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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
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September 25, 2003EPNES: Intelligent Power Routers2 Project Goal: Electrical Energy Networks Featuring Intelligent Power Routers (IPRs) GOAL: System Reconfiguration with Minimal Human Intervention
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September 25, 2003EPNES: Intelligent Power Routers3 State-of-Art Power Delivery Producers P1P2 Pn P3 Consumers C1C2 C3 C4 Power Systems with centralized control
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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
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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
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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
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September 25, 2003EPNES: Intelligent Power Routers7 Outline Background and Problem Statement Analogy: IPRs and Data Networks Year 1 Goals and Results –IPR Architecture and Modeling –IPR Restoration Model –IPR Network Restoration Protocols –IPR Risk Assessment –Education and Economics Year 2 Projected Goals Summary
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September 25, 2003EPNES: Intelligent Power Routers8 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
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September 25, 2003EPNES: Intelligent Power Routers9 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
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September 25, 2003EPNES: Intelligent Power Routers10 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
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September 25, 2003EPNES: Intelligent Power Routers11 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
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September 25, 2003EPNES: Intelligent Power Routers12 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
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September 25, 2003EPNES: Intelligent Power Routers13 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!
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September 25, 2003EPNES: Intelligent Power Routers14 Outline Background and Problem Statement Analogy: IPRs and Data Networks Year 1 Goals and Results –IPR Architecture and Modeling –IPR Restoration Model –IPR Network Restoration Protocols –IPR Risk Assessment –Education and Economics Year 2 Projected Goals Summary
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September 25, 2003EPNES: Intelligent Power Routers15 Restoration Models IPR PROTOCOLS Distributed Control Models IPR Architecture Project Organization Education Economics Dr. Bienvenido Velez
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September 25, 2003EPNES: Intelligent Power Routers16 Potential architecture of the Intelligent Power Router
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September 25, 2003EPNES: Intelligent Power Routers17 IPRs Design Basic Functionality of IPR Take the role of controlling the routing of power over the lines.
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September 25, 2003EPNES: Intelligent Power Routers18 Simulation Tool Understand how to model physical components for power system Creating self-defined models
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September 25, 2003EPNES: Intelligent Power Routers19 Simulating the IPR Simulating basic functionality of IPR –Load Priority –Line Priority
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September 25, 2003EPNES: Intelligent Power Routers20 Restoration Models IPR PROTOCOLS Distributed Control Models IPR Architecture Project Organization Education Economics Dr. Ricardo Cedeño
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September 25, 2003EPNES: Intelligent Power Routers21 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.
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September 25, 2003EPNES: Intelligent Power Routers22 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.
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September 25, 2003EPNES: Intelligent Power Routers23 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
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September 25, 2003EPNES: Intelligent Power Routers24 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
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September 25, 2003EPNES: Intelligent Power Routers25 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
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September 25, 2003EPNES: Intelligent Power Routers26 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
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September 25, 2003EPNES: Intelligent Power Routers27 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
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September 25, 2003EPNES: Intelligent Power Routers28 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
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September 25, 2003EPNES: Intelligent Power Routers29 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
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September 25, 2003EPNES: Intelligent Power Routers30 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
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September 25, 2003EPNES: Intelligent Power Routers31 Validation TestBed: DC Zonal Electric Distribution System By: Lida Jáuregui-Rivera, Ph.D. Student Advisor: Dr. Miguel Vélez-Reyes
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September 25, 2003EPNES: Intelligent Power Routers32 DCZEDS: Simplified Model
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September 25, 2003EPNES: Intelligent Power Routers33 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
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September 25, 2003EPNES: Intelligent Power Routers34 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.
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September 25, 2003EPNES: Intelligent Power Routers35 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
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September 25, 2003EPNES: Intelligent Power Routers36 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
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September 25, 2003EPNES: Intelligent Power Routers37 Zone 2 Subsystem Two Ship Service Converter Modules (SSCM) A diode or’ing network Motor Controller Module Voltages and Currents Waveforms
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September 25, 2003EPNES: Intelligent Power Routers38 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
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September 25, 2003EPNES: Intelligent Power Routers39 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
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September 25, 2003EPNES: Intelligent Power Routers40 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
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September 25, 2003EPNES: Intelligent Power Routers41 Simulation of Fault Conditions Fault in Zone 2 Bus at 0.4 sec. of operation
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September 25, 2003EPNES: Intelligent Power Routers42 Output Voltages and Currents of the Zone 2 SSCMs Torque, Speed, Voltages and Currents of the Induction Motor
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September 25, 2003EPNES: Intelligent Power Routers43 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.
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September 25, 2003EPNES: Intelligent Power Routers44 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)
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September 25, 2003EPNES: Intelligent Power Routers45 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
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September 25, 2003EPNES: Intelligent Power Routers46 Questions ?
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