© The Institution of Engineering and Technology
In order to diminish the impacts brought by high penetration of renewable energy on the reliability of distribution systems, some distribution networks (e.g. Chattanooga electric power board system) have deployed smart switches (SSs) to island some areas to mitigate outage losses. However, due to intermittency and sharply changing rate of renewable energy, it is likely to experience insufficient or excessive power for islanded areas. Therefore, a microgrid controller featured with flexible boundaries is proposed. With proposed microgrid controller, the microgrid can not only shrink or expand its boundaries according to current renewable energy supply, but also disconnect/connect to the main grid with a designated SS. Moreover, to ensure the microgrid controller could obtain suitable boundaries on the time scale of seconds, a real-time power management technique with alternative generating algorithm is designed to generate all possible alternative boundaries and choose the optimal one, which is scalable to any topology. In addition, in order to maintain state of charge of batteries within a desirable range, anti-overcharge/discharge strategies are designed. Four comprehensive experiments verify that the implementation of the microgrid controllers can realise flexible boundaries and deal with sharply changing rate of renewable generation or load on the time scale of seconds.
References
-
-
1)
-
13. Schmidt, O., Hawkes, A., Gambhir, A., et al: ‘The future cost of electrical energy storage based on experience rates’, Nature Energy, 2017, 2, (8), pp. 1–5.
-
2)
-
36. Robert, T.: ‘Depth-first search and linear graph algorithms’, SIAM J. Comput., 1972, 1, (2), pp. 146–160.
-
3)
-
29. Du, Y., Lu, X., Wang, J., et al: ‘Distributed secondary control strategy for microgrid operation with dynamic boundaries’, IEEE Trans. Smart Grid, 2018, 10, (5), pp. 5269–5282.
-
4)
-
7. Carpinelli, G., Mottola, F., Proto, D., et al: ‘A multi-objective approach for microgrid scheduling,’ IEEE Trans. Smart Grid, 2017, 8, (5), pp. 2109–2118.
-
5)
-
20. Wang, Z., Wang, J.: ‘Self-healing resilient distribution systems based on sectionalization into microgrids’, IEEE Trans. Power Syst., 2015, 30, (6), pp. 3139–3149.
-
6)
-
35. Office of Power Technologies of the U.S. Department of Energy.: ‘White paper on integration of distributed energy resources—the microgrid concept’. .
-
7)
-
5. Kim, S.-T., Bae, S., Kang, Y.C., et al: ‘Energy management based on the photovoltaic HPCS with an energy storage device’, IEEE Trans. Ind. Electron., 2015, 62, (7), pp. 4608–4617.
-
8)
-
12. National Renewable Energy Lab.: ‘Economic analysis case studies of battery energy storage with SAM’. .
-
9)
-
2. Thirugnanam, K., Kerk, S.K., Yuen, C., et al: ‘Energy management for renewable micro-grid in reducing diesel generators usage with multiple types of battery’, IEEE Trans. Ind. Electron., 2018, 65, (8), pp. 6772–6786.
-
10)
-
30. Lasseter, R.H.: ‘Smart distribution: coupled microgrids’, Proc. IEEE, 2011, 99, (6), pp. 1074–1082.
-
11)
-
21. Chen, C., Wang, J., Qiu, F., et al: ‘Resilient distribution system by microgrids formation after natural disasters’, IEEE Trans. Smart Grid, 2016, 7, (2), pp. 958–966.
-
12)
-
10. Nelson, J.A.: ‘Effects of cloud-induced photovoltaic power transients on power system protection’. , California Polytechnic State University, San Luis Obispo, CA, 2010.
-
13)
-
19. Manshadi, S.D., Khodayar, M.E.: ‘Expansion of autonomous microgrids in active distribution networks’, IEEE Trans. Smart Grid, 2016, 9, (3), pp. 1878–1888.
-
14)
-
32. Ma, Y., Hu, X., Yin, H., et al: ‘Real-time control and operation for a flexible microgrid with dynamic boundary’. IEEE Energy Conversion Congress and Exposition, Portland, Oregon, September 2018, pp. 5158–5163.
-
15)
-
14. IRENA.: ‘Electricity storage and renewables: costs and markets to 2030’. .
-
16)
-
4. Mohammadi, A., Bahrami, S.: ‘An overview of future microgrids’, in Bahrami, S., Mohammadi, A. (Eds): ‘Smart microgrids’ (Springer, Cham), pp. 1–6.
-
17)
-
6. Kroposki, B., Lasseter, R., Ise, T., et al: ‘Making microgrids work’, IEEE Power Energy Mag.., 2008, 6, (3), pp. 40–53.
-
18)
-
22. Chen, B., Chen, C., Wang, J., et al: ‘Sequential service restoration for unbalanced distribution systems and microgrids’, IEEE Trans. Power Syst., 2018, 33, (2), pp. 1507–1520.
-
19)
-
15. Nassar, M.E., Salama, M.M.A.: ‘Adaptive self-adequate microgrids using dynamic boundaries’, IEEE Trans. on Smart Grid, 2016, 7, (1), pp. 105–113.
-
20)
-
34. Shahabi, M., Member, S., Haghifam, M.R., et al: ‘Microgrid dynamic performance improvement using a doubly fed induction wind generator’, IEEE Trans. Energy Convers., 2009, 24, (1), pp. 137–145.
-
21)
-
25. Poudel, S., Dubey, A.: ‘Critical load restoration using distributed energy resources for resilient power distribution system’, IEEE Trans. Power Syst., 2019, 34, (1), pp. 52–63.
-
22)
-
23. Kim, Y., Wang, J., Lu, X.: ‘A framework for load service restoration using dynamic change in boundaries of advanced microgrids with synchronous-machine DGs’, IEEE Trans. Smart Grid, 2018, 9, (4), pp. 3676–3690.
-
23)
-
16. Arefifar, S.A., Mohamed, Y.A.R.I., El-Fouly, T.H.M.: ‘Supply-adequacy-based optimal construction of microgrids in smart distribution systems’, IEEE Trans. Smart Grid, 2012, 3, (3), pp. 1491–1502.
-
24)
-
33. Zhen, S., Ma, Y., Wang, F., et al: ‘Operation of a flexible dynamic boundary microgrid with multiple islands’. IEEE Applied Power Electronics Conf. and Exposition, Anaheim, California, March 2019, pp. 548–554.
-
25)
-
9. Nisar, A., Thomas, M.S.: ‘Comprehensive control for microgrid autonomous operation with demand response’, IEEE Trans. Smart Grid, 2017, 8, (5), pp. 2081–2089.
-
26)
-
17. Arefifar, S.A., Mohamed, Y.A.R.I., El-Fouly, T.: ‘Optimized multiple microgrid-based clustering of active distribution systems considering communication and control requirements’, IEEE Trans. Ind. Electron., 2015, 62, (2), pp. 711–723.
-
27)
-
1. Michaelson, D., Mahmood, H., Jiang, J.: ‘A predictive energy management system using pre-emptive load shedding for islanded photovoltaic microgrids’, IEEE Trans. Ind. Electron., 2017, 64, (7), pp. 5440–5448.
-
28)
-
31. Pashajavid, E., Shahnia, F., Ghosh, A.: ‘Development of a self-healing strategy to enhance the overloading resilience of islanded microgrids’, IEEE Trans. Smart Grid, 2017, 8, (2), pp. 868–880.
-
29)
-
26. Che, L., Shahidehpour, M.: ‘Adaptive formation of microgrids with mobile emergency resources for critical service restoration in extreme conditions’, IEEE Trans. Power Syst., 2019, 34, (1), pp. 742–753.
-
30)
-
28. Shahnia, F., Bourbour, S., Ghosh, A.: ‘Coupling neighboring microgrids for overload management based on dynamic multicriteria decision-making’, IEEE Trans. Smart Grid, 2017, 8, (2), pp. 969–983.
-
31)
-
27. Arefi, A., Shahnia, F.: ‘Tertiary controller-based optimal voltage and frequency management technique for multi-microgrid systems of large remote towns’, IEEE Trans. Smart Grid, 2017, 9, (6), pp. 5962–5974.
-
32)
-
18. Gazijahani, F.S., Salehi, J.: ‘Robust design of microgrids with reconfigurable topology under severe uncertainty’, IEEE Trans. Sust. Energy, 2018, 9, (2), pp. 559–569.
-
33)
-
8. Hu, X., Liu, T.: ‘Co-optimisation for distribution networks with multi-microgrids based on a two-stage optimisation model with dynamic electricity pricing’, IET Gener. Transm. Distrib., 2017, 11, (9), pp. 2251–2259.
-
34)
-
3. Bacha, S., Picault, D., Burger, B., et al: ‘Photovoltaics in micro grids: an overview of grid integration and energy management aspects’, IEEE Ind. Electron. Mag., 2015, 9, (1), pp. 33–46.
-
35)
-
24. Arif, A., Wang, Z.: ‘Networked microgrids for service restoration in resilient distribution systems’, IET Gener. Transm. Distrib., 2017, 11, (14), pp. 3612–3619.
-
36)
-
11. Lazard.: ‘Lazard's levelized cost of storage analysis–version 4.0’. .
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2019.1576
Related content
content/journals/10.1049/iet-gtd.2019.1576
pub_keyword,iet_inspecKeyword,pub_concept
6
6