A review on the integration of probabilistic solar forecasting in power systems
As one of the fastest growing renewable energy sources, the integration of solar power
poses great challenges to power systems due to its variable and uncertain nature. As an …
poses great challenges to power systems due to its variable and uncertain nature. As an …
Design of experiments using artificial neural network ensemble for photovoltaic generation forecasting
MO Moreira, PP Balestrassi, AP Paiva… - … and Sustainable Energy …, 2021 - Elsevier
In recent years, renewable and sustainable energy sources have attracted the attention of
various investors and stakeholders, such as energy sector agents and even consumers. It is …
various investors and stakeholders, such as energy sector agents and even consumers. It is …
Model-free renewable scenario generation using generative adversarial networks
Scenario generation is an important step in the operation and planning of power systems
with high renewable penetrations. In this work, we proposed a data-driven approach for …
with high renewable penetrations. In this work, we proposed a data-driven approach for …
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 …
Review of wind power scenario generation methods for optimal operation of renewable energy systems
J Li, J Zhou, B Chen - Applied Energy, 2020 - Elsevier
Scenario generation is an effective method for addressing uncertainties in stochastic
programming for energy systems with integrated wind power. To comprehensively …
programming for energy systems with integrated wind power. To comprehensively …
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 …
A review of scenario analysis methods in planning and operation of modern power systems: Methodologies, applications, and challenges
Addressing the rapidly growing penetration of renewable energy sources and the increasing
variations in loads has been a significant challenge in the planning and operation of modern …
variations in loads has been a significant challenge in the planning and operation of modern …
Short-term optimal operation of hydro-wind-solar hybrid system with improved generative adversarial networks
H Wei, Z Hongxuan, D Yu, W Yiting, D Ling, X Ming - Applied Energy, 2019 - Elsevier
The high penetration of variable renewable energy sources (RESs) has greatly increased
the difficulty in power system scheduling and operation. To fully utilize the complementary …
the difficulty in power system scheduling and operation. To fully utilize the complementary …
A multi-data driven hybrid learning method for weekly photovoltaic power scenario forecast
This paper proposes a multi-data driven hybrid learning method for weekly photovoltaic (PV)
power scenario forecast that is coordinately driven by weather forecasts and historical PV …
power scenario forecast that is coordinately driven by weather forecasts and historical PV …
Machine learning-based utilization of renewable power curtailments under uncertainty by planning of hydrogen systems and battery storages
Increasing wind and solar generation in power grids leads to more renewable power
curtailments in some periods of time due to the fast and unpredictable variations of their …
curtailments in some periods of time due to the fast and unpredictable variations of their …