INRUSH-CURRENT-REDUCTION-IN-THREE-PHASE-POWER-TRA - This paper presents a scalable integration approach for algorithms and models written in fourth
generation (programming) languages for massive Smart Grid simulations as well as applications.
While fourth generation languages (4GL) focus on rapid application development and the
reduction of lines of code, they lack of integration and scalability features. Nevertheless, they are
widely spread and often used by engineers. The scalable integration of such elements is achieved
in this paper by wrapping the 4GL-models and algorithms with established web technologies like
RESTful web services and load balancing. The provision of a seamless integration concept allows
engineers to focus on rapid application development and liberates them integration efforts.
1. Introduction
Today’s energy grid undergoes a structural change towards the so-called Smart Grid. The,2014-12-28 01:38:55,下载1次
RouletteWheelSelection.zip - This paper presents a scalable integration approach for algorithms and models written in fourth
generation (programming) languages for massive Smart Grid simulations as well as applications.
While fourth generation languages (4GL) focus on rapid application development and the
reduction of lines of code, they lack of integration and scalability features. Nevertheless, they are
widely spread and often used by engineers. The scalable integration of such elements is achieved
in this paper by wrapping the 4GL-models and algorithms with established web technologies like
RESTful web services and load balancing. The provision of a seamless integration concept allows
engineers to focus on rapid application development and liberates them integration efforts.
1. Introduction
Today’s energy grid undergoes a structural change towards the so-called Smart Grid. The power,2014-12-28 00:40:59,下载2次
yazdani_natsheh_albarbar_7336.rar - This paper presents a scalable integration approach for algorithms and models written in fourth
generation (programming) languages for massive Smart Grid simulations as well as applications.
While fourth generation languages (4GL) focus on rapid application development and the
reduction of lines of code, they lack of integration and scalability features. Nevertheless, they are
widely spread and often used by engineers. The scalable integration of such elements is achieved
in this paper by wrapping the 4GL-models and algorithms with established web technologies like
RESTful web services and load balancing. The provision of a seamless integration concept allows
engineers to focus on rapid application development and liberates them integration efforts.,2014-12-27 21:46:34,下载2次
Smart-Grid-Modeling-Approach-for-Wide-Area.rar - This paper presents a scalable integration approach for algorithms and models written in fourth
generation (programming) languages for massive Smart Grid simulations as well as applications.
While fourth generation languages (4GL) focus on rapid application development and the
reduction of lines of code, they lack of integration and scalability features. Nevertheless, they are
widely spread and often used by engineers. The scalable integration of such elements is achieved
in this paper by wrapping the 4GL-models and algorithms with established web technologies like
RESTful web services and load balancing. The provision of a seamless integration concept allows
engineers to focus on rapid application development and liberates them integration efforts.,2014-12-27 21:45:32,下载2次
25401808powerp.rar - This paper presents a scalable integration approach for algorithms and models written in fourth
generation (programming) languages for massive Smart Grid simulations as well as applications.
While fourth generation languages (4GL) focus on rapid application development and the
reduction of lines of code, they lack of integration and scalability features. Nevertheless, they are
widely spread and often used by engineers. The scalable integration of such elements is achieved
in this paper by wrapping the 4GL-models and algorithms with established web technologies like
RESTful web services and load balancing. The provision of a seamless integration concept allows
engineers to focus on rapid application development and liberates them integration efforts.,2014-12-27 21:42:09,下载2次
Iron.Man.3.2013.720p.BluRay.x264.YIFY.rar - of the electrical power system. At the time of transformer energization high current is drawn by the transformer known as the inrush current. This current is nearly ten times more than the full load current of transformer. It produces mechanical stress on transformer and also affects the windings and bushings of the transformer. The large switching transient current affects malfunction of protection system of power system and the different equipments connected to system. So the inrush current should be minimized. There are different methods used to minimize the inrush current such as volt second balance, series compensator, point on wave switching method etc. This paper focuses on point on wave switching method. It also explains the results for inrush current of three phase transformer with and without point on wave switching method. A test is driven on 450 kVA, 500kV/230kV grounded Y/D transformer in MATLAB/SIMLINK environment. It also focuses on,2014-12-26 23:00:05,下载8次
herraiz_icsoft2011.rar - Optimal power flow (OPF) is one of the nonlinear problems of power system. The various
algorithms for solving optimal power flow problem are found in the literature. The genetic algorithm
(GA) based solution techniques are found to be most suitable because of their ability of
simultaneous multidimensional search for optimal solution. This paper presents a novel GA-Fuzzy
based approach for solving OPF. The GA parameters e.g. crossover and mutation probabilities are
governed by fuzzy rule base. Algorithms for GA-OPF and GA-Fuzzy (GAF) OPF are developed
and compared. The results obtained for these systems demonstrate that the GAF-OPF has faster
convergence and lesser generation costs as compared to various methods tested for above systems.
KEYWORDS: optimal power flow, genetic algorithm, GA-Fuzzy approach
Authors,2014-12-26 14:21:36,下载6次
mathprog.rar - 2.1 optimal power flow analysis:
The main aim of Optimal Power flow (OPF) algorithm is to capture a steady state operating point. Generation cost, loss are curtailed by steady state operating point. Further, it also maximizes load ability preserving a suitable system representation in terms of parameters of generators (real and reactive powers, line flow limits, output of various compensating devices etc.) . Usually , classical optimization methods were used but as the technology has advanced and integration of FACTS devices in the power system, the traditional concepts and practices of power systems are placed over by an economic market management. . Therefore, OPF has become complex in nature. So, Artificial Intelligence (AI) methods are used which can solve higher complexity problem than OPF.
,2014-12-24 23:54:38,下载15次
EEE-212-lab-sheet.rar - empirical formula with kaiser
clc
clear all
fs=1000
fc=250
df=50
r=0.001
f=fc/fs
dw=2*pi*(df/fs)
a=-20*log(r)
n=floor(((a-8)/(2.285*dw))+1)
if a>50
b=0.1102*(a-8.7)
elseif a>=21 && a<=50
b=0.5842*((a-21)^0.4)+0.07886*(a-21)
elseif a<21
b=0.0
end
w=kaiser(n,b)
for i=1:n
if i~=(n-1)/2
hd(i)= (2*f*sin((i-((n-1)/2))*2*pi*f))/((i-((n-1)/2))*2*pi*f)
elseif i==(n-1)/2
hd(i)=2*f
end
end
for j=1:n
h(j)=w(j)*hd(j)
end
subplot(3,1,1), plot(w)
subplot(3,1,2), plot(h)
subplot(3,1,3), plot(h,n)
,2014-12-24 23:21:13,下载5次
11.rar - empirical formula with kaiser
clc
clear all
fs=1000
fc=250
df=50
r=0.001
f=fc/fs
dw=2*pi*(df/fs)
a=-20*log(r)
n=floor(((a-8)/(2.285*dw))+1)
if a>50
b=0.1102*(a-8.7)
elseif a>=21 && a<=50
b=0.5842*((a-21)^0.4)+0.07886*(a-21)
elseif a<21
b=0.0
end
w=kaiser(n,b)
for i=1:n
if i~=(n-1)/2
hd(i)= (2*f*sin((i-((n-1)/2))*2*pi*f))/((i-((n-1)/2))*2*pi*f)
elseif i==(n-1)/2
hd(i)=2*f
end
end
for j=1:n
h(j)=w(j)*hd(j)
end
subplot(3,1,1), plot(w)
subplot(3,1,2), plot(h)
subplot(3,1,3), plot(h,n)
,2014-12-24 23:20:03,下载2次
2.rar - Objects forming possible solution within original problem context are called phenotypes, their encoding, the individuals within the GA, are called genotypes.
The representation step specifies the mapping the phenotypes onto a set of genotypes.
Candidate solution, phenotype and individual are used to denotes points of the space of possible solutions. This space is called phenotype space.
Chromosome, and individual can be used for points in the genotye space.
Elements of a chromosome are called genes. A value of a gene is called an allele.
Variation Operators
The role of variation operators is to create new individuals old ones. Variation operators form the implementation of the elementary steps with the search space.
,2014-12-22 22:54:47,下载3次