DOI QR코드

DOI QR Code

Probabilistic Evaluation of Voltage Quality on Distribution System Containing Distributed Generation and Electric Vehicle Charging Load

  • CHEN, Wei (Dept of Electrical Engineering and Information Engineering, Lanzhou University of Technology) ;
  • YAN, Hongqiang (Dept of Electrical Engineering and Information Engineering, Lanzhou University of Technology) ;
  • PEI, Xiping (Dept of Electrical Engineering and Information Engineering, Lanzhou University of Technology)
  • Received : 2016.10.15
  • Accepted : 2017.05.11
  • Published : 2017.09.01

Abstract

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

Keywords

Composite sampling method;Distributed generator;Electric vehicle charging load;Probabilistic load flow;Voltage quality

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. Doaa Khalil Ibrahim, Essam El Din Abo El Zahab, Saadoun Abd El Aziz Mostafa, "New Coordination Approach to Minimize the Number of Re-adjusted Relays When Adding DGs in Interconnected Power Systems," Journal of Electrical Engineering & Technology, vol. 12, pp. 502-512, March.2017. https://doi.org/10.5370/JEET.2017.12.2.502
  2. G. Marchesan, M.R. Muraro, G. Cardoso Jr, "Method for distributed generation anti-islanding protection based on singular value decomposition and linear discrimination analysis," Electric Power Systems Research, vol. 130, pp. 124-131, Oct. 2016. https://doi.org/10.1016/j.epsr.2015.08.025
  3. M. Fan, V. Vittal, G. Heydt, R. Ayyanar, "Probabilistic power flow analysis with generation dispatch including photovoltaic resource," IEEE Transactions on Power Systems, vol. 28, pp. 1797-1805, Feb. 2013. https://doi.org/10.1109/TPWRS.2012.2219886
  4. Wei CHEN, Hongqiang YAN, Xiping PEI, Butuo WU, "A Quasi Monte Carlo Probabilistic Load Flow Method of Distribution System Containing Distributed Generation and Electric Vehicle Charging Load Based on Sobol Sequence," in Proceedings of the 7th China International Conference on Electricity Distribution, Xi'an, China, August 2016.
  5. J. Romero-Ruiz, J. Perez-Ruiz, S. Martin, J. A. Aguado, S. De la Torre, "Probabilistic congestion management using EVs in a smart grid with intermittent renewable generation," Electric Power Systems Research, vol. 137, pp. 155-162, June. 2016. https://doi.org/10.1016/j.epsr.2016.03.015
  6. D. Jayaweera, S. Islam, "Steady-state security in distribution networks with large wind farms," Power System Clean Energy, vol. 2, pp. 134-142, July. 2014. https://doi.org/10.1007/s40565-014-0052-4
  7. C. S. Saunders, "Point estimate method addressing correlated wind power for probabilistic optimal power flow," IEEE Transactions on Power Systems, vol. 29, pp. 1045-1054, Oct. 2014.
  8. E. Arriagada, E. Lopez, M. Lopez, R. Blasco-Gimenez, C. Roa, M. Poloujadoff, "A probabilistic economic dispatch model and methodology considering renewable energy, demand and generator uncertainties," Electric Power Systems Research, vol. 121, pp. 325-332, Nov. 2015. https://doi.org/10.1016/j.epsr.2014.11.018
  9. Wei CHEN, Hongqiang YAN, Xiping PEI, Butuo WU. "Probabilistic Load Flow Calculation in Distribution System Considering the Stochastic Characteristic of Wind Power and EVCL." in Proceedings of IEEE PES Asia-Pacific Power and Energy Engineering Conference, Xi'an, China, October 2016.
  10. M.S. ElNozahy, M.M.A. Salama, "Probabilistic ESS sizing and scheduling for improved integration of PHEVs and PV systems in residential distribution systems," Electric Power Systems Research, vol. 125, pp. 55-66, Oct. 2015. https://doi.org/10.1016/j.epsr.2015.03.029
  11. M. Aien, M. Fotuhi-Firuzabad, M. Rashidinejad, "Probabilistic optimal power flow in correlated hybrid wind-photovoltaic power systems," Power System Clean Energy, vol. 5, pp. 130-138, May. 2014.
  12. A.Y. Abdelaziz, Y.G. Hegazy, Walid El-Khattam, M. M. Othman, "Optimal allocation of stochastically dependent renewable energy based distributed generators in unbalanced distribution networks," Electric Power Systems Research, vol. 119, pp. 34-44, Feb. 2015. https://doi.org/10.1016/j.epsr.2014.09.005
  13. X. Bian, Y. Geng, F. Yuan, L. Kwok L, Y. Fu, "Identification and improvement of probabilistic voltage instability modes of power system with wind power integration," Electric Power Systems Research, vol. 130, pp. 1-11, August. 2016. https://doi.org/10.1016/j.epsr.2015.08.009
  14. M.K. Gray, W.G. Morsi, "Probabilistic quantification of voltage unbalance and neutral current in secondary distribution systems due to plug-in battery electric vehicles charging," Electric Power Systems Research, vol. 133, pp. 249-256, June. 2016. https://doi.org/10.1016/j.epsr.2015.12.022
  15. C. Wu, F. Wen, Y. Lou, "Probabilistic load flow analysis of photovoltaic generation system with plug-in electric vehicles," Electric Power Systems Research, vol. 64, pp. 1221-1228, Jan. 2015. https://doi.org/10.1016/j.ijepes.2014.09.014
  16. B. Borkowska, "Probabilistic load flow," IEEE Trans on Power Apparatus and Systems, vol. 27, pp. 752-759, 1974.
  17. X. Li, J. Cao, D. Du, "Probabilistic optimal power flow for power systems considering wind uncertainty and load correlation," Power System Clean Energy, vol. 148, pp. 240-247, 2014.
  18. G. Neeraj, P. Vinay, D. Biswarup, "Probabilistic load flow incorporating generator reactive power limit violations with spline based reconstruction method," Electric Power Systems Research, vol. 106, pp. 203-213, Oct. 2014. https://doi.org/10.1016/j.epsr.2013.08.011
  19. F. J. Ruiz-Rodriguez, J. C. Hernandez, F. Jurado, "Probabilistic load flow for photovoltaic distributed generation using the Cornish-Fisher expansion," Electric Power Systems Research, vol. 89, pp. 129-138, Jan. 2012. https://doi.org/10.1016/j.epsr.2012.03.009
  20. M. Fan, V. Vittal, G. Heydt, "Probabilistic power flow studies for transmission systems with photovoltaic generation using cumulants," IEEE Transactions on Power Systems, vol. 27, pp. 2251-2261, June. 2012. https://doi.org/10.1109/TPWRS.2012.2190533
  21. D. Cai, D. Shi, J. Chen, "Probabilistic load flow computation using Copula and Latin hypercube sampling," IET Gener. Transm. Distrib, vol. 8, pp. 1539-1549, August. 2014. https://doi.org/10.1049/iet-gtd.2013.0649
  22. Z. Shu, P. Jirutitijaroen, "Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources," IEEE Transactions on Power Systems, vol. 26, pp. 2066-2073, Jan. 2011.
  23. M. Hajian, W.D. Rosehart, H. Zareipour, "Probabilistic power flow by Monte Carlo simulation with latin supercube sampling," IEEE Trans on Power Apparatus and Systems, vol. 28, pp. 1550-1559, Feb. 2013. https://doi.org/10.1109/TPWRS.2012.2214447
  24. M. Mohammadi, A. Shayegani, H. Adaminejad, "A new approach of point estimate method for probabilistic load flow," IEEE Transactions on Power Delivery, vol. 51, pp. 54-60, Oct. 2013.
  25. Q. Xiao, "Comparing three methods for solving probabilistic optimal power flow, Electr," Electric Power Systems Research, vol. 124, pp. 92-99, 2015. https://doi.org/10.1016/j.epsr.2015.03.001
  26. Y. Chen, J. Wen, S. Cheng, "Probabilistic load flow method based on Nataf transformation and Latin hypercube sampling," IEEE Trans. Sustain. Energy, vol. 4, pp. 294-301, Feb. 2013. https://doi.org/10.1109/TSTE.2012.2222680
  27. Z. Shu, P. Jirutitijaroen, "Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources," IEEE Transactions on Power Systems, vol. 26, pp. 2066-2073, 2011.
  28. Camille Hamon, Magnus Perninge, Lennart Soder, "An importance sampling technique for probabilistic security assessment in power systems with large amounts of wind power," Electric Power Systems Research, vol. 131, pp. 11-18, Jan.2016. https://doi.org/10.1016/j.epsr.2015.09.016
  29. A. Carpinone, M. Giorgio, R. Langella, A. Testa, "Markov chain modeling for very-short-term wind power forecasting," Electric Power Systems Research, vol. 122, pp. 152-158, April. 2015. https://doi.org/10.1016/j.epsr.2014.12.025
  30. Jose Nuno Fidalgoa, Manuel Antonio Matosb, Luis Ribeiroc, "A new clustering algorithm for load profiling based on billing data," Electric Power Systems Research, vol. 82, pp. 27-33, Feb. 2012. https://doi.org/10.1016/j.epsr.2011.08.016
  31. Q. Kejun, Z. Chengke, M. Allan, Y. Yue, "Modeling of load demand due to EV battery charging in distribution systems," IEEE Transactions on Power Systems, vol. 26, pp. 802-810, 2011. https://doi.org/10.1109/TPWRS.2010.2057456
  32. H. Huang, C. Chung, K. Chan, H. Chen, "Quasimonte carlo based probabilistic small signal stability analysis for power systems with plug-in electric vehicle and wind power integration," IEEE Transactions on Power Systems. vol. 28, pp. 3335-3343, July.2013. https://doi.org/10.1109/TPWRS.2013.2254505
  33. H. Nima. Tehrani, P. Wang, "Probabilistic estimation of plug-in electric vehicles charging load profile," Electric Power Systems Research, vol. 124, pp. 133-143, 2015. https://doi.org/10.1016/j.epsr.2015.03.010
  34. Y. Liu, S. Gao, H. Cui, L. Yu, "Probabilistic load flow considering correlations of input variables following arbitrary distributions," Electric Power Systems Research, vol. 130, pp. 1-9, April.2016. https://doi.org/10.1016/j.epsr.2015.08.009
  35. P. Anderson, "Power system control and stability," The Iowa State University Press, Iowa, USA. 1977.
  36. Pil Sung Woo, Balho H. Kim, "Methodology of Cyber Security Assessment in the Smart Grid," Journal of Electrical Engineering & Technology, vol. 12, pp. 495-501, 2017. https://doi.org/10.5370/JEET.2017.12.2.495
  37. Rade MC, Antonio PF, "Observing the performance of distribution systems with embedded generators," European Transactions on Electrical Power, vol. 14, pp. 347-359, 2002.