Wind energy outweighs other kinds of renewable energy for endless harvestable potential.
The integration of wind power into electric grids poses unique challenges because of its …

To accurately evaluate the reliability of the renewable energy distribution network, a
combined data-driven and model-driven method of distribution network reliability evaluation …

Industrial peak shaving is a regularly discussed application of battery storage. We introduce
the notion of risk attitude in the context of joint industrial peak shaving and frequency …

This paper proposes a novel hybrid optimization technique based on a machine learning
(ML) approach and transient search optimization (TSO) to solve the optimal power flow …

The district heating system (DHS) is one of the essential carriers for coordinating renewable
energy with fossil energy and achieving flexible energy consumption. Considering the …

The present study examines a future energy systems scenario, the so-called All Electrical
Society (AES), which is defined by a very high number of active prosumers in the distribution …

Probabilistic forecasting is extremely crucial in eliminating uncertainty in photovoltaic (PV)
power generation. Quantile regression long and short-term memory neural network …

The probabilistic power flow (PPF) computation involves quantifying and propagating
uncertainty over hundreds of variables. Zhao's point estimate method (PEM) has been …

This paper proposes a new load pattern recognition method for probabilistic short-term load
forecasting to facilitate the management of low voltage networks and account for future load …

In recent years, the increasing integration of renewable energy and electric vehicles has
exacerbated uncertainties in power systems. Operators are interested in identifying potential …