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This work presents a maiden approach of coordinated frequency control of novel solar tower (ST)Archimedes wave energy conversion (AWEC)geothermal energy conversion (GEC)biodiesel driven generator (BDDG)energy storage (ES) units and direct current (DC) links based independent threearea interconnected microgrid system (ImGS). A recent metaheuristic technique, named butterfly optimisation algorithm (BOA) is applied to obtain the optimal gains of the controllers employed with the ImGS and system participation factors. The dynamic performance of proportional–integral derivative (PID), PID with filter (PIDN), proportional–fractionalorder integral derivative (PFOID) controllers with their gains tuned by different algorithms such as particle swarm optimisation (PSO), firefly algorithm (FA), whale optimisation algorithm (WOA), and BOA have been compared. Further, the effect of ES units and DC links in all the areas is analysed first time in ImGS. The results have established the superiority of the BOAbased PFOID controllers under different realworld scenarios in terms of frequency deviation, tieline power, and objective functions. Finally, rigorous sensitivity analysis has been conducted to evaluate the superiority of BOAoptimised PFOID controller towards preserving system stability of ImGS with ±25% change in synchronising tieline coefficients and bias values, and +20% change in loading condition without resetting the nominal condition gain values.
References


1)

1. Hirsch, A., Parag, Y., Guerrero, J.: ‘Microgrids: a review of technologies, key drivers, and outstanding issues’, Renew. Sust. Energy Rev., 2018, 90, pp. 402–411.

2)

2. Yoo, J.H., Nguyen, T.T., Kim, H.M.: ‘Multifrequency control in a standalone multi microgrid system using a backtoback converter’, Energies, 2017, 10, (6), p. 822.

3)

3. RuizCortes, M., GonzalezRomera, E., Lopes, R.A., et al: ‘Optimal charge/discharge scheduling of batteries in microgrids of prosumers’, IEEE Trans. Energy Convers., 2019, 34, (1), pp. 468–477, .

4)

4. Das, D.C., Roy, A.K., Sinha, N.: ‘GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system’, Int. J. Electr. Power Energy Syst., 2012, 43, (1), pp. 262–279.

5)

5. Das, D.C., Sinha, N., Roy, A.K.: ‘Automatic generation control of an organic rankine cycle solar–thermal/wind–diesel hybrid energy system’, Energy Technol., 2014, 2, (8), pp. 721–731.

6)

6. ‘Global review of solar tower technology’, .

7)

7. Hasanien, H.M.: ‘Gravitational search algorithmbased optimal control of Archimedes wave swingbased wave energy conversion system supplying a DC microgrid under uncertain dynamics’, IET Renew. Power Gener., 2017, 11, (6), pp. 763–770.

8)

8. ‘Geothermal power database’, .

9)

9. EiFergany, A.A., EiHameed, A.M.: ‘Efficient frequency controllers for autonomous twoarea hybrid microgrid system using socialspider optimizer’, IET Gener. Transm. Distrib., 2017, 11, (3), pp. 637–648.

10)

10. Xing, L., Wang, J., Dooner, M., et al: ‘Overview of current development in electrical energy storage technologies and the application potential in power system operation’, Appl. Energy, 2015, 137, pp. 511–536.

11)

11. Ray, P.K., Mohanty, S.R., Kishor, N.: ‘Proportional–integral controller based smallsignal analysis of hybrid distributed generation systems’, Energy Convers. Manage., 2011, 52, (4), pp. 1943–1954.

12)

12. Goya, T., Omine, E., Kinjyo, Y., et al: ‘Frequency control in isolated island by using parallel operated battery systems applying H∞ control theory based on droop characteristics’, IET Renew. Power Gener., 2011, 5, (2), pp. 160–166.

13)

13. Mallesham, G., Mishra, S., Jha, A.N.: ‘Ziegler–Nichols based controller parameters tuning for load frequency control in a microgrid’. Int. Conf. on Energy, Automation, and Signal (ICEAS), Bhubaneswar, Odisha, India, December 2011, pp. 1–8.

14)

14. Mohamed, T.H., Shabib, G., Hossam, A.: ‘Distributed load frequency control in an interconnected power system using ecological technique and coefficient diagram method’, Int. J. Electr. Power Energy Syst., 2016, 82, pp. 496–507.

15)

15. Zamani, A., Barakati, S.M., YousofiDarmian, S.: ‘Design of a fractional order PID controller using GBMO algorithm for load–frequency control with governor saturation consideration’, ISA Trans., 2016, 64, pp. 56–66.

16)

16. Ibraheem, N., Bhatti, T.S.: ‘AGC of two area power system interconnected by AC/DC links with diverse sources in each area’, Int. J. Electr. Power Energy Syst., 2014, 55, pp. 297–304.

17)

17. Barisal, A.K.: ‘Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multisource power system’, Int. J. Electr. Power Energy Syst., 2015, 66, pp. 67–77.

18)

18. Barisal, A.K.: ‘Improved PSO based automatic generation control of mutisource nonlinear power system interconnected by ACDC links’, Cogent Eng., 2018, 5, (1), pp. 1–20.

19)

19. Milano, F., Dorfler, F., Hug, G., et al: ‘Foundations and challenges of lowinertia systems’. 2018 Power Systems Computation Conf. (PSCC), Dublin, Ireland, 11–15 June 2018, pp. 1–25.

20)

20. Tungadio, D.H., Bansal, R.C., Siti, M.W.: ‘Optimal control of active power of two microgrids interconnected with two AC tielines’, Electr. Power Compon. Syst., 2017, 45, (19), pp. 2188–2199.

21)

21. Lal, D.K., Barisal, A.K., Tripathy, M.: ‘Load frequency control of multi area interconnected microgrid power system using grasshopper optimization algorithm optimized fuzzy PID controller’. Recent Advances on Engineering, Technology and Computational Sciences (RAETCS), Allahabad, India, 6–8 February 2018, pp. 1–6.

22)

22. Ranjan, S., Das, D.C., Behera, S.: ‘Parabolic trough solar–thermal–wind–diesel isolated hybrid power system: active power/frequency control analysis’, IET Renew. Power Gener., 2018, 12, (16), pp. 1893–1903.

23)

23. Latif, A., Pramanik, A., Das, D.C., et al: ‘Plug in hybrid vehiclewinddiesel autonomous hybrid power system: frequency control using FA and CSA optimized controller’, Int. J. Syst. Assur. Eng. Manag., 2018, 9, (5), pp. 1147–1158.

24)

24. Arora, S., Singh, S.: ‘Butterfly optimization algorithm: a novel approach for global optimization’, Soft Comput., 2019, 23, (3), pp. 715–734.

25)

25. Ramos, C.D.K.: ‘Model and control of solar tower for energy production’. , Instituto Superior Tecnico, 2015.

26)

26. Ramos, C.D.K.: ‘Model and control of solar tower for energy production’. , 2015.

27)

27. Hasanien, M.H.: ‘Whale optimisation algorithm for automatic generation control of interconnected modern power systems including renewable energy sources’, IET Gener. Transm. Distrib., 2018, 12, (3), pp. 607–614.

28)

28. Elgard, O.I.: ‘Electric energy system theory: an introduction’ (Tata McGrawHill, New Delhi, 1983, 2nd edn.).

29)

29. Barik, A.K., Das, D.C.: ‘Expeditious frequency control of solar photobiotic/biogas/biodiesel generator based isolated renewable microgrid using Grasshopper Optimisation Algorithm’, IET Renew. Power Gener., 2018, 12, (14), pp. 1659–1667.

30)

30. Chidambaram, A.I., Parasmasivam, B.: ‘Control performance standards based load frequency controller coordinating redox flow batteries coordinate with interline power flow controller’, Int. J. Power Sources, 2012, 219, pp. 292–304.

31)

31. Ponnusamya, M., Banakara, B., Dash, S.S., et al: ‘Design of integral controller for load frequency control of static synchronous series compensator and capacitive energy source based multi area system consisting of diverse sources of generation employing imperialistic compensation algorithm’, Int. J. Electr. Power Energy Syst., 2015, 73, pp. 863–871.

32)

32. Deng, Z., Cao, H., Li, X., et al: ‘Generalized predictive control for fractional order dynamic model of solid oxide fuel cell output power’, J. Power Sources, 2010, 195, pp. 8097–8103.

33)

33. Wang, H., Zeng, G., Dai, Y., et al: ‘Design of fractional order frequency controller for an islanded microgrid: a multiobjective external optimization method’, Energies, 2017, 10, (10), p. 1502.
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