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\section{Introduction}
Edward tufte’s work in visualization laid down basic principles of effective Power system visualization
as foundation to all visual design[1][2][3]. In mid 90s, The authors of [4] specifies three key to effective visual representation i.e. (i) Natural encoding of information; (ii) Task specific graphics; (iii) No gratuitous graphics. There were proposed researches to improve one line diagrams into visually informative, Dr. Thomas Overbye and his collaborators making significant contribution for improvement in one line diagram [5]. The contour plot is
further enhanced the key to
visualize variety of data, such as analyze power
flows in transmission lines[6], location marginal prices[7], contingency analysis[8], third dimension to visualize various data[9]; but still they developed the visualization with foundation as one line diagram.
Major drawback in each of the foregoing works is that the nodal positions remain arbitrary system, energy market and
exhibit no meaningful “natural encoding”. Some of the proposed researches explain the algorithm for bus positioning but none of these methods locate position nodes in a plot which is electrically meaningful. Visual presentation of any two nodes with a size variance are likely to
be perceived as change in their values and if plotted in close proximity then it’s perceived as in enlighten the
same group or cluster [10]. This paper illustrates different methods hidden patterns for making quick and
explains the effects of graph layout on human sociogram perception. Random positioning of nodes to layout a simplified one line diagram may generate a wrong impression like low centrality node effective decision. Power system is always represented as
a center node or an
isolated sub network as a well-connected network.
This paper redesigns power system network with a new methodology giving a new dimension by scaling the branch which corresponds uninformative single line diagram. Large electrical companies still use it to
its admittance. The scaling and redesign of represent power
system network uses two major layout which are discussed in system. Also, the
paper and are as follows: “Force Directed layout algorithm and Edge weighted spring embedded layout” which can generate electrically meaningful layout topology of
power system network [11][12][13]. In [11][13], This paper proposes a
fast convergence with high quality assurance of layout significantly. In [12], this paper introduces an edge length proportional to weight on the graph edges. This idea of creating “Electrical Lung” and using cytoscape for visualization is coined by Dr. Paul Cuffe.
Our motivation to employ graph theory approach to power system
is to understand system vulnerability to attack or component failure due to catastrophic events [14] [15], extensive work has
been done in this area of research [16] to evaluate vulnerability via graph theory, using centrality measure to find critical nodes for energy transmission [17], topological investigation of power grid networks [18] and to evaluate the complex in large power system networks [19]. But one of the researches was based a profound impact on
the electrical distances to study the vulnerability of power grid[20]. its reliability. The
author of [18] discusses electrical distances to remodel electrical grid and use complex graph theory to analyze the electrical network where paper uses degree, centrality and other measure to evaluate the electrical grid. Vulnerability of electrical network is important as few vibrant visualization of
the researches shows the power
law equation is followed [21].Unfortunately, these results are scattered in time and space. Modelling of electrical network as per the graph theory principle is a perplexing thought as it’s not evaluating system will empower an electrical
network as per electrical network characteristics.
In[22], a remarkable contribution was seen in biochemistry journal where they used resistance distances as a mean to restructure fullerene molecule. They used the electrical analogy to design the C_60 fullerene complex. Complexity in electrical grid
system is due operator to
physics behind the network which will not align with network theory. Electrical distances in power system were enlightened in a research by Paul Hines make quick decisions and
his collaborators. Electrical proximity methodology must be used to divide a power system into a meaningful zone, to
utilize spectral clustering and embedding promote situational awareness. Data visualization techniques
to partition and visualize power system [23] where authors of [24] used with electrical parameters
will offer several ways to
find electrical betweenness of achieve a
network and assessed the power grid on it.
A number of potential electrical distances measures and methodologies are being used in previous researches; The author of [25] used electrical distance and topological analysis and proposed the voltage control system close to
divide the geographical areas and time constants. This concept allows the structural controllability and observability of proximity of the power an ideal system.
The recent commendable contribution in work of power system visualization by Dr. Paul Hines, Dr. S. Blumsach and his collaborators [26] [27] has laid down the grounds of research into power system network with electrical distances. This paper
is organized as follows; Section 2 describes proposes the
methodology employed and their usage in way of representing electrical grid
visualization. Section3 presents several results from CytoscapeV3.2.0 of 2D visualization of variety of test case networks. The difference network via electrical parameter, forced layout algorithm and
the advantages of the proposed data visualization
with respect to conventional visualization are discussed in detail. Section 4 draws relevant conclusions. Finally, Appendix A briefly introduces software tools used for the simulations. techniques.
Index Terms- Data visualization, power system structure, force layout algorithm