User Interface for Situational Awareness for openpdc

Transcription

1 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 1

2 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 Need for Situational Awareness in Electric Utilities Data 2

3 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 [2] [1] Figure 1: Phasor Measurements using PMUs Figure 2: PMU Phasor Measurement Units (PMU) 3 [1]. [2].

4 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 Figure 3: openpdc Dataflow OpenPDC Framework 4

5 Create tools for more robust data monitoring alerts upon alarm activation Expand upon data analysis tools Give geographic representation of data Prototype K-Means clustering on received data Objectives 5

6 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 Methodology 6

7 Action Adapter add-on to openpdc Uses SMTP protocol Gmail SMTP server used during testing Figure 4: Alert Message Adapter 7

8 Send /s to specified addresses, whenever any selected alarm is triggered If service providers is known, can be sent directly to cell phone as well Adapter Figure 5: Snapshot of to text 8

9 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 Geographic Representation 9

10 Figure 6: Geographic representation GUI Geographic Representation GUI 10

11 Figure 7: Geographic representation GUI verbose 1 Geographic Representation GUI 11

12 Figure 8: Geographic representation GUI verbose 2 Geographic Representation GUI 12

13 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. Figure 9: Flowchart showing PMU data analysis in OpenPDC K-Means Clustering Algorithm 13

14 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. Figure 10: Display of voltage data using K-means clustering K-Means Clustering Algorithm (Cont.) 14

15 Change colored circle data representation to true heatmap 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. Future Work 15

16 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. Figure 11: Unit circle phase Angle representation Representation of Phasor Data 16

17 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 Density-Based Spatial Clustering 17 of Applications with Noise

18 Our research explores ways to improve the situational awareness of the grid using OpenPDC 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 Summary 18

19 A. G. Phadke, Synchronized phasor measurements in power systems, IEEE Comput. Appl. Power, vol. 6, no. 2, pp , Apr J.Phadke, A.G., Thorp, Synchronized Phasor Measurements and Their Applications Use of Synchrophasor Measurements in Protective Relaying Applications, B. K. Greene, Novel Applications for Phasor Measurement Units and Synchrophasor Data, B. Singh, N. K. Sharma, A. N. Tiwari, K. S. Verma, and S. N. Singh, Applications of phasor measurement units ( PMUs ) in electric power system networks incorporated with FACTS controllers, vol. 3, no. 3, pp , W. U. Rahman, M. Ali, A. Ullah, H. U. Rahman, and M. Iqbal, Advancement in Wide Area Monitoring Protection and Control Using PMU s Model in MATLAB / SIMULINK, vol. 2012, no. November, pp , E. Schweitzer and D. Whitehead, Real-time power system control using synchrophasors, Prot. Relay Eng., pp. 1 11, Y. Chompoobutrgool, S. Member, L. Vanfretti, and A. N. M. S, A Fundamental Study on Damping Control Design using PMU signals from Dominant Inter-Area Oscillation Paths, no. 3, pp M. Rihan, M. Ahmad, and M. S. Beg, Vulnerability Analysis of Wide Area Measurement System in the Smart Grid, vol. 2013, no. September, pp. 1 7, K. Koellner, Generator black start validation using synchronized phasor measurement, Prot. Relay Eng., pp. 1 7, M. Mills-Price and M. Scharf, Solar generation control with time-synchronized phasors,, th Annu., pp. 1 8, B. K. Johnson, S. Jadid, and S. E. Laboratories, Validation of Transmission Line Relay Parameters Using Synchrophasors, pp Grid Protection Alliance. [Online]. Available: Documentation of openpdc. [Online]. Available: [Accessed: 15-Jul-2014]. Microsoft Developer Network. [Online]. Available: RGB to HSL / HSL to RGB in C#. [Online]. Available: G. Nagy, State of the Art in Pattern Recognition, vol. 56, no. 5, pp , J. Hartigan and M. Wong, Algorithm AS 136: A k-means clustering algorithm, Appl. Stat., vol. 28, no. 1, pp , C. Cortes, V. Vapnik, and L. Saitta, Support-vector networks, Mach. Learn., vol. 20, no. 3, pp , N. Alon, Y. Matias, and M. Szegedy, The space complexity of approximating the frequency moments, in Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC 96, 1996, pp References 19

20 GROUP PHOTO Questions? 20

21 Thank You. 21