Risk based valuation of reactive power sources for open access transmission

Author(s):  
W.H. Chen ◽  
C.W. Yu
Author(s):  
Bawoke Simachew

Power loss reduction is an important problem that needs to be addressed with respect to generating electrical power. It is important to reduce power loss using locally generated power sources and/or compensations. This chapter brings a method of presents a method of maximizing energy utilization, feeder loss reduction, and voltage profile improvement for radial distribution network using the active and reactive power sources. Distributed Generation (DG) (wind and solar with backup by biomass generation) and shunt capacitor (QG) for reactive power demand are used. Integrating DG and QG at each bus might reduce the loss but it is economically unaffordable, especially for developing countries. Therefore, the utilization optimization method is required for finding an optimal size and location to feeders for placing QG and DG to minimize feeder loss.


Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3177 ◽  
Author(s):  
Yunqi Xiao ◽  
Yi Wang ◽  
Yanping Sun

A reactive power/voltage control strategy is proposed that uses wind turbines as distributed reactive power sources to optimize the power flow in large-scale wind farms and reduce the overall losses of the collector system. A mathematical model of loss optimization for the wind farm collector systems is proposed based on a reactive power/voltage sensitivity analysis; a genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used to validate the optimization performances. The simulation model is established based on a large-scale wind farm. The results of multiple scenarios show that the proposed strategy is superior to the traditional methods with regard to the reactive power/voltage control of the wind farm and the loss reduction of the collector system. Furthermore, the advantages in terms of annual energy savings and environmental protection are also estimated.


2014 ◽  
Vol 986-987 ◽  
pp. 394-399
Author(s):  
Xue Yong Xu ◽  
Pan Zhou ◽  
Qi Zhe Huang ◽  
Chun Ming Deng ◽  
Meng Meng Shi ◽  
...  

Along with the increasing use of cables in power grid and the increasing ration of distributed power sources’ synchronization, such as small hydropower’s synchronization, increasing the reactive power transmission on the line, make it difficult to achieve the balance of reactive hierarchical partition. Take a certain region’s power grid for actual examples, after the installation of magnetic control reactor (MCR), using immune genetic algorithm (IGA) to coordinate the capacity of magnetic control reactor and the existing reactive power resources, the results show that the magnetic control reactor does much good to absorb the system’s excessive reactive power and limit the voltage’s increasing.


Author(s):  
V. Z. Manusov ◽  
P. V. Matrenin ◽  
E. S. Tretiakova

<p><span lang="EN-US">The article dues to the arrangement of the reactive power sources in the power grid to reduce the active power losses in transmission lines and minimize cable cross-sections of the lines. The optimal arrangement is considered from two points of view. In the first case, it is possible to minimize the active power losses only. In the second case, it is possible to change the cross-sections of the supply lines to minimize both the active power losses and the volume of the cable lines. The sum of the financial cost of the active power losses, the capital investment to install the deep reactive power compensation, and cost of the cable volume is introduced as the single optimization criterion. To reduce the losses, the deep compensation of reactive power sources in nodes of the grid are proposed. This optimization problem was solved by the Genetic algorithm and the Particle Swarm optimization algorithm. It was found out that the deep compensation allows minimizing active power losses the cable cross-section. The cost-effectiveness of the suggested method is shown. It was found out that optimal allocation of the reactive power sources allows increasing from 9% to 20% the financial expenses for the enterprise considered.</span></p>


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