Deep-learning forecasting method for electric power load via attention-based encoder-decoder with bayesian optimization
Short-term electrical load forecasting plays an important role in the safety, stability, and
sustainability of the power production and scheduling process. An accurate prediction of …
sustainability of the power production and scheduling process. An accurate prediction of …
Co-optimizing virtual power plant services under uncertainty: A robust scheduling and receding horizon dispatch approach
J Naughton, H Wang, M Cantoni… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Market and network integration of distributed energy resources can be facilitated by their
coordination within a virtual power plant (VPP). However, VPP operation subject to network …
coordination within a virtual power plant (VPP). However, VPP operation subject to network …
Review of load data analytics using deep learning in smart grids: Open load datasets, methodologies, and application challenges
MF Elahe, M Jin, P Zeng - International Journal of Energy …, 2021 - Wiley Online Library
The collection and storage of large‐scale load data in a smart grid provide new approaches
for the efficient, economical, and safe operation of power systems. Deep Learning (DL) has …
for the efficient, economical, and safe operation of power systems. Deep Learning (DL) has …
Wasserstein distributionally robust chance-constrained optimization for energy and reserve dispatch: An exact and physically-bounded formulation
In the context of transition towards sustainable, cost-efficient and reliable energy systems,
the improvement of current energy and reserve dispatch models is crucial to properly cope …
the improvement of current energy and reserve dispatch models is crucial to properly cope …
Data-driven scheduling of energy storage in day-ahead energy and reserve markets with probabilistic guarantees on real-time delivery
Energy storage systems (ESS) may provide the required flexibility to cost-effectively
integrate weather-dependent renewable generation, in particular by offering operating …
integrate weather-dependent renewable generation, in particular by offering operating …
A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems
Hydro-wind-solar integrated operation is a promising way to balance the growing amount of
variable renewable energy (RE) and enhance energy utilization efficiency. This study …
variable renewable energy (RE) and enhance energy utilization efficiency. This study …
SAMNet: Toward latency-free non-intrusive load monitoring via multi-task deep learning
Non-intrusive load monitoring (NILM), including state detection and energy disaggregation,
aims to identify the on/off state and energy consumption from the aggregate load of a …
aims to identify the on/off state and energy consumption from the aggregate load of a …
[HTML][HTML] Limiting imbalance settlement costs from variable renewable energy sources in the Nordics: Internal balancing vs. balancing market participation
Due to the market gate closures in the Nordic energy markets, producers with variable
renewable energy (VRE) assets, eg, PV and wind power plants, must forecast their …
renewable energy (VRE) assets, eg, PV and wind power plants, must forecast their …
Interpretable probabilistic forecasting of imbalances in renewable-dominated electricity systems
High penetration of renewable energy such as wind power and photovoltaic (PV) requires
large amounts of flexibility to balance their inherent variability. Making an accurate …
large amounts of flexibility to balance their inherent variability. Making an accurate …
Distributional reinforcement learning-based energy arbitrage strategies in imbalance settlement mechanism
Growth in the penetration of renewable energy sources makes supply more uncertain and
leads to an increase in the system imbalance. This trend, together with the single imbalance …
leads to an increase in the system imbalance. This trend, together with the single imbalance …