user interface for situational awareness for openpdc · user interface for situational awareness...

User Interface for Situational

Awareness for openPDC

Nickolas Gellerman, B.S.E.E Student

Ranganath Vallakati, M.S.E.E Student

Anupam Mukherjee, M.S.E.E Student

Advisor: Dr. Prakash Ranganathan, Assistant Professor

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Need for Situational Awareness

in Electric Utilities Data

World becoming increasingly dependent on electrical energy.

� Communication Systems

� Transportation Systems

� Medical Equipment/Devices

Situational awareness involves being aware of what is happening in the electrical grid in order

to understand how information, events, and operator actions will impact goals and objectives,

both immediately and in the near future.

Benefits of a situational awareness tool:

� Real-time monitoring of electrical grid status.

� Address anomalies (phase, frequency, voltage, current) as they happen, shortening

downtime in the grid.

� Detect patterns and prevent future outage problems

Nick G, et.al. User Interface for Situational Awareness for

OpenPDC. IEEE NAPS 2014

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Phasor Measurement Units (PMU)

Phasor Measurement Units

� Measures phasor data (frequency, magnitude, phase angle, etc.)

at a bus on the power grid

� Takes measurements in real time (between 30 and 240 Hz)

� Vital tool to maintain awareness of the power grid



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[1]. http://www.phasor-rtdms.com/phaserconcepts/phasor_adv_faq.html

[2]. http://www.macrodyneusa.com/model_1690.htm

[1][2]

Figure 1: Phasor Measurements using PMUs Figure 2: PMU

OpenPDC Framework

Open source Phasor Data Concentrator

� Reads and archives data streamed from PMUs

� Supports many different data protocols

� Has a small amount of built-in data analysis/dashboard tools



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Figure 3: openPDC Dataflow

Objectives

� Create tools for more robust data monitoring

� Email alerts upon alarm activation

� Expand upon data analysis tools

� Give geographic representation of data

� Prototype K-Means clustering on received data



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Methodology

� C# used for all coding

� Visual Studio 2012 IDE used for development

� External libraries utilized:

� Grid Solutions Framework

� Google Static Maps API

� .NET Framework 4.5



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Email Adapter

� Action Adapter add-on to

openPDC

� Uses SMTP protocol

� Gmail SMTP server used

during testing



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Figure 4: Email Alert Message

Email Adapter

� Send email/s to specified

addresses, whenever any

selected alarm is triggered

� If service providers is known,

email can be sent directly to

cell phone as well



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Figure 5: Snapshot of email to text

Geographic

Representation

� Windows Forms application

� Uses the Google Static Maps API as basis for location

mapping

� Individual PMUs placed on top of Static Map map using

Mercator Projection



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Geographic

Representation GUINick G, et.al. User Interface for Situational Awareness for


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Figure 6: Geographicrepresentation GUI

Geographic



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Figure 7: Geographic representation GUI verbose 1

Geographic



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Figure 8: Geographic representation GUI verbose 2

K-Means Clustering Algorithm

� Cluster Formation & Data into Groups

� 1) Initial statistical “mean values”

are randomly generated for each

cluster.

� 2) Each data point is assigned to the

cluster with the closest mean value.

� 3) Mean values are re-calculated

using the data points contained in

the clusters.

� 4) Repeat Step 2. If none of the

data points require re-assignment,

terminate the algorithm.



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Figure 9: Flowchart showing PMU data analysis in OpenPDC

K-Means Clustering Algorithm

(Cont.)

� Basework created to allow

for K-Means clustering of

data

� Red dots represent centroid

of a cluster.

� Blue dots represent

individual data points that

are used to calculate

centroid.



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Figure 10: Display of voltage data using K-means clustering

Future Work

� Change colored circle data representation to true heat-

map using openGL

� Make clustering through the GUI more flexible

� Selectable samples, time period, etc.

� Improve general user-friendliness of GUI

� Expand data mining research using other

classification/clustering algorithms.



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Representation of

Phasor Data

� Displays the complex phasor

data in a Unit Circle

Representation.

� Length of arrow represents

magnitude of voltage/current

� Direction of arrow represents

the phase angle.



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Figure 11: Unit circle phase Angle representation

Density-Based Spatial Clustering

of Applications with NoiseNick G, et.al. User Interface for Situational Awareness for


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• Initially, select a point � arbitrarily.

• Observe all the points that are density

reachable from � w.r.t ε (Eps)

and��.

• If point � is a core point, a cluster is

formed.

• If point � is a border point and no points

are density reachable from�, Then

DBSCAN visits the next point of the data

base.

• This process from step1 to step 5 is

continued till all the points have been

processed or when no new point can be

added to any cluster.Figure 12: Clustering representation through DBSCAN for openPDC data

Summary

� Our research explores ways to improve the situational

awareness of the grid using OpenPDC

� E-mail adapter added to the OpenPDC environment to

provide real-time alerts on grid status

� K-means clustering explored to provide more

sophisticated data analysis tools



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References

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Apr. 1993.

J.Phadke, A.G., Thorp, Synchronized Phasor Measurements and Their Applications. 2008.

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“Grid Protection Alliance.” [Online]. Available: http://openpdc.codeplex.com/.

“Documentation of openPDC.” [Online]. Available: http://openpdc.codeplex.com/documentation. [Accessed: 15-Jul-2014].

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G. Nagy, “State of the Art in Pattern Recognition,” vol. 56, no. 5, pp. 836–857, 1968.

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Questions?• GROUP PHOTO



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Thank You.



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