Optimal power flow application to EHVAC interconnections for GW-sized Offshore Wind Farms

2016 ◽  
Author(s):  
S. Lauria ◽  
M. Maccioni ◽  
M. Schembari ◽  
A. Codino ◽  
A. Faza
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Optimal Power

scholarly journals Optimal power flow in multi-terminal HVDC grids with offshore wind farms and storage devices

2015 ◽  
Vol 65 ◽  
pp. 291-298 ◽  
Author(s):  
Miguel Jiménez Carrizosa ◽  
Fernando Dorado Navas ◽  
Gilney Damm ◽  
Françoise Lamnabhi-Lagarrigue
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Storage Devices ◽  
Optimal Power ◽  
And Storage

scholarly journals An Aerodynamics-Based Novel Optimal Power Extraction Strategy for Offshore Wind Farms With Central VSCs

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 44351-44361 ◽  
Author(s):  
Si-Zhe Chen ◽  
Guozhuan Xiong ◽  
Guidong Zhang ◽  
Samson Shenglong Yu ◽  
Herbert Ho-Ching Iu ◽  
...  
Keyword(s):  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Power Extraction ◽  
Optimal Power

scholarly journals Multi-objective optimal power flow in the presence of intermittent renewable energy sources

2018 ◽  
Vol 7 (4) ◽  
pp. 2766 ◽  
Author(s):  
S. Surender Reddy
Keyword(s):  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Thermal Power ◽  
Wind Farms ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost

This paper solves a multi-objective optimal power flow (MO-OPF) problem in a wind-thermal power system. Here, the power output from the wind energy generator (WEG) is considered as the schedulable, therefore the wind power penetration limits can be determined by the system operator. The stochastic behavior of wind power and wind speed is modeled using the Weibull probability density function. In this paper, three objective functions i.e., total generation cost, transmission losses and voltage stability enhancement index are selected. The total generation cost minimization function includes the cost of power produced by the thermal and WEGs, costs due to over-estimation and the under-estimation of available wind power. Here, the MO-OPF problems are solved using the multi-objective glowworm swarm optimiza-tion (MO-GSO) algorithm. The proposed optimization problem is solved on a modified IEEE 30 bus system with two wind farms located at two different buses in the system.  

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