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Co-Simulation of Computer Networks and Power Grid. Joint work with Prof. M. Branicky, Dr. A. Al-Hammouri, and D. Agarwal. Prof. Vincenzo Liberatore. Research supported in part by NSF CCR-0329910, Department of Commerce
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Co-Simulation of Computer Networks and Power Grid Joint work with Prof. M. Branicky, Dr. A. Al-Hammouri, and D. Agarwal Prof. Vincenzo Liberatore Research supported in part by NSF CCR-0329910, Department of Commerce TOP 39-60-04003, Department of Energy DE-FC26-06NT42853, an OhioICE training grant, and the Wright Center for Sensor Systems Engineering.
Intelligent Power Grid • Power grid • Essential to economy, national security, public health • Mostly designed and deployed prior to microprocessors, computer networks • As a result, assets underutilized, subject to massive failures • Objectives • Collaborative management, planning, and operations • Situational awareness and control • Plug-and-play asset integration • Market dynamics • Reduce peak prices • Stabilize costs when supply is limited.
First step: Co-simulation • Modelica (www.modelica.org) • Modeling and simulation of large-scale physical systems • Several libraries (e.g., Standard, Power systems, Hydraulics, Pneumatics, Power train) • ns-2 (www.isi.edu/nsnam/ns/) • Simulating routing, transport, and application protocols over wired, wireless, local- and wide area networks • Integrating state-of-the-art simulators
Integrating Modelica & ns-2 • Electrical power systems • simulated using Modelica • DC & AC (abc & dqo) • generators, transmission lines, loads, machines, breakers & faults, … • Networks • simulated using ns-2
Configuration parameters Voltage set point PI controller P controller Voltage sensor Symmetrical capacitor Transient disturbance Transient disturbances Ground Rotational source PM generator Power sensor Impedance load
Results (1) • Multimedia application consumes only 0.25Mbps of the 3 Mbps bottleneck link
Results (2) • Multimedia application consumes 2.5 Mbps of the 3 Mbps bottleneck link
Conclusions • Intelligent Power Grid • Situational awareness and distributed control • Co-simulation • Joint simulation of networks and grid dynamics • Integration and synchronization of simulators • Example with remote sensing of voltage, network congestion