Document Type : Research paper


1 Department of Electrical Engineering, Medi-Caps University, Indore, India

2 Gokhale Education Society R.H.Sapat COEMS\&R, Nashik, India

3 Medi-Caps Univeristy, Indore, India


A sampling method is proposed related to-system state transition based Monte Carlo simulation (SSTMCS) for the adequacy assessment in the radial distribution system (RDS) in the presence of distributed generation (DG) termed as a composite distribution system (CDS). This method evaluates well-being indices such as probabilities, frequency, and duration indices in healthy, marginal, and risky states. A deterministic criterion is used for adequacy assessment. Samples are generated using a load flow program for RDS used in SSTMCS. The loss sensitivity factor is utilized for the positioning of DGs in RDS. DG capacity and load at buses are considered continuous random variables. Different cases are addressed to demonstrate the impact of varying DG capacities on well-being indices. Moreover, the results are compared with the state enumeration method (SEM). IEEE-33 bus RDS is considered for this study.


  1. Aravindhababu, S. Ganapathy, and K. R. Nayar, “A novel technique for the analysis of radial distribution systems,” Int J. Elect. Power Energy Syst., vol. 23, no. 3, pp. 167-171, 2001.
  2. Bompard, E. Carpaneto, G. Chicco, and R. Napoli, “ Convergence of the backward/forward sweep method for the load-flow analysis of radial distribution systems,” Int. J. Electr. Power & Energy Syst., vol. 22, no. 7, pp. 521-530, 2000.
  3. Singh, and T. Ghose, “ Improved radial load flow method,” Int. J. Electr. Power Energy Syst, vol. 44, no. 1, pp. 721-727, 2013.
  4. Jen-Hao Teng, “A direct approach for distribution system load flow solutions,” IEEE Trans. Power Delivery, vol. 18, no. 3, pp. 882-887, 2003.
  5. I. Dulau, and D. Bic˘ a, “ Influence of distributed generators˘ on power systems,” Procedia. Engg., vol. 181, pp. 791-795, 2017.
  6. C. V. Suresh, and E. J. Belwin, “ Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm,” Renewables: Wind, Water, and Solar, vol. 5, no. 1, pp. 1-8, 2018.
  7. B. Prakash, and C. Lakshminarayana, “ Multiple DG placements in radial distribution system for multi objectives using whale optimization algorithm,” Alexandria Eng. J., vol. 57, no. 4, pp. 2797-2806, 2018.
  8. A. Tavakoli Ghazi Jahani, P. Nazarian, A. Safari and M.R. Haghifam," Multi-objective grasshopper optimization algorithm based reconfiguration of distribution networks, " J. Oper. Autom. Power Eng., vol. 7, no. 2, pp. 148-156, 2019.
  9. Ghobadpour, M. Gandomkar, and J. Nikoukar, " Multiobjective function optimization for locating and sizing of distributed generation sources in radial distribution networks with fuse and recloser protection," J. Oper. Autom. Power Eng., vol. 9, no. 3, pp. 266-273, 2021.
  10. Salyani and J. Salehi," A Customer oriented approach for distribution system reliability improvement using optimal distributed generation and switch placement ", J. Oper. Autom. Power Eng., vol. 7, no. 2, pp. 246-260, 2019.
  11. Majidi and S. Nojavan, " Optimal sizing of energy storage system in a renewable-based microgrid under flexible demand side management considering reliability and uncertainties," J. Oper. Autom. Power Eng., vol. 5, no. 2, pp. 205-214, 2017.
  12. Salehi, F. S. Gazijahani and A. Safari," Stochastic simultaneous planning of interruptible loads, renewable generations and capacitors in distribution network, " J. Oper. Autom. Power Eng., vol. 10, no. 2, pp. 113-121, 2022.
  13. Billinton and W. Li," A system state transition sampling method for composite system reliability evaluation, " IEEE Trans. Power Syst., vol. 8, no. 3, pp. 761-770, 1993.
  14. J. Beshir, T. C. Cheng and A. S. A. Farag," Comparision of Monte Carlo simulation and state enumeration based adequacy assessment program: CREAM and COMREL, "Proce. 1996 Trans. Dist. Conf. exposition,1996.
  15. Wang, C. Guo and Q. H. Wu," A Cross-entropy-based three-stage sequential importance sampling for composite power system short-term reliability evaluation," IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4254-4263, 2013.
  16. Billinton, and G. Lian, “ Composite power system health analysis using a security constrained adequacy evaluation procedure,” IEEE Trans. Power Syst, vol. 9, no. 2, pp. 936-931, 1994.
  17. Billinton, and M. Fotuhi-Firuzabad, “A basic framework for generating system operating health analysis,” IEEE Trans. Power Syst., vol. 9, no. 3, pp. 1610-1617, 1994.
  18. G. Hegazy, M. M. A. Salama, and A. Y. Chikhani, “Adequacy assessment of distributed generation systems using Monte Carlo simulation,” IEEE Trans. Power Syst., vol. 18, no.1, pp. 48-52, 2003.
  19. Xu, and C. Singh, “Adequacy and economy analysis of distribution systems ıntegrated with electric energy storage and renewable energy resources,” IEEE Trans. Power Syst., vol. 27, no. 4, pp. 2332-2341, 2012.
  20. D. Arya, and A. Koshti," Probabilistic simulation approach for distributed generation (DG) capacity evaluation using artificial neural network representation of load duration curve,” J. Institution of Engg (India): Series B, vol. 93, no. 1, pp. 57-62, 2012.
  21. Billinton and L.Gan," A Monte Carlo simulation model for adequacy assessment of multi-area generating systems ", Third Int. Conf. Probabil. methods appli. Electric Power Syst., 1991.
  22. D. Arya, A. Koshti, and S. C. Choube, “Frequencyduration analysis of composite distribution system using a non-sequential Monte Carlo simulation,” Electr. Power Energy Syst., vol. 46, pp.17-25, 2013.
  23. Conti and S. A. Rizzo, “ Monte Carlo simulation by using a systematic approach to assess distribution system reliability considering ıntentional islanding,” IEEE Trans Power Delivery, vol. 30, no.1, pp. 64-73, 2015.
  24. Zhang, Q. Zhang, X. Wang, X. Li, C. Shen, and W. Du, “ Reliability evaluation method of offshore oil power system based on sequential hybrid method,” 5th Asia Conf. Power Electr. Eng. (ACPEE), 2020.
  25. Primadianto, and Chan-Nan Lu, “A review on distribution system state estimation,” IEEE Trans. Power Syst., vol. 32, no. 5, pp. 3875-3883, 2017.
  26. Y. Rubinstein and D. P. Kroese," Simulation and the Monte Carlo Methods", Wiley Publication,1981.
  27. D. Arya, and A. Koshti, “Distributed generation capacity reliability evaluation using safety index,” J. Institution of Engg(India): Series B, vol. 89, pp. 3-7, 2008.
  28. S. Halve, A. Koshti, and R. Arya, “ Statistical Analysis for active power loss ıncorporating distributed generation in distribution system,” 3rd Int. Conf. Electron. Communi. Aerospace Techn. (ICECA), 2019.
  29. Billinton and R. N. Allan," Reliability evaluation of engineering systems", Springer, Second edition, 1983.
  30. G. Das," Statistical methods: Combined Edition (Volume I and II)," McGraw-Hill Education India, First edition, 2017.