scholarly journals Large-scale integration of renewable energies and impact on storage demand in a European renewable power system of 2050—Sensitivity study

2016 ◽  
Vol 6 ◽  
pp. 1-10 ◽  
Author(s):  
Christian Bussar ◽  
Philipp Stöcker ◽  
Zhuang Cai ◽  
Luiz Moraes Jr. ◽  
Dirk Magnor ◽  
...  
Keyword(s):  
Power System ◽  
Large Scale ◽  
Sensitivity Study ◽  
Renewable Energies ◽  
Renewable Power ◽  
Large Scale Integration ◽  
Storage Demand ◽  
Scale Integration

scholarly journals Large-Scale Integration of Renewable Power Sources into the Vietnamese Power System

2017 ◽  
Vol 125 ◽  
pp. 207-213 ◽  
Author(s):  
Alexander Kies ◽  
Bruno Schyska ◽  
Dinh Thanh Viet ◽  
Lueder von Bremen ◽  
Detlev Heinemann ◽  
...  
Keyword(s):  
Power System ◽  
Large Scale ◽  
Power Sources ◽  
Renewable Power ◽  
Large Scale Integration ◽  
Scale Integration

scholarly journals Day-ahead renewable scenario forecasts based on generative adversarial networks

2020 ◽  
Author(s):  
Congmei Jiang ◽  
Yongfang Mao ◽  
Yi Chai ◽  
Mingbiao Yu
Keyword(s):  
Power Systems ◽  
Renewable Resources ◽  
Large Scale ◽  
Generative Adversarial Networks ◽  
Power Sources ◽  
Renewable Power ◽  
Adversarial Networks ◽  
Future Behavior ◽  
Large Scale Integration ◽  
Scale Integration

<p>With the increasing penetration of renewable resources such as wind and solar, the operation and planning of power systems, especially in terms of large-scale integration, are faced with great risks due to the inherent stochasticity of natural resources. Although this uncertainty can be anticipated, the timing, magnitude, and duration of fluctuations cannot be predicted accurately. In addition, the outputs of renewable power sources are correlated in space and time, and this brings further challenges for predicting the characteristics of their future behavior. To address these issues, this paper describes an unsupervised method for renewable scenario forecasts that considers spatiotemporal correlations based on generative adversarial networks (GANs), which have been shown to generate high-quality samples. We first utilized an improved GAN to learn unknown data distributions and model the dynamic processes of renewable resources. We then generated a large number of forecasted scenarios using stochastic constrained optimization. For validation, we used power-generation data from the National Renewable Energy Laboratory wind and solar integration datasets. The experimental results validated the effectiveness of our proposed method and indicated that it has significant potential in renewable scenario analysis.</p>

scholarly journals Flexible Modern Power System: Real-Time Power Balancing through Load and Wind Power

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1710 ◽  
Author(s):  
Abdul Basit ◽  
Tanvir Ahmad ◽  
Asfand Yar Ali ◽  
Kaleem Ullah ◽  
Gussan Mufti ◽  
...  
Keyword(s):  
Power System ◽  
Real Time ◽  
Wind Power ◽  
Power Plants ◽  
Large Scale ◽  
Power Requirement ◽  
Wind Power Plants ◽  
Large Scale Integration ◽  
Flexible Load ◽  
Scale Integration

Increasing large-scale integration of renewables in conventional power system has led to an increase in reserve power requirement owing to the forecasting error. Innovative operating strategies are required for maintaining balance between load and generation in real time, while keeping the reserve power requirement at its minimum. This research work proposes a control strategy for active power balance control without compromising power system security, emphasizing the integration of wind power and flexible load in automatic generation control. Simulations were performed in DIgSILENT for forecasting the modern Danish power system with bulk wind power integration. A high wind day of year 2020 was selected for analysis when wind power plants were contributing 76.7% of the total electricity production. Conventional power plants and power exchange with interconnected power systems utilize an hour-ahead power regulation schedule, while real-time series are used for wind power plants and load demand. Analysis showed that flexible load units along with wind power plants can actively help in reducing real-time power imbalances introduced due to large-scale integration of wind power, thus increasing power system reliability without enhancing the reserve power requirement from conventional power plants.

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