[HTML][HTML] Increasing the resolution of solar and wind time series for energy system modeling: A review
Bottom-up energy system models are often based on hourly time steps due to limited
computational tractability or data availability. However, in order to properly assess the …
computational tractability or data availability. However, in order to properly assess the …
Generative ai and process systems engineering: The next frontier
This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …
such as large language models (LLMs), can enhance solution methodologies within process …
Planning of distributed renewable energy systems under uncertainty based on statistical machine learning
X Fu, X Wu, C Zhang, S Fan… - Protection and Control of …, 2022 - ieeexplore.ieee.org
The development of distributed renewable energy, such as photovoltaic power and wind
power generation, makes the energy system cleaner, and is of great significance in reducing …
power generation, makes the energy system cleaner, and is of great significance in reducing …
Data-driven scenario generation of renewable energy production based on controllable generative adversarial networks with interpretability
W Dong, X Chen, Q Yang - Applied Energy, 2022 - Elsevier
Efficient and reliable scenario generation is of paramount importance in the modeling of
uncertainties and fluctuations of wind and solar based renewable energy production for …
uncertainties and fluctuations of wind and solar based renewable energy production for …
Improving the accuracy of global forecasting models using time series data augmentation
Forecasting models that are trained across sets of many time series, known as Global
Forecasting Models (GFM), have shown recently promising results in forecasting …
Forecasting Models (GFM), have shown recently promising results in forecasting …
A deep generative model for probabilistic energy forecasting in power systems: normalizing flows
Greater direct electrification of end-use sectors with a higher share of renewables is one of
the pillars to power a carbon-neutral society by 2050. However, in contrast to conventional …
the pillars to power a carbon-neutral society by 2050. However, in contrast to conventional …
Typical wind power scenario generation for multiple wind farms using conditional improved Wasserstein generative adversarial network
Because of environmental benefits, wind power is taking an increasing role meeting
electricity demand. However, wind power tends to exhibit large uncertainty and is largely …
electricity demand. However, wind power tends to exhibit large uncertainty and is largely …
Conditional style-based generative adversarial networks for renewable scenario generation
R Yuan, B Wang, Y Sun, X Song… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Day-ahead scenario generationof renewable power plays an important role in short-term
power system operations due to considerable output uncertainty included. In this paper, a …
power system operations due to considerable output uncertainty included. In this paper, a …
Multi-objective wind power scenario forecasting based on PG-GAN
R Yuan, B Wang, Z Mao, J Watada - Energy, 2021 - Elsevier
Accurate scenario forecasting of wind power is crucial to the day-ahead scheduling of power
systems with large-scale renewable generation. However, the intermittence and fluctuation …
systems with large-scale renewable generation. However, the intermittence and fluctuation …
Stochastic optimization and scenario generation for peak load shaving in Smart District microgrid: sizing and operation
F Bagheri, H Dagdougui, M Gendreau - Energy and Buildings, 2022 - Elsevier
Microgrids play an essential role in the integration of multiple distributed energy resources in
buildings. They can meet critical loads in buildings while reducing peak loads and …
buildings. They can meet critical loads in buildings while reducing peak loads and …