Intelligent Power Routers for Distributed Coordination in Electric Energy Processing Networks Progress Report Agustín IrizarryCarlos Torres Manuel RodríguezIdalides Vergara José CedeñoJuan Jiménez Bienvenido VélezMarianela Santiago Miguel Vélez-ReyesNoel Figueroa Efraín O’Neill-CarrilloAlma Estremera Alberto Ramírez

October EPNES: Intelligent Power Routers2 Outline Background and Problem Statement Analogy: IPRs and Data Networks Report on project activities Year 1 Accomplishments Summary Year 2 Proposed activities

October EPNES: Intelligent Power Routers3 State-of-the-Art Power Delivery Producers P1P2 Pn P3 Consumers C1C2 C3 C4 GOAL: De-centralized System Reconfiguration with Minimal Human Intervention

October EPNES: 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

October EPNES: 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

October EPNES: 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

October EPNES: Intelligent Power Routers7 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 EPNES: Intelligent Power Routers8 Outline Background and Problem Statement Analogy: IPRs and Data Networks Report on project activities Year 1 Accomplishments Summary Year 2 Proposed activities

October EPNES: Intelligent Power Routers9 Distributed Data Routing S3 C1 S1 S2 C2 Data Consumer Data Network Data Servers Multiple redundant paths to move data between computers R1 R3 R4 R2 Routers

October EPNES: Intelligent Power Routers10 Re-routing in Response to Major Disturbances S3 C1 S1 C2 Data Consumer Data Servers R1 R3 R4 R2 S2 Data Packets Major Disturbance Data Network

October EPNES: Intelligent Power Routers11 Re-routing in Response to Major Disturbances S3 C1 S1 C2 Data Consumer Data Servers R1 R3 R4 R2 S2 Data Packets Major Disturbance Data Network

October EPNES: Intelligent Power Routers12 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 EPNES: Intelligent Power Routers13 Outline Background and Problem Statement Analogy: IPRs and Data Networks Report on project activities Year 1 Accomplishments Summary Year 2 Proposed activities

October EPNES: Intelligent Power Routers14 Restoration Models IPR Protocols Distributed Control Models IPR Architecture Project Organization Economics Education Risk Assessment

October EPNES: Intelligent Power Routers15 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 de- centralized restoration strategies Restoration Models IPR Protocols

October EPNES: Intelligent Power Routers16 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 Restoration Models

October EPNES: Intelligent Power Routers17 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 Restoration Models

October EPNES: Intelligent Power Routers18 Power System Restoration:Example Test System and Results: Total load served increased through the stages. At each stage, all the control and state variables remained within their feasible limits and the power balance constraints were satisfied. The restoration path was established and all loads were successfully served. 50% 25% 50% 100% 75%100% Restoration Completed Restoration Models WSCC Nine-Bus Test System

October EPNES: Intelligent Power Routers19 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] De-Centralized Communication & Control Protocols IPR Protocols

October EPNES: Intelligent Power Routers20 Modeling a Power Network As a Graph Link 1Link 2Link 3 Link 4Link 5Link 6 Link 7Link 8 Bus 1Bus 2 Bus 4 Bus 3 IPR 4IPR 3 IPR 1IPR 2 Src 1Src 3Src 2 Snk 2Snk 1 IPR Protocols IPR model: Vertices – IPRs on buses Edges – branches between buses Weight – power flow Edges have Priority/ Reliability measure Control Messages

October EPNES: Intelligent Power Routers21 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 IPR 4IPR 3 IPR 1IPR 2 Src 1Src 3Src 2 Snk 2Snk 1 PRLinkPriorityReliability Pr Pr Pr Pr Normal State — Normal State Message System going down — Request Power — Deny Request — Request Status — Response Status — Affirmative Response Restoration Process Table 1. Priority and Reliability IPR Protocols

October EPNES: Intelligent Power Routers22 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 [McCalley et.al.] –Need failure probability data Risk Assessment

October EPNES: Intelligent Power Routers23 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. Data Router Comp Hardware Switch Power Hardware Intelligence Software Risk Assessment IPR

October EPNES: Intelligent Power Routers24 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 EPNES: Intelligent Power Routers25 DC Zonal Electric Distribution System (DCZEDS) with Centralized Controller Central Controller Controller Characteristics Global State Information Controller decisions can achieve global optimality. Reliability issues. Distributed Control Models

October EPNES: Intelligent Power Routers26 Controller Characteristics Local State Information Quality is an issue in controller decisions. Potential to improve survivability and reliability. Controller DCZEDS with Distributed Control Distributed Control Models

October EPNES: Intelligent Power Routers27 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 Distributed Control Models

October EPNES: Intelligent Power Routers28 Proposed architecture for the Intelligent Power Router IPR Architecture Power Network Energy Sensors and Flow Control Devices ICCU Interfacing Circuits Sensor Input Switching Commands Intelligent Power Router Programmable Intelligent Communication and Control Unit

October EPNES: Intelligent Power Routers29 A Simple Switch-based IPR System IPR Architecture IPR Source Load sensor Transfer Switch Transfer Switch 1.Upon failure of a source, IPR decides which load to serve based on latest dynamic priorities 2.Decision can be any computable function 3.More complex configurations possible by modular composition of multiple levels of IPRs 4.Future IPRs based on more complex power flow control devices (e.g. FACTS)

October EPNES: Intelligent Power Routers30 Simulating the Simple IPR System IPR Architecture Source Current Sensor Power Lines Transfer Switch Load

October EPNES: Intelligent Power Routers31 Outline Background and Problem Statement Analogy: IPRs and Data Networks Report on project activities Year 1 Accomplishments Summary Year 2 Proposed activities

October EPNES: Intelligent Power Routers32 What we accomplished in year 1 Developed first generation IPR software models Developed first generation communication and data exchange mechanism for IPR Studied the DC Zonal Electric Distribution System (DCZEDS) Studied the power system restoration problem, using particle swarm optimization Started to determine IPR failure modes thru analogy to data routers Developed economics and ethics modules One accepted paper, two under review

October EPNES: Intelligent Power Routers33 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 EPNES: Intelligent Power Routers34