# A Novel Control Strategy for Autonomous Operation of Isolated Microgrid with Prioritized Loads

Original Contribution

First Online:

## Abstract

Maintenance of power balance between generation and demand is one of the most critical requirements for the stable operation of a power system network. To mitigate the power imbalance during the occurrence of any disturbance in the system, fast acting algorithms are inevitable. This paper proposes a novel algorithm for load shedding and network reconfiguration in an isolated microgrid with prioritized loads and multiple islands, which will help to quickly restore the system in the event of a fault. The performance of the proposed algorithm is enhanced using genetic algorithm and its effectiveness is illustrated with simulation results on modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid.

## Keywords

Microgrid Load shedding Reconfiguration Genetic Algorithm Prioritized Loads## References

- 1.Y. Hu, N. Hua, C. Wang, J. Gong, X. Li, Research on distribution network reconfiguration, in
*Proceedings of the International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE)*, vol. 1 (2010), pp. 176–180Google Scholar - 2.H. Kim, Y. Ko, K.H. Jung, Artificial neural-network based feeder reconfiguration for loss reduction in distribution systems. IEEE Trans. Power Delivery
**8**(3), 1356–1366 (1993)CrossRefGoogle Scholar - 3.P. Kayal, S. Chanda, C. K. Chanda, An ANN based network reconfiguration approach for voltage stability improvement of distribution network, in
*Proceedings of the International Conference on Power and Energy Systems*(2011), pp. 1–7Google Scholar - 4.K. Nara, A. Shiose, M. Kitagawa, T. Ishihara, Implementation of genetic algorithm for distribution systems loss minimum reconfiguration. IEEE Trans. Power Syst.
**7**(3), 1044–1051 (1992)CrossRefGoogle Scholar - 5.Y.S. Jun, Y. Zhi, W. Yan, Y.Y. Xin, S.X. Yan, Distribution network reconfiguration with distributed power based on genetic algorithm, in
*Proceedings of 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies*(2011), pp. 811–815Google Scholar - 6.V. Farahani, B. Vahidi, H.A. Abyaneh, Reconfiguration and capacitor placement simultaneously for energy loss reduction based on an improved reconfiguration method. IEEE Trans. Power Syst.
**27**(2), 587–595 (2012)CrossRefGoogle Scholar - 7.Y.J. Jeon, J.C. Kim, Network reconfiguration in radial distribution system using simulated annealing and tabu search. Proceedings of Power Engineering Society Winter Meeting
**4**, 2329–2333 (2000)Google Scholar - 8.Y.J. Jeon, J.C. Kim, J.O. Kim, J.R. Shin, K. Lee, An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems. IEEE Trans. Power Delivery
**17**(4), 1070–1078 (2002)CrossRefGoogle Scholar - 9.B. Amanulla, S. Chakrabarti, S.N. Singh, Reconfiguration of power distribution systems considering reliability and power loss. IEEE Trans. Power Delivery
**27**(2), 918–926 (2012)CrossRefGoogle Scholar - 10.W.C. Wu, M.S. Tsai, F.Y. Hsu, A new binary coding particle swarm optimization for feeder reconfiguration, in
*Proceedings of the International Conference on Intelligent Systems Applications to Power Systems*(2007), pp. 1–6Google Scholar - 11.Y.T. Hsiao, Multiobjective evolution programming method for feeder reconfiguration. IEEE Trans. Power Syst.
**19**(1), 594–599 (2004)CrossRefGoogle Scholar - 12.M.S. Tsai, C.C. Chu, Applications of hybrid EP-ACO for power distribution system loss minimization under load variations, in
*Proceedings of the 16th International Conference on Intelligent System Application to Power Systems*(2011), pp. 1–7Google Scholar - 13.A. Swarnkar, N. Gupta, K. R. Niazi, Efficient reconfiguration of distribution systems using ant colony optimization adapted by graph theory, in
*Proceedings of the IEEE Power and Energy Society General Meeting*(2011), pp. 1–8Google Scholar - 14.F. Scenna, D. Anaut, L.I. Passoni, G.J. Meschino, Reconfiguration of electrical networks by an ant colony optimization algorithm. IEEE Latin America Transactions
**11**(1), 538–544 (2013)CrossRefGoogle Scholar - 15.X. Zhan, T. Xiang, H. Chen, B. Zhou, Z. Yang, Vulnerability assessment and reconfiguration of microgrid through search vector artificial physics optimization algorithm. Int. J. Electr. Power Energy Syst.
**62**, 679–688 (2014)CrossRefGoogle Scholar - 16.V.C. do Nascimento, G. Lambert-Torres, C.I. de Almeida Costa, L.E.B. da Silva, Control model for distributed generation and network automation for microgrids operation. Electr. Power Syst. Res.
**127**, 151–159 (2015)CrossRefGoogle Scholar - 17.H. Nafisi, V. Farahani, H. Askarian Abyaneh, M. Abedi, Optimal daily scheduling of reconfiguration based on minimisation of the cost of energy losses and switching operations in microgrids. IET Gener. Transm. Distrib.
**9**(6), 513–522 (2015)CrossRefGoogle Scholar - 18.A. Mokari-Bolhasan, H. Seyedi, B. Mohammadiivatloo, S. Abapour, S. Ghasemzadeh, Modified centralized ROCOF based load shedding scheme in an islanded distribution network. Int. J. Electr. Power Energy Syst.
**62**, 806–815 (2014)CrossRefGoogle Scholar - 19.A. Ketabi, M.H. Fini, An under frequency load shedding scheme for islanded microgrids. Int. J. Electr. Power Energy Syst.
**62**, 599–607 (2014)CrossRefGoogle Scholar - 20.W. Liu, W. Gu, Y. Xu, S. Xue, M. Chen, B. Zhao, M. Fan, Improved average consensus algorithm based distributed cost optimization for loading shedding of autonomous microgrids. Int. J. Electr. Power Energy Syst.
**73**, 89–96 (2015)CrossRefGoogle Scholar - 21.F. Shariatzadeh, C.B. Vellaithurai, S.S. Biswas, R. Zamora, A.K. Srivastava, Real-time implementation of intelligent reconfiguration algorithm for microgrid. IEEE Transactions on Sustainable Energy
**5**(2), 598–607 (2014)CrossRefGoogle Scholar - 22.N. Kumar, A. K. Srivastava, N. N. Schulz, Shipboard power system restoration using binary particle swarm optimization, in
*Proceedings of the 39th North American Power Symposium*(2007), pp. 164–169Google Scholar - 23.P. Mitra, G.K. Venayagamoorthy, Implementation of an intelligent reconfiguration algorithm for an electric ship’s power system. IEEE Trans. Ind. Appl.
**47**(5), 2292–2300 (2011)CrossRefGoogle Scholar - 24.S.H.K. Vuppalapatil, A.K. Srivastava, Application of ant colony optimisation for reconfiguration of shipboard power system. International Journal of Engineering, Science and Technology
**2**(3), 119–131 (2010)Google Scholar - 25.K.R. Padamati, N. Schulz, A.K. Srivastava, Application of genetic algorithm for reconfiguration of shipboard power system, in
*Proceedings of 39th North American Power Symposium*(2007), pp. 159–163Google Scholar - 26.D.E. Goldberg,
*Genetic Algorithms in Search, Optimization and Machine Learning*, 1st edn. (Addison Wesley Longman Publishing Co., Inc., Boston, 1989)zbMATHGoogle Scholar - 27.R. Lasseter, A. Akhil, C. Marnay, J. Stephens, J. Dagle, R. Guttromson, M. A. Sakis, R. Yinger, J. Eto, White Paper on Integration of Distributed Energy Resources, The CERTS MicroGrid Concept. Tech. Rep., Consortium for Electric Reliability Technology Solutions, California Energy Commission (2002)Google Scholar

## Copyright information

© The Institution of Engineers (India) 2018