1. EPNES: Intelligent Power Routers for Distributed Coordination in Electric Energy Processing Networks: Report 1 Agustín IrizarryCarlos Torres Manuel RodríguezIdalides Vergara José CedeñoJuan Jimenez Bienvenido VélezMarianela Santiago Miguel Vélez-Reyez Efraín O’Neill

2. September 25, 2003EPNES: Intelligent Power Routers2 Project Goal: Electrical Energy Networks Featuring Intelligent Power Routers (IPRs) System Reconfiguration with Minimal Human Intervention

3. September 25, 2003EPNES: Intelligent Power Routers3 State-of-Art Power Delivery Producers P1P2 Pn P3 Consumers C1C2 C3 C4 Power systems with centralized control

4. September 25, 2003EPNES: Intelligent Power Routers4 Re-routing in Response to Failures Producers P1P2 Pn P3 Consumers C1C2 C3 C4 x x System MTTR Limited by Operator Response Time

5. September 25, 2003EPNES: Intelligent Power Routers5 Re-routing in Response to Major Disturbances Producers P1P2 Pn P3 Consumers C1C2 C3 C4 Slow Operator Response May Cause Cascading Failures

6. September 25, 2003EPNES: Intelligent Power Routers6 Re-routing in Response to Major Disturbances Producers P1P2 Pn P3 Consumers C1C2 C3 C4 IPRS Respond Promptly to Avoid Further Deterioration

7. September 25, 2003EPNES: Intelligent Power Routers7 Our approach Decentralized control in response to major disturbances Intelligent Power Routers (IPR): –modular building blocks –strategically distributed over entire network –embedded intelligence –information exchange allows neighboring IPRs to coordinate network reconfiguration –improve network survivability, security, reliability, and re-configurability

8. September 25, 2003EPNES: Intelligent Power Routers8 Distributed Data Routing C1 C3 S1 S2 C2 Data Consumer Internet Data Servers Multiple redundant paths to move data between computers R1 R3 R4 R2 Routers

9. September 25, 2003EPNES: Intelligent Power Routers9 Distributed Routing: Tradeoffs Advantages –Highly reliable Multiple redundant paths to deliver the data –Highly scalable Grow network by adding more routers incrementally –Improved Performance Distributed and Parallel processing for data movement Disadvantages –Complex Control: Requires intelligence! Continuously run routing algorithms to find possible routes – Complex Implementation Hardware and software not trivial to implement

10. September 25, 2003EPNES: Intelligent Power Routers10 Recovering from Failures Each router continuously monitors the network When a broken link is detected by a router: –Its routing table is updated to reflect unavailable link –Update notice is propagated to near neighbors –Neighboring routers react accordingly Update their tables Propagate their updates to their own neighbors Idea is to find new paths to move the data –Avoid routes that use broken link

11. September 25, 2003EPNES: Intelligent Power Routers11 Distributed routing for power delivery systems ? We believe possible to use the concept of distributed control and coordination to obtain: –Greater reliability –Scalability –Improved survivability

12. September 25, 2003EPNES: Intelligent Power Routers12 How are power delivery systems different from computer networks? –Energy (not data) is transmitted –Must match generation to demand at all times –No buffers –Its a bit hard to get rid of excess energy We must deal with the laws of Physics!

13. September 25, 2003EPNES: Intelligent Power Routers13 Restoration Models IPR PROTOCOLS Distributed Control Models IPR Architecture Project Organization Education Economics

14. September 25, 2003EPNES: Intelligent Power Routers14 Potential architecture of the Intelligent Power Router

15. September 25, 2003EPNES: Intelligent Power Routers15 IPRs Design Basic Functionality of IPR Take the role of controlling the routing of power over the lines.

16. September 25, 2003EPNES: Intelligent Power Routers16 Simulation Tool Understand how to model physical components for power system Creating self-defined models

17. September 25, 2003EPNES: Intelligent Power Routers17 Simulating the IPR Simulating basic functionality of IPR –Load Priority –Line Priority

18. September 25, 2003EPNES: Intelligent Power Routers18 Power System Restoration  Overview: Improvement of security and reliability of the electric power system operation.  Researchers: Juan J. Jiménez, Graduate Student UPRM José R. Cedeño, Assistant Professor UPRM  Research: Formulate the Power System Restoration (PSR) problem and solve it with an Evolutionary Computation technique.  Approach: Use particle swarm optimization for solving the PSR problem. Formulate the PSR problem as a multi-stage, combinatorial, nonlinear, constrained optimization problem with binary and continuous variables.

19. September 25, 2003EPNES: Intelligent Power Routers19 Power System Restoration Problem formulation in terms of penalty functions: The objective of the formulation is to minimize the unserved load while satisfying the operating constraints of the system. Also, at each stage of the restoration process only one switching operation is allowed.

20. September 25, 2003EPNES: Intelligent Power Routers20 Power System Restoration Particle swarm optimization (PSO) Approach: PSO is one of the Evolutionary Computation techniques. PSO was originally developed in 1995 by a social-psychologist (James Kennedy) and an electrical engineer (Russell Eberhart). PSO emerged from earlier experiments with algorithms that modeled the "flocking behavior" seen in many species of birds. PSO consists of a number of particles (possible solutions) moving around in the search space looking for the best solution. PSO Model: Continuous variables Binary variables

21. September 25, 2003EPNES: Intelligent Power Routers21 Power System Restoration Test System and Results: Total load served increase through the stages. In each stage all the control and stage variables were within their limits and the power balance equations were met. The restoration path was established and all loads were served. 50% 25% 50% 100% 75%100% Restoration Completed

22. September 25, 2003EPNES: Intelligent Power Routers22 Objectives –De-centralized System Restoration Algorithm –Maximize number of high-priority loads restored Approach –Model as Network of IPRs (Graph Model) –Design Communication Protocols and Routing messages algorithms –Design Objective Function Pr k : Priority of load k, range [1,N], N is the lowest priority L k : each of the loads in the system (power required/load) Y k : Variable decision ( y k = 1 : Restored, y k = 0 : no restored) R: set of de-energized loads De-Centralized Communication & Control Protocols

23. September 25, 2003EPNES: Intelligent Power Routers23 Modeling Power Network As a Graph C B F G E D H A (5) (2) (10) (7) (8) (3) (4) (6) (5) (2) (1) (5) (3) (12) (15) (5) Graph G(V,E) : A set of nodes V connected by a set of edges E that represent some objects and their relations. IPRS model: Vertices – IPRs on buses Edges – lines between buses Weight – power flow Edges have Priority/ Reliability measure Weight w(e) of an edge e : indicates some metric about e

24. September 25, 2003EPNES: Intelligent Power Routers24 Restoration in Electrical Energy Network Featuring Intelligent Power Routers (IPRs) Link 1Link 2Link 3 Link 4Link 5Link 6 Link 7Link 8 Bus 1Bus 2 Bus 4 Bus 3 PR 4PR 3 PR 1PR 2 Src 1Src 3Src 2 Snk 2Snk 1 PRLinkPriorityReliability Pr11-1 41- Pr22-1 3-2 52- 61- Pr34-1 5-2 71- Pr46-1 81- Normal State — Normal State Message System going down — Request Power — Deny Request — Request Status — Response Status — Affirmative Response Restoration Process Table 1. Priority and Realibility

25. September 25, 2003EPNES: Intelligent Power Routers25 Risk Assessment What do we want to do? –Measure the change in reliability of the system when is operated with and without IPRs. How to measure it? –Adequacy –Security Well-Being indices Risk Framework What influences reliability ? –Effect on system’s reliability of adding IPRs

26. September 25, 2003EPNES: Intelligent Power Routers26 Well Being indices What are they? How do they capture changes in the network? Example: two 3 MW units, one 5 MW unit, 2% FOR each Capacity Out (MW) Probability 0.98×.98×.98.941192 3.02×.98×.98 +.98×.02×.98.038416 5.98×.98×.02.019208 6.02×.02×.98.000392 8.02×.98×.02 +.98×.02×.02.000784 11.02×.02×.02.000008

27. September 25, 2003EPNES: Intelligent Power Routers27 Failure mechanism We need the IPR failure probability –No data available on IPR’s failure modes or probability (They have not being built yet !) –Data Routers info may be useful to make an approximation. Data Router Comp Hardware Switch Power Hardware Intelligence How does it fail? –Software –Router –Switch

28. September 25, 2003EPNES: Intelligent Power Routers28 Validation TestBed: DC Zonal Electric Distribution System By: Lida Jáuregui-Rivera, Ph.D. Student Advisor: Dr. Miguel Vélez-Reyes

29. September 25, 2003EPNES: Intelligent Power Routers29 DCZEDS: Simplified Model

30. September 25, 2003EPNES: Intelligent Power Routers30 Starboard and Port Power Supplies  3-phase input Voltage : 480-560 V line-line rms  Regulates an output of 500 V dc for loads up to 15KW Power Supply Voltages and Currents

31. September 25, 2003EPNES: Intelligent Power Routers31 Zone 1 Subsystem Components of Zone1  Two Ship Service Converter Modules (SSCM).  A diode or’ing network  One Ship Service Inverter Module (SSIM) with a Load Bank  The inputs to this subsystem block include  on/off signals for the two SSCM’s and the SSIM  Voltage reference setting for the SSCM’s.  The voltage reference setting controls the output voltage of the SSCM.

32. September 25, 2003EPNES: Intelligent Power Routers32 Zone1 Ship Service Converter Module  The converter accepts 500 V dc and regulates the output voltage to 400 dc for loads up to 20 A. Block Diagram of the SSCM Control Voltages and Currents Waveforms

33. September 25, 2003EPNES: Intelligent Power Routers33 Zone1 Ship Services Inverter Module  Accepts 380 – 440 V dc and Provides a 3-phase AC voltage (380 – 440 V) SSIM Control Diagram Voltages and Currents Waveforms of the Three Phase Load

34. September 25, 2003EPNES: Intelligent Power Routers34 Zone 2 Subsystem  Two Ship Service Converter Modules (SSCM)  A diode or’ing network  Motor Controller Module Voltages and Currents Waveforms

35. September 25, 2003EPNES: Intelligent Power Routers35 Inverter Topology of the Motor Controller  Accepts 300 – 420 V dc. The ouput of the inverter is connected to a inductio motor Block Diagram of the Drive Control Torque, Speed, Voltages and Currents Waveforms

36. September 25, 2003EPNES: Intelligent Power Routers36 Zone 3 Components  Two Ship Service Converter Modules (SSCM)  A diode or’ing network  Constant Power Load Module Output Voltages and Currents Waveforms of the SSCM’s

37. September 25, 2003EPNES: Intelligent Power Routers37 Constant Power Load Module  The topology is based on a buck converter.  Accepts 120 – 600 V dc and regulates the output voltage to 100 V dc  The converter is loaded with a 2-Ohm resistor CPL Control Diagram Output Voltage and Current Waveforms of the CPL

38. September 25, 2003EPNES: Intelligent Power Routers38 Simulation of Fault Conditions Fault in Zone 2 Bus at 0.4 sec. of operation

39. September 25, 2003EPNES: Intelligent Power Routers39 Output Voltages and Currents of the Zone 2 SSCMs Torque, Speed, Voltages and Currents of the Induction Motor

40. September 25, 2003EPNES: Intelligent Power Routers40 Final Comments We have familiarized ourselves with the DC Zonal testbed developed by ONR –Lida Jauregui left UPRM. –New student started: Noel Figueroa Testbed will serve a model for control system development.

41. September 25, 2003EPNES: Intelligent Power Routers41 What we promised for year 1 Design of first IPR(v1.0) software module Integration of the IPR module into simulation system or development of the programmatic interface Experimentation with IPR(v1.0) Formulation of the risk assessment problem for IPR controlled system Development of economics and ethics modules (curriculum improvement)

42. September 25, 2003EPNES: Intelligent Power Routers42 Activities for year 2 Disseminate results from iteration 0 Design of alternative IPR control algorithms Simulations and preliminary reliability assessment Design of second IPR (v2.0) software module Evaluation of alternative IPR control algorithms Use of economics and ethics modules in electrical engineering courses (use assessment tools) Development of short course for non-power engineeering majors

43. September 25, 2003EPNES: Intelligent Power Routers43 Questions ?