scholarly journals HYBRIDZATION OF SOLAR WIND RENEWABLE POWER SYSTEMS USING MODELING AND SIMULATION

2021 ◽  
Vol 12 (9) ◽  
Author(s):  
Prashant Gautam ◽  
Jaya Shukla ◽  
Rajnish Bhasker ◽  
Satyam Kumar Upadhaya
Keyword(s):  
Solar Wind ◽  
Power Systems ◽  
Modeling And Simulation ◽  
Renewable Power

scholarly journals State-Space Model of Quasi-Z-Source Inverter-PV Systems for Transient Dynamics Studies and Network Stability Assessment

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4150
Author(s):  
Lluís Monjo ◽  
Luis Sainz ◽  
Juan José Mesas ◽  
Joaquín Pedra
Keyword(s):  
Power Systems ◽  
State Space ◽  
State Space Model ◽  
Pv System ◽  
Pv Systems ◽  
Renewable Power ◽  
Ac Networks ◽  
Transient Interactions ◽  
The Stability ◽  
Averaged Model

Photovoltaic (PV) power systems are increasingly being used as renewable power generation sources. Quasi-Z-source inverters (qZSI) are a recent, high-potential technology that can be used to integrate PV power systems into AC networks. Simultaneously, concerns regarding the stability of PV power systems are increasing. Converters reduce the damping of grid-connected converter systems, leading to instability. Several studies have analyzed the stability and dynamics of qZSI, although the characterization of qZSI-PV system dynamics in order to study transient interactions and stability has not yet been properly completed. This paper contributes a small-signal, state-space-averaged model of qZSI-PV systems in order to study these issues. The model is also applied to investigate the stability of PV power systems by analyzing the influence of system parameters. Moreover, solutions to mitigate the instabilities are proposed and the stability is verified using PSCAD time domain simulations.

Optimal Energy Storage Portfolio for High and Ultrahigh Carbon-Free and Renewable Power Systems

2021 ◽  
Author(s):  
Omar J Guerra ◽  
Joshua Eichman ◽  
Paul Denholm
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Short Duration ◽  
Current Literature ◽  
Optimal Energy ◽  
Renewable Power ◽  
Long Duration ◽  
Storage Technologies

Achieving 100% carbon-free or renewable power systems can be facilitated by the deployment of energy storage technologies at all timescales, including short-duration, long-duration, and seasonal scales; however, most current literature...

scholarly journals Techno-Economic Feasibility Study of Renewable Power Systems for a Small-Scale Plasma-Assisted Nitric Acid Plant in Africa

Processes ◽  
2016 ◽  
Vol 4 (4) ◽  
pp. 54 ◽  
Author(s):  
Aikaterini Anastasopoulou ◽  
Sughosh Butala ◽  
Bhaskar Patil ◽  
John Suberu ◽  
Martin Fregene ◽  
...  
Keyword(s):  
Nitric Acid ◽  
Power Systems ◽  
Feasibility Study ◽  
Economic Feasibility ◽  
Small Scale ◽  
Acid Plant ◽  
Renewable Power

scholarly journals Scenario-Based Economic Dispatch With Tunable Risk Levels in High-Renewable Power Systems

2019 ◽  
Vol 34 (6) ◽  
pp. 5103-5114 ◽  
Author(s):  
Mohammad Sadegh Modarresi ◽  
Le Xie ◽  
Marco Claudio Campi ◽  
Simone Garatti ◽  
Algo Care ◽  
...  
Keyword(s):  
Power Systems ◽  
Economic Dispatch ◽  
Risk Levels ◽  
Renewable Power

scholarly journals Frequency Response Characteristic (FRC) Curve and Fast Frequency Response Assessment in High Renewable Power Systems

2020 ◽  
Author(s):  
Shutang You
Keyword(s):  
Power Systems ◽  
Frequency Response ◽  
Real Time ◽  
Response Assessment ◽  
Response Characteristic ◽  
Assessment Method ◽  
Frequency Response Characteristic ◽  
Dynamic Simulations ◽  
Renewable Power ◽  
Response Performance

This letter introduces a frequency response characteristic (FRC) curve and its application in high renewable power systems. In addition, the letter presents a method for fast frequency response assessment and frequency nadir prediction without performing dynamic simulations using detailed models. The proposed FRC curve and fast frequency response assessment method are useful for operators to understand frequency response performance of high renewable systems in real time.

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>

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