Neural Computing and Applications

, Volume 30, Issue 9, pp 2709–2723 | Cite as

Toward intelligent transient stability enhancement in inverter-based microgrids

  • Rahmat Khezri
  • Sajjad GolshannavazEmail author
  • Shoresh Shokoohi
  • Hassan Bevrani
Original Article


Nowadays, the concept of multiple inverter-interfaced distributed generations (IIDGs)-based MG is recognized as a renowned notion. Encountering unexpected transient situations, the fast inflexible response of IIDG may contribute in serious concerns over its successful operation. Contemplating the transient stability paradigm, first swing stability of the investigated system is the mostly pinpointed matter. In the state-of-the-art indices in transient analysis of IIDG-based technologies, the current index is referred as the frequently deployed one. However, this index is capped within the switches’ twice rated current to afford the inverter’s physical constraints. To tackle this requirement, the ongoing study aims at devising an efficient transient current control loop (TCCL) embedded as a part of main control procedure. In this practice, the well-known simple proportional–integral (PI) controller, as the most persuasive industrial choice, is regarded as the supplementary TCCL key unit. The main functionality of the founded TCCL is deemed as a talented transient current limiter in IIDGs during the versatile possible short-circuit situations. In spite of this, the conventional fixed tuning of gains in PI controller would depreciate its safe and reliable operation encountering different contingencies. To rehabilitate this matter, fuzzy logic and artificial neural network concepts are deployed for realizing an adaptive PI controller capable of handling both the connected and autonomous modes of operation. Precise numerical studies are carried out to interrogate the performance of the proposed approach. Results are analyzed in depth.


Microgrids Inverter-interfaced distributed generations (IIDGs) Transient stability enhancement Transient current control loop (TCCL) Fuzzy logic (FL) Artificial neural network (ANN) 


  1. 1.
    Bevrani H, Watanabe M, Mitani Y (2012) “Microgrid controls”, in standard handbook for electrical engineers. McGraw-Hill, New YorkGoogle Scholar
  2. 2.
    Gholami A, Aminifar F (2015) A hierarchical response-based approach to the load restoration problem. IEEE Trans Smart Grid 99:7352361. doi: 10.1109/TSG.2015.2503320 CrossRefGoogle Scholar
  3. 3.
    Shekari T, Aminifar F, Sanaye-Pasand M (2016) An analytical adaptive load shedding scheme against severe combinational disturbances. IEEE Trans Power Syst 31(5):4135–4143CrossRefGoogle Scholar
  4. 4.
    Shekari T, Gholami A, Aminifar F, Sanaye-Pasand M (2016) An adaptive wide-area load shedding scheme incorporating power system real-time limitations. IEEE Syst J. doi: 10.1109/JSYST.2016.2535170 CrossRefGoogle Scholar
  5. 5.
    Gholami A, Shekari T, Aminifar F, Shahidehpour M (2016) Microgrid scheduling with uncertainty: the quest for resilience. IEEE Trans Smart Grid 7(6):2849–2858CrossRefGoogle Scholar
  6. 6.
    Shekari T, Gholami A, Aminifar F (2014) Optimal parking lot placement considering operational and security limitations using COA. In: Smart grid conference (SGC), Tehran, pp 1–6Google Scholar
  7. 7.
    Bevrani H, Watanabe M, Mitani Y (2014) Power system monitoring and control. Wiley, HobokenCrossRefGoogle Scholar
  8. 8.
    Pecas Lopes JA, Moreira CL, Madureira AG (2006) Defining control strategies for microgrids islanded operation. IEEE Trans Power Syst 21(2):916–924CrossRefGoogle Scholar
  9. 9.
    Bevrani H, Shokoohi Sh (2013) An intelligent droop control for simultaneous voltage and frequency regulation in islanded microgrids. IEEE Trans Smart Grid 4(3):1505–1513CrossRefGoogle Scholar
  10. 10.
    Ahmadi S, Shokoohi Sh, Bevrani H (2014) A fuzzy logic-based droop control for simultaneous voltage and frequency regulation in an AC microgrid. Int J Elect Power Energy Syst 64(15):148–155Google Scholar
  11. 11.
    Al-Saedi W, Lachiwicz SW, Habibi D, Bass O (2013) Voltage and frequency regulation based DG unit in an autonomous microgrid operation using particle swarm optimization. Int J Electr Power Energy Syst 53(4):742–751CrossRefGoogle Scholar
  12. 12.
    Bevrani H, Habibi F, Babahajyani P, Watanabe M, Mitani Y (2012) Intelligent frequency control in an AC microgrid: online PSO-based fuzzy tuning approach. IEEE Trans Smart Grid 3(4):1935–1944CrossRefGoogle Scholar
  13. 13.
    Bevrani H, Feizi MR, Ataee S (2015) Robust frequency control in an islanded microgrid: H and μ-synthesis approaches. IEEE Trans Smart Grids, pp 1–12Google Scholar
  14. 14.
    Majumder R (2013) Some aspects of stability in microgrids. IEEE Trans Power Syst 28(3):3243–3252CrossRefGoogle Scholar
  15. 15.
    Pogaku N, Prodanovic M, Green TC (2007) Modeling, analysis and testing of autonomous operation of an inverter-based microgrid. IEEE Trans Power Electr 22(2):613–625CrossRefGoogle Scholar
  16. 16.
    Tang X, Deng W, Qi Z (2013) Investigation of the dynamic stability of microgrid. IEEE Trans Power Syst 29(2):698–702CrossRefGoogle Scholar
  17. 17.
    Rowe ChN, Summers TJ, Betz RE, Cornforth DJ, Moore TG (2013) Arctan power-frequency droop for improved microgrid stability. IEEE Trans Power Electr 28(8):3747–3759CrossRefGoogle Scholar
  18. 18.
    Iyer ShV, Belur MN, Chandorkar MC (2010) A generalized computational method to determine stability of a multi-inverter microgrid. IEEE Trans Power Electr 25(9):2420–2432CrossRefGoogle Scholar
  19. 19.
    Mohamed YI, El-Saadany EF (2008) Adaptive decentralized droop controller to preserve power sharing stability of paralleled inverters in distributed generation microgrids. IEEE Trans Power Electr 23(6):2806–2816CrossRefGoogle Scholar
  20. 20.
    Kasem Alaboudy AH, Zeineldin HH, Kirtley JL (2012) Microgrid stability characterization subsequent to fault-triggered islanding incidents. IEEE Trans Power Deliv 27(2):658–669CrossRefGoogle Scholar
  21. 21.
    Ashabani SM, Mohamed YI (2012) A flexible control strategy for grid-connected and islanded microgrids with enhanced stability using nonlinear microgrid stabilizer. IEEE Trans Smart Grid 3(3):1291–1301CrossRefGoogle Scholar
  22. 22.
    Li Y, Zhang P, Zhang L, Wang B (2017) Active synchronous detection of deception attacks in microgrid control systems. IEEE Trans Smart Grid 8(1):373–375CrossRefGoogle Scholar
  23. 23.
    Kundur P, Paserba J, Ajjarapu V, Andersson G, Bose A, Canizares C, Hatziargyriou N, Hill D, Stankovic A, Taylor C, Van Cutsem T, Vittal V (2004) Definition and classification of power system stability. IEEE Trans Power Syst 19(2):1387–1401Google Scholar
  24. 24.
    Chen X, Pei W, Tang X (2010) Transient stability analysis of micro-grids with multiple distributed generations. In: Proceedings of IEEE power system technology conference (POWERCON), pp 1–8Google Scholar
  25. 25.
    Baran ME, El-Markaby I (2005) Fault analysis on distributed feeders with distributed generators. IEEE Trans Power Syst 20(4)Google Scholar
  26. 26.
    Lasseter R (2002) Integration of distributed energy resources: the CERTS microgrid concept. CERT ReportGoogle Scholar
  27. 27.
    IEEE Committee Report (1968) Proposed definitions of terms for reporting and analyzing outages of electrical transmission and distribution facilities and interruptions. IEEE Trans Power Appl Syst PAS-87(5):1318–1323CrossRefGoogle Scholar
  28. 28.
    Katiraei F, Iravani M (2005) Transients of a micro-grid system with multiple distributed energy resources. In: Proceedings of the international conference on power system transients (IPST05)Google Scholar
  29. 29.
    Wall SR (2001) Performance of inverter interfaced distributed generation. In: IEEE/PES transmission and distribution conference and exposition, pp 945–950Google Scholar
  30. 30.
    Keller J, Kroposki B (2010) Understanding fault characteristics of inverter-based distributed energy resources. Technical Report NREL/TP-550- 46698, National Renewable Energy LaboratoryGoogle Scholar
  31. 31.
    Radial Test Feeders—IEEE Distribution System Analysis Subcommittee. [Online].
  32. 32.
    Zadeh A (1965) Fuzzy sets. Inf Control 8:338–353CrossRefGoogle Scholar
  33. 33.
    Bevrani H, Hiyama T (2011) Intelligent automatic generation control. CRC, New YorkGoogle Scholar
  34. 34.
    Mamdani EH (1974) Application of fuzzy algorithms for control of dynamic plant. Proc IEEE 121(12):1585–1588Google Scholar
  35. 35.
    Hagan MT, Demuth HB, Beale MH (1996) Neural network design. PWS Pub, BostonGoogle Scholar
  36. 36.
    Bevrani H, Habibi F, Shokoohi S (2012) ANN-based self-tuning frequency control design for an isolated microgrid. In: Meta-heuristics optimization algorithms in engineering, business, economics, and finance, p 357Google Scholar

Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  • Rahmat Khezri
    • 1
  • Sajjad Golshannavaz
    • 2
  • Shoresh Shokoohi
    • 1
  • Hassan Bevrani
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of KurdistanSanandajIran
  2. 2.Electrical Engineering DepartmentUrmia UniversityUrmiaIran

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