging stations
The penetration of electric vehicles (EV) has been increasing rapidly in recent years. Electric
vehicle charging load poses a huge demand on the power grids. The forecasting for electric …
vehicle charging load poses a huge demand on the power grids. The forecasting for electric …
[HTML][HTML] Evaluation of TerraClimate gridded data in investigating the changes of reference evapotranspiration in different climates of Iran
K Solaimani, SB Ahmadi - Journal of Hydrology: Regional Studies, 2024 - Elsevier
Study region Different climates in Iran, including the northwestern regions (cold), southern
coasts (hot and humid) and central regions (hot and dry). Study focus TerraClimate network …
coasts (hot and humid) and central regions (hot and dry). Study focus TerraClimate network …