DOI QR코드

DOI QR Code

End-to-end system level modeling and simulation for medium-voltage DC electric ship power systems

  • Zhu, Wanlu (School of Electronics and Information, Jiangsu University of Science and Technology) ;
  • Shi, Jian (Department of Electrical and Computer Engineering, Mississippi State University) ;
  • Abdelwahed, Sherif (Department of Electrical and Computer Engineering, Mississippi State University)
  • Received : 2016.11.04
  • Accepted : 2017.04.16
  • Published : 2018.01.31

Abstract

Dynamic simulation is critical for electrical ship studies as it obtains the necessary information to capture and characterize system performance over the range of system operations and dynamic events such as disturbances or contingencies. However, modeling and simulation of the interactive electrical and mechanical dynamics involves setting up and solving system equations in time-domain that is typically time consuming and computationally expensive. Accurate assessment of system dynamic behaviors of interest without excessive computational overhead has become a serious concern and challenge for practical application of electrical ship design, analysis, optimization and control. This paper aims to develop a systematic approach to classify the sophisticated dynamic phenomenon encountered in electrical ship modeling and simulation practices based on the design intention and the time scale of interest. Then a novel, comprehensive, coherent, and end-to-end mathematical modeling and simulation approach has been developed for the latest Medium Voltage Direct Current (MVDC) Shipboard Power System (SPS) with the objective to effectively and efficiently capture the system behavior for ship-wide system-level studies. The accuracy and computation efficiency of the proposed approach has been evaluated and validated within the time frame of interest in the cast studies. The significance and the potential application of the proposed modeling and simulation approach are also discussed.

Keywords

References

  1. Abdelwahed, S., Asrari, A., Crider, J., Dougal, R., Faruque, M., Fu, Y., Langston, J., Lee, Y., Mohammadpour, H., Ouroua, A., 2013. Reduced order modeling of a shipboard power system. In: Electric Ship Technologies Symposium (ESTS). IEEE, pp. 256-263. IEEE.
  2. Ali, H., Dougal, R., Ouroua, A., Hebner, R., Steurer,M., Andrus,M., Langston, J., Schoder, K., Hovsapian, R., 2011. Cross-platform validation of notional baseline architecture models of naval electric ship power systems. In: Electric Ship Technologies Symposium (ESTS), 2011 IEEE. IEEE, pp. 78-83.
  3. Amy Jr., C., 2002. Considerations in the design of naval electric power systems. In: Power Engineering Society Summer Meeting, 2002 IEEE, vol. 1. IEEE, pp. 331-335.
  4. Andrus, M., 2010. Ngips Mvdc Baseline Architecture Definition C Rtds Implementation. Tech. Rep., Center for Advanced Power Systems, Florida State University.
  5. Andrus, M., Bosworth, M., Crider, J., Ouroua, H., Santi, E., Sudhoff, S., 2013. Notional System Models. Tech. Rep. ESRDC.
  6. Bash, M., Chan, R., Crider, J., Harianto, C., Lian, J., Neely, J., Pekarek, S., Sudhoff, S., Vaks, N., 2009. A medium voltage dc testbed for ship power system research. In: Electric Ship Technologies Symposium, 2009. ESTS 2009. IEEE. IEEE, pp. 560-567.
  7. Chiniforoosh, S., Jatskevich, J.,Yazdani,A., Sood,V.,Dinavahi,V.,Martinez, J.A., Ramirez,A., 2010.Definitions and applications of dynamic averagemodels for analysis of power systems. Power Deliv. IEEE Trans. 25 (4), 2655-2669. https://doi.org/10.1109/TPWRD.2010.2043859
  8. Cramer, A., Liu, X., Zhang, Y., Stevens, J., Zivi, E., 2015. Early-stage shipboard power system simulation of operational vignettes for dependability assessment. In: Electric Ship Technologies Symposium (ESTS), 2015 IEEE, pp. 382-387. http://dx.doi.org/10.1109/ESTS.2015.7157923.
  9. Doerry, N., 2009. Next generation integrated power systems (ngips) for the future fleet. In: IEEE Electric Ship Technologies Symposium.
  10. Doktorcik, C.J., May, 2011. Modeling and Simulatin of a Hybrid Ship Power System (Master's thesis). Purdue University.
  11. Ericsen, T., Hingorani, N., Khersonsky, Y., 2006. Power electronics and future marine electrical systems. Ind. Appl. IEEE Trans. 42 (1), 155-163. http://dx.doi.org/10.1109/TIA.2005.861306.
  12. Ferrante, M., Chalfant, J., Chryssostomidis, C., Langland, B., Dougal, R., 2015. Adding simulation capability to early-stage ship design. In: Electric Ship Technologies Symposium (ESTS), 2015 IEEE, pp. 207-212. http://dx.doi.org/10.1109/ESTS.2015.7157889.
  13. Ge, J., Huang, X., Xie, H., 2015. Fast equivalent model of isolated bidirectional dc-dc converters for dc microgrid study. In: Industrial Electronics' Society, IECON 2015-Conference of the IEEE, pp. 000031-000035.
  14. Hebner, R., Herbst, J., Gattozzi, A., 2010. Large scale simulations of a ship power system with energy storage and multiple directed energy loads. In: Proc. 2010 Grand Challenges in Modeling and Simulation, pp. 430-435.
  15. IEEE Std 1709-2010, 2010. IEEE Recommended Practice For 1 kv to 35 kv Medium-voltage Dc Power Systems on Ships, pp. 1-54. http://dx.doi.org/10.1109/IEEESTD.2010.5623440.
  16. Lahiri, S., 2011. Modeling and Simulation of Shipboard Integrated Power Systems (Ph.D. thesis). Drexel University.
  17. Langston, J., Steurer, M., Crider, J., Sudhoff, S., Lee, Y., Zivi, E., Dougal, R., Zhang, Y., Hebner, R., Ouroua, A., 2012. Waveform-level time-domain simulation comparison study of three shipboard power system architectures. In: Proc. 2012 Summer Computer Simulation Conference. Genoa, Italy.
  18. Mayer, J.S., Wasynczuk, O., 1991. An efficient method of simulating stiffly connected power systems with stator and network transients included. Power Syst. IEEE Trans. 6 (3), 922-929. http://dx.doi.org/10.1109/59.119230.
  19. Park, H., Sun, J., Pekarek, S., Stone, P., Opila, D., Meyer, R., Kolmanovsky, I., DeCarlo, R., 2015. Real-time model predictive control for shipboard power management using the ipa-sqp approach. Control Syst. Technol. IEEE Trans. PP 99, 1. http://dx.doi.org/10.1109/TCST.2015.2402233.
  20. Qi, L., 2006. Ac System Stability Analysis and Assessment for Shipboard Power Systems (Ph.D. thesis). Texas A&M University.
  21. Roddy, R.F., Hess, D.E., Faller, W., 2006. Neural Network Predictions of The 4-Quadrant Wageningen Propeller Series, Hydromechanics Department Report, NSWCCD-50-TR2006/004.
  22. Schmitt, K., 2010. Modeling and Simulation of an All Electric Ship in Random Seas (Master's thesis). Massachusetts Institute of Technology.
  23. Shampine, L.F., Reichelt, M.W., 1997. The matlab ode suite. SIAM J. Sci. Comput. 18 (1), 1-22. https://doi.org/10.1137/S1064827594276424
  24. Shi, J., Abdelwahed, S., Zhu, W., Amgai, R., 2015. Development of a controlbased performance management system for shipboard power systems. In: Electric Ship Technologies Symposium (ESTS), 2015 IEEE, pp. 129-134. http://dx.doi.org/10.1109/ESTS.2015.7157874.
  25. Stevens, J., Opila, D., Cramer, A., Zivi, E., 2015. Operational vignette-based electric warship load demand. In: Electric Ship Technologies Symposium (ESTS), 2015 IEEE, pp. 213-218. http://dx.doi.org/10.1109/ESTS.2015.7157890.
  26. Sudhoff, S.D., Corzine, K.A., Hegner, H.J., Delisle, D.E., 1996. Transient and dynamic average-value modeling of synchronous machine fed loadcommutated converters. Energy Convers. IEEE Trans. 11 (3), 508-514. http://dx.doi.org/10.1109/60.537001.
  27. Suryanarayana, H., Sudhoff, S., 2013. Average-value modeling of a peak-current controlled galvanically-isolated dc-dc converter for shipboard power distribution. In: Electric Ship Technologies Symposium (ESTS), 2013 IEEE. IEEE, pp. 152-161.
  28. Xue, Y., Xu, X., Habetler, T.G., Divan, D.M., 1990. A low cost stator flux oriented voltage source variable speed drive. In: Industry Applications Society Meeting, 1990., Conference Record of the, vol. 1, pp. 410-415.
  29. Zahedi, B., Norum, L., 2013. Modeling and simulation of all-electric ships with low-voltage dc hybrid power systems. Power Electron. IEEE Trans. 28 (10), 4525-4537. http://dx.doi.org/10.1109/TPEL.2012.2231884.
  30. Zhang, Y., Zhang, T., Wang, R., Liu, Y., Guo, B., 2015. Optimal operation of a smart residential microgrid based on model predictive control by considering uncertainties and storage impacts. Sol. Energy 122, 1052-1065. https://doi.org/10.1016/j.solener.2015.10.027

Cited by

  1. A Survey on Fault Detection, Isolation, and Reconfiguration Methods in Electric Ship Power Systems vol.6, pp.None, 2018, https://doi.org/10.1109/access.2018.2798505
  2. A novel approach for real-time implementation of MVDC shipboard power system reconfiguration vol.100, pp.None, 2018, https://doi.org/10.1016/j.ijepes.2018.01.037
  3. Controlling-strategy design and working-principle demonstration of novel anti-winding marine propulsion vol.12, pp.None, 2018, https://doi.org/10.1016/j.ijnaoe.2019.05.002
  4. Balancing loads of rotating generators utilizing VSC direct power controllers in a ship AC/DC smartgrid vol.182, pp.None, 2020, https://doi.org/10.1016/j.epsr.2020.106200
  5. Magnetic levitation planar motor and its adaptive contraction backstepping control for logistics system vol.13, pp.3, 2021, https://doi.org/10.1177/16878140211004782
  6. An ameliorative whale optimization algorithm (AWOA) for HES energy management strategy optimization vol.48, pp.None, 2018, https://doi.org/10.1016/j.rsma.2021.102033