Control of doubly fed induction generator for power quality improvement: an overview
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 …
The integration of wind power into electric grids poses unique challenges because of its …
[HTML][HTML] Combing data-driven and model-driven methods for high proportion renewable energy distribution network reliability evaluation
To accurately evaluate the reliability of the renewable energy distribution network, a
combined data-driven and model-driven method of distribution network reliability evaluation …
combined data-driven and model-driven method of distribution network reliability evaluation …
[HTML][HTML] Probabilistic optimal power flow solution using a novel hybrid metaheuristic and machine learning algorithm
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 …
(ML) approach and transient search optimization (TSO) to solve the optimal power flow …
Industrial peak shaving with battery storage using a probabilistic forecasting approach: Economic evaluation of risk attitude
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 …
the notion of risk attitude in the context of joint industrial peak shaving and frequency …
A novel hybrid model based on evolving multi-quantile long and short-term memory neural network for ultra-short-term probabilistic forecasting of photovoltaic power
J Zhu, Y He - Applied Energy, 2025 - Elsevier
Probabilistic forecasting is extremely crucial in eliminating uncertainty in photovoltaic (PV)
power generation. Quantile regression long and short-term memory neural network …
power generation. Quantile regression long and short-term memory neural network …
Dynamic modeling and uncertainty quantification of district heating systems considering renewable energy access
X Lin, Y Mao, J Chen, W Zhong - Applied Energy, 2023 - Elsevier
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 …
energy with fossil energy and achieving flexible energy consumption. Considering the …
Using open data for modeling and simulation of the all electrical society in eASiMOV
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 …
Society (AES), which is defined by a very high number of active prosumers in the distribution …
Cumulant Learning: Highly Accurate and Computationally Efficient Load Pattern Recognition Method for Probabilistic STLF at the LV Level
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 …
forecasting to facilitate the management of low voltage networks and account for future load …
Probabilistic power flow computation using nested point estimate method
Q ** in Evolutionary Algorithms for Energy Hub Scheduling
Abstract The integration of Renewable Energy Resources into the existing electricity grid to
reduce Greenhouse Gas emissions raises several challenges, such as volatile generation …
reduce Greenhouse Gas emissions raises several challenges, such as volatile generation …