Agustín Irizarry Carlos Torres Manuel Rodríguez Idalides Vergara José Cedeño Juan Jimenez

1. EPNES: Intelligent Power Routers for Distributed Coordination in Electric Energy Processing Networks: Report 1 Agustín Irizarry Carlos Torres Manuel Rodríguez Idalides Vergara José Cedeño Juan Jimenez Bienvenido Vélez Marianela Santiago Miguel Vélez-Reyez Efraín O’Neill

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

3. State-of-Art Power Delivery Producers P1 P2 P3 Pn Consumers C1 C2 C4 C3 Power systems with centralized control EPNES: Intelligent Power Routers

4. System MTTR Limited by Operator Response Time Re-routing in Response to Failures Producers P1 P2 P3 Pn x x Consumers C1 C2 C4 C3 EPNES: Intelligent Power Routers

5. Re-routing in Response to Major Disturbances Producers P1 P2 P3 Pn Slow Operator Response May Cause Cascading Failures Consumers C1 C2 C4 C3 EPNES: Intelligent Power Routers

6. Re-routing in Response to Major Disturbances Producers P1 P2 P3 Pn IPRS Respond Promptly to Avoid Further Deterioration Consumers C1 C2 C4 C3 EPNES: Intelligent Power Routers

7. 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 networkreconfiguration • improve network survivability, security, reliability, and re-configurability EPNES: Intelligent Power Routers

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

9. 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 EPNES: Intelligent Power Routers

10. 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 EPNES: Intelligent Power Routers

11. 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 EPNES: Intelligent Power Routers

12. 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! EPNES: Intelligent Power Routers

13. Project Organization IPR Architecture Distributed Control Models Economics Education Restoration Models IPR PROTOCOLS EPNES: Intelligent Power Routers

14. Potential architecture of the Intelligent Power Router EPNES: Intelligent Power Routers

15. IPRs Design • Basic Functionality of IPR Take the role of controlling the routing of power over the lines. EPNES: Intelligent Power Routers

16. Simulation Tool • Understand how to model physical components for power system • Creating self-defined models EPNES: Intelligent Power Routers

17. Simulating the IPR • Simulating basic functionality of IPR • Load Priority • Line Priority EPNES: Intelligent Power Routers

18. 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. EPNES: Intelligent Power Routers

19. 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. EPNES: Intelligent Power Routers

20. 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 EPNES: Intelligent Power Routers

21. Power System Restoration • 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. Test System and Results: 75% 100% Restoration Completed 100% 50% 25% 50% 100% 50% EPNES: Intelligent Power Routers

22. De-Centralized Communication & Control Protocols • 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 • Prk : Priority of load k , range [1,N], N is the lowest priority • Lk : each of the loads in the system (power required/load) • Yk : Variable decision ( yk = 1 : Restored, yk = 0 : no restored) • R: set of de-energized loads EPNES: Intelligent Power Routers

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

24. Link 1 Link 2 Link 3 Bus 1 Bus 2 Src 1 Src 2 Src 3 PR 1 PR 2 Link 4 Link 5 Link 6 Bus 4 Bus 3 Link 7 Link 8 PR 3 PR 4 Snk 1 Snk 2 Restoration in Electrical Energy Network Featuring Intelligent Power Routers (IPRs) System going down Restoration Process Normal State Table 1. Priority and Realibility — Normal State Message — Deny Request — Response Status — Request Power — Request Status —Affirmative Response EPNES: Intelligent Power Routers

25. 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 EPNES: Intelligent Power Routers

26. What are they? How do they capture changes in the network? Example: two 3 MW units, one 5 MW unit, 2% FOR each Well Being indices EPNES: Intelligent Power Routers

27. 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 Intelligence Switch Power Hardware • How does it fail? • Software • Router • Switch EPNES: Intelligent Power Routers

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

29. DCZEDS: Simplified Model EPNES: Intelligent Power Routers

30. 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 EPNES: Intelligent Power Routers

31. 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. EPNES: Intelligent Power Routers

32. Zone1Ship Service Converter Module • The converter accepts 500 V dc and regulates the output voltage to 400 dc for loads up to 20 A. Voltages and Currents Waveforms Block Diagram of the SSCM Control EPNES: Intelligent Power Routers

33. Zone1Ship Services Inverter Module • Accepts 380 – 440 V dc and Provides a 3-phase AC voltage (380 – 440 V) Voltages and Currents Waveforms of the Three Phase Load SSIM Control Diagram EPNES: Intelligent Power Routers

34. Zone 2 Subsystem • Two Ship Service Converter Modules (SSCM) • A diode or’ing network • Motor Controller Module Voltages and Currents Waveforms EPNES: Intelligent Power Routers

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

36. 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 EPNES: Intelligent Power Routers

37. CPL Control Diagram 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 Output Voltage and Current Waveforms of the CPL EPNES: Intelligent Power Routers

38. Simulation of Fault Conditions Fault in Zone 2 Bus at 0.4 sec. of operation EPNES: Intelligent Power Routers

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

40. 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. EPNES: Intelligent Power Routers

41. 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) EPNES: Intelligent Power Routers

42. 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 EPNES: Intelligent Power Routers

43. Questions ? EPNES: Intelligent Power Routers