Load forecasting models in smart grid using smart meter information: a review
The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …
the reliability and sustainability of power supply by operating in self-control mode to find and …
Deep learning for renewable energy forecasting: A taxonomy, and systematic literature review
C Ying, W Wang, J Yu, Q Li, D Yu, J Liu - Journal of Cleaner Production, 2023 - Elsevier
In order to identify power production and demand in realtime for efficient and dependable
management for diverse renewable energy systems, precise and intuitive renewable energy …
management for diverse renewable energy systems, precise and intuitive renewable energy …
[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 …
Privacy-preserving and communication-efficient energy prediction scheme based on federated learning for smart grids
Energy forecasting is important because it enables infrastructure planning and power
dispatching while reducing power outages and equipment failures. It is well-known that …
dispatching while reducing power outages and equipment failures. It is well-known that …
A novel sequence to sequence data modelling based CNN-LSTM algorithm for three years ahead monthly peak load forecasting
Long-term load forecasting (LTLF) models play an important role in the strategic planning of
power systems around the globe. Obtaining correct decisions on power network expansions …
power systems around the globe. Obtaining correct decisions on power network expansions …
[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 …
A survey of power system state estimation using multiple data sources: PMUs, SCADA, AMI, and beyond
State estimation (SE) is indispensable for the situational awareness of power systems.
Conventional SE is fed by measurements collected from the supervisory control and data …
Conventional SE is fed by measurements collected from the supervisory control and data …
An improved encoder-decoder-based CNN model for probabilistic short-term load and PV forecasting
M Jurado, M Samper, R Rosés - Electric Power Systems Research, 2023 - Elsevier
Integrating distributed energy resources (DER) such as distributed generation, demand
response, and plug-in electric vehicles is one of the major causes of fluctuating and …
response, and plug-in electric vehicles is one of the major causes of fluctuating and …
[HTML][HTML] Multifaceted impacts of widespread renewable energy integration on socio-economic, ecological, and regional development
Clean and sustainable energy has become a main objective in the modern world. However,
achieving clean and sustainable energy required active participation from customers and …
achieving clean and sustainable energy required active participation from customers and …
FPSeq2Q: Fully parameterized sequence to quantile regression for net-load forecasting with uncertainty estimates
The increased penetration of Renewable Energy Sources (RES) as part of a decentralized
and distributed power system makes net-load forecasting a critical component in the …
and distributed power system makes net-load forecasting a critical component in the …