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Large scale simulation ship power system hebner-herbst-gatozzi - july 2010
1. Large Scale Simulation of a Ship Power System with Energy Storage and Multiple Directed Energy Loads R. E. Hebner, J. D. Herbst, A. L. Gattozzi Center for Electromechanics University of Texas, Austin July 13, 2010
2. Presentation Overview Ship Design Challenges & Power System Studies CEM Ship Power System Model Modeling Issues & Simulation Alternatives Path Forward
3. Challenges to Naval Power System Designers Wide variety of loads on board Continuous duty to pulsed Loads with different requirements (low freq. ac, high freq. ac, dc) Generated power capacity minimally larger than averagetotal load and smaller than peak load Reliance on energy storage to supply intermittent loads Increased use of power electronics Need to maintain power quality and stability margins Need flexible architecture suitable for fault management and reconfiguration
4. Ship Power System Studies Modeling and Simulation play a crucial role Experimental data not easy to generate Difficult to reproduce the complexity of system interactions in subscale physical models Scarcity of accumulated experience with non-traditional energy resources and loads Models provide a common base to evaluate alternatives and study component interactions Key concerns: Scale of the model Modeling technique Software and Hardware Platforms Need a flexible tool for the ship designer, not application specific codes
5. CEM’s Notional Ship Power System Two turbo-generators with cross-connect option Two flywheel energy storage systems System designed around common 6 kVdc bus Subsystems modeled : Propulsion Hotel Loads Free Electron Laser (FEL) AN/SQQ-90 Sonar System Electromagnetic Rail Gun Active Denial System Advanced Radar Laser Weapon System Electromagnetic Aircraft Launch System
10. ACTIVE DENIAL EMGUN Voltage Current Current Power: Active – yellow Reactive-pink Heat Control Signals Voltage
11. Modeling Issues Modeling some very unusual loads, many still experimental or in the R&D stage Complex model results in long simulation times Typical values are σ≈ 100,000 (real time is σ = 1) 6 seconds simulated time = 1 week running time on a 64-bit, 3.16 GHz, 3.93 GB, dual core desktop.
12. Simulation Alternatives & Issues Segmentation of the simulation model Run one section at a time Creates interface issues similar to parallel processing Makes interpretation of results more difficult Compression of operating scenarios Not reflective of realistic operating scenarios Affects component interactions Prevents real time operator engagement Eliminated GUI due to impact on simulation times Makes interpretation of results more difficult
13. Multi-Rate / Multi-Core Options Expanded use of multi-rate techniques Models run now on dual rates Expansion to further levels is possible Multi-core calculations: MATLAB/Simulink version for parallel computations (Parallel Computing Toolbox) run on quad core computer resulting in speed gains of ~2-3:1 Third-party supported parallel MATLAB not being pursued now but remains an option MATLAB/Simulink run on computer cluster (Distributed Computing Server) in cooperation with the Texas Advanced Computing Center (TACC) Work is ongoing Goal is 10:1 speed gain Develop custom code to fully exploit parallel processing Kept as a last option due to cost and specificity of resulting code
14. Heterogeneous Computation FPGA assisted processing: FPGAs outperform CPUs by >1 order of magnitude in speed Potential solution should: 1. Retain broad utility of programs developed 2. High degree of generality Pursue COTS suppliers e.g. National Instruments (NI), Xilinx, etc.
15. Heterogeneous Computation NI offers a hybrid architecture that can be exploited by their LabView software LabView is an intrinsically parallel language Simulink is sequential Our model can be transferred to LabView and executed on NI’s RT-HPC system The University of Texas has a Long Term Working Relationship with National Instruments
16. Path Forward Heterogeneous computation appears to be a promising path to significant reductions in simulation times Capabilities of FPGA’s and GPU’s are increasing UT-CEM is seeking opportunities to apply these techniques to simulation of Naval power systems Exploring collaborations with National Instruments and Xilinx Questions?