scholarly journals A power optimization method considering glitch reduction by gate sizing

Author(s):  
Masanori Hashimoto ◽  
Hidetoshi Onodera ◽  
Keikichi Tamaru
Author(s):  
First A.XIE Ruidong ◽  
Second B.YI Yingmin ◽  
Third C.Yang Haichuan

Author(s):  
F. Dabiri ◽  
A. Nahapetian ◽  
T. Massey ◽  
M. Potkonjak ◽  
M. Sarrafzadeh

2014 ◽  
Vol 1008-1009 ◽  
pp. 421-425
Author(s):  
Yong Jin Chen ◽  
Jie He Su ◽  
Yong Jun Zhang ◽  
Ying Qi Yi

A reactive power optimization method based on interval arithmetic is presented to solve the uncertainty of the output of distributed generation (DG) and the effects of load fluctuation. The concept of interval number and interval arithmetic is introduced to model the interval power flow of distribution system, which is iterated by using the Krawczyk-Moore operator. The objective function is to minimize the interval midpoint value of system’s power loss, with taking the interval voltage constraints into consideration for the interval reactive power optimization model. A modified IEEE 14-bus system is used to validate the proposed model and its Particle Swarm Optimization (PSO) algorithm. The simulation results show that the proposed method is effective.


2014 ◽  
Vol 971-973 ◽  
pp. 979-982
Author(s):  
Yan Hong Li ◽  
Zhi Rong Zhang

Automatic voltage control(AVC) is the highest form of current power grid voltage and reactive power control,during the implementation of AVC, the whole network reactive power optimization isthe core and foundation. Thispaper researches and discuses the application of reactive power optimization inpower grid AVC. In the traditional reactive power optimization, the reactivepower limits of synchronous generators are fixed. In this paper, thesynchronous generator PQ operating limits change with external conditions,thus establishes reactive power optimization model in accordance with therequirements of AVC. Thispaper presents reactive power optimization method based on the principle ofpartition. The method decomposes the system to several partitions. Eachpartition separately optimized, thus reduces the system scale.And the convergence of the algorithm, the calculation speed and the discretevariable processing etc. improve. At the same time, this method reflects theclassification, hierarchical, partition, characteristics of coordinated controlof AVC.


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