Intelligent Power Routers for Distributed Coordination in Electric

Intelligent Power Routers for Distributed Coordination in Electric Energy Processing Networks Progress Report Agustín Irizarry Manuel Rodríguez José Cedeño Bienvenido Vélez Miguel Vélez-Reyes Efraín O’Neill-Carrillo Alberto Ramírez October 4, 2002 Carlos Torres Idalides Vergara Juan Jiménez Marianela Santiago Noel Figueroa Alma Estremera EPNES: Intelligent Power Routers iprs@ece. uprm. edu

Outline • • • Background and Problem Statement Analogy: IPRs and Data Networks Report on project activities Year 1 Accomplishments Summary Year 2 Proposed activities October 23 -24 2003 EPNES: Intelligent Power Routers 2

State-of-the-Art Power Delivery Producers P 1 P 2 P 3 Pn GOAL: De-centralized System Reconfiguration with Minimal Human Intervention Consumers C 1 October 23 -24 2003 C 2 C 3 EPNES: Intelligent Power Routers C 4 3

Re-routing in Response to Failures Producers P 1 P 2 P 3 Pn System MTTR Limited by Operator Response Time x x Consumers C 1 October 23 -24 2003 C 2 C 3 EPNES: Intelligent Power Routers C 4 4

Re-routing in Response to Major Disturbances Producers P 1 P 2 P 3 Pn Slow Operator Response May Cause Cascading Failures C 1 October 23 -24 2003 Consumers C 2 C 3 EPNES: Intelligent Power Routers C 4 5

Re-routing in Response to Major Disturbances Producers P 1 P 2 P 3 Pn IPRS Respond Promptly to Avoid Further Deterioration Consumers C 1 October 23 -24 2003 C 2 C 3 EPNES: Intelligent Power Routers C 4 6

Our approach • De-centralized 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 October 23 -24 2003 EPNES: Intelligent Power Routers 7

Outline ü Background and Problem Statement • Analogy: IPRs and Data Networks • Report on project activities • Year 1 Accomplishments Summary • Year 2 Proposed activities October 23 -24 2003 EPNES: Intelligent Power Routers 8

Distributed Data Routing Routers S 1 Data Servers Data Consumer S 3 R 1 R 2 C 1 Data Network R 3 S 2 R 4 C 2 Multiple redundant paths to move data between computers October 23 -24 2003 EPNES: Intelligent Power Routers 9

Re-routing in Response to Major Disturbances Data Packets Data Consumer S 1 S 3 Major Data Disturbance Servers R 2 R 1 C 1 Data Network R 3 S 2 R 4 C 2 October 23 -24 2003 EPNES: Intelligent Power Routers 10

Re-routing in Response to Major Disturbances Data Packets Data Consumer S 1 S 3 Major Data Disturbance Servers R 2 R 1 C 1 Data Network R 3 S 2 R 4 C 2 October 23 -24 2003 EPNES: Intelligent Power Routers 11

How are power delivery systems different from computer networks? – Energy transmission (not data) – Must match generation to demand at all times – No buffers – Hard to get rid of excess energy We must deal with the laws of Physics! October 23 -24 2003 EPNES: Intelligent Power Routers 12

Outline ü Background and Problem Statement ü Analogy: IPRs and Data Networks • Report on project activities • Year 1 Accomplishments Summary • Year 2 Proposed activities October 23 -24 2003 EPNES: Intelligent Power Routers 13

Project Organization Education Economics Risk Assessment Education October 23 -24 2003 EPNES: Intelligent Power Routers 14

Restoration Models and IPR Protocols • Use the Power System Restoration (PSR) problem, an extreme condition, as starting point to address the system reconfiguration problem. – Use PSR problem global (centralized) solution as benchmark – Develop communication and data protocols that allow the implementation of different decentralized restoration strategies

Power System Restoration (PSR) • Goal: – rebuild a stable electric system – restore all unserved loads • Approach: – Apply particle swarm optimization (PSO) to solve PSR • Optimization problem: – minimize the amount of unserved loads at each stage – – power flow constraints feasible bounds on state and control variables capacity limits on lines and transformers only one switching operation per stage October 23 -24 2003 EPNES: Intelligent Power Routers 16

Particle swarm optimization (PSO) method • Emerging Evolutionary Computation (EC) technique [Kennedy 1995] • Based on "flocking behavior" of animals • In PSO individuals move around in a search space looking for an optimal solution based on their current position and on the best position within the flock. Continuous variables Binary variables October 23 -24 2003 EPNES: Intelligent Power Routers 17

Power System Restoration: Example Test System and Results: 100% 75% ü Total load served increased through the stages. ü At each stage, all the control and state variables remained within their feasible limits and the power balance constraints were satisfied. ü The restoration path was established and all loads were successfully served. Restoration Completed 100% 25% 50% 100% 50% WSCC Nine-Bus Test System October 23 -24 2003 EPNES: Intelligent Power Routers 18

Oct De-Centralized Communication & Control Protocols • Goal: – Develop Communication Protocols to implement a System Restoration Algorithm • Approach: – Use a graph model for the power network with IPRs • Optimization problem: – minimize the amount of unserved loads based on priority [Nagata et. al. 2002]

October Modeling a Power Network As a Graph Src 1 Src 2 Link 1 Bus 1 Link 2 IPR 1 Link 4 Bus 3 Src 3 IPR 3 Link 7 Snk 1 Link 3 Bus 2 IPR 2 Link 5 Link 6 Bus 4 IPR 4 Link 8 Snk 2

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

Risk Assessment • Goal: – Measure the change in reliability of a power system operated with and without IPRs. • Approach: – Use an existing method • Well-Being indices [Billinton et. al. ] • Risk Framework [Mc. Calley et. al. ] – Need failure probability data October 23 -24 2003 EPNES: Intelligent Power Routers 22

Risk Assessment IPR failure mechanism • No data available on IPR failure probability • Need to understand failure mechanisms – Computer Hardware – Power Hardware • Literature search well under way for both – Software • Data Routers info will be used to make an initial estimate on failure probability. October 23 -24 2003 Data Router Intelligence Comp Hardware Software Switch Power Hardware IPR EPNES: Intelligent Power Routers 23

Education Year-to-Date Accomplishments • Proposed: – Development of economics and ethics modules • Achieved: – Developed a module on ethics – Offered two ethics seminars • Ethical and Social Implications in Engineering • Integrating Ethics to the Curriculum – Proposed a new EE Course on economic issues – Started collaboration with Social Sciences (modules to assess student perceptions) – Introduced IPR concept in graduate courses – Offered IPRs seminars • integration of research into undergraduate education • recruit students • disseminate our results October 23 -24 2003 EPNES: Intelligent Power Routers 24

DC Zonal Electric Distribution System (DCZEDS) with Centralized Controller Central Controller Characteristics • Global State Information • Controller decisions can achieve global optimality. • Reliability issues.

DCZEDS with Distributed Controller Controller Characteristics • Local State Information • Quality is an issue in controller decisions. • Potential to improve survivability and reliability.

Intelligence in the IPR • Flat system: no supervisory control • Solving a dynamic optimization (or control) problem • Different Concepts to be Explored – Agents – Biologically collaborative schemes

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Outline ü Background and Problem Statement ü Analogy: IPRs and Data Networks ü Report on project activities • Year 1 Accomplishments Summary • Year 2 Proposed activities October 23 -24 2003 EPNES: Intelligent Power Routers 31

What we accomplished in year 1 üDeveloped first generation IPR software models üDeveloped first generation communication and data exchange mechanism for IPR üStudied the DC Zonal Electric Distribution System (DCZEDS) üStudied the power system restoration problem, using particle swarm optimization üStarted to determine IPR failure modes thru analogy to data routers üDeveloped economics and ethics modules üOne accepted paper, two under review October 23 -24 2003 EPNES: Intelligent Power Routers 32

What we promise for year 2 … • Disseminate results from iteration 0 • Design of alternative IPR control algorithms • Perform simulations for preliminary reliability assessment on IPR-based system • Design of second generation of IPR software model • Evaluate alternative IPR control algorithms • Use economics and ethics modules in electrical engineering courses and use assessment tools • Develop a short course for non-power engineering majors October 23 -24 2003 EPNES: Intelligent Power Routers 33

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