A Novel Hybrid Swarm Intelligence and Cuckoo Search Based Microgrid EMS for Optimal Energy Scheduling

Authors

  • Priyadarshini Balasubramanyam Faculty of Engineering and Applied Science, Ontario Tech University, Oshawa, ON L1G 0C5, Canada
  • Vijay K. Sood Faculty of Engineering and Applied Science, Ontario Tech University, Oshawa, ON L1G 0C5, Canada

DOI:

https://doi.org/10.13052/dgaej2156-3306.3843

Keywords:

Microgrid, PSO, CSA, Hybrid algorithm, optimization, EMS, Tertiary Control

Abstract

A grid-connected or islanded microgrid made up of distributed energy sources (DERs), requires a power management/dispatch system to control the power dispatch and meet the load demand in the system. At the tertiary control level in a typical microgrid, an optimal scheduling mechanism is used to manage the power generated from the local DERs, energy drawn from the grid and energy consumption by the load. This paper proposes a novel hybrid optimization technique for day-ahead scheduling in a smart-grid. A Hybrid Feedback PSO-MCS algorithm is implemented using swarm intelligence and cuckoo search to enhance the performance and obtain a cost-effective solution for a microgrid prosumer. A comparison has been made of the Hybrid Feedback PSO-MCS (HFPSOMCS) algorithm with PSO and modified CS (MCS) algorithm. The best performing algorithm among the three is executed in MATLAB/Simulink and Python IDE platforms to compare the execution time.

Downloads

Download data is not yet available.

Author Biographies

Priyadarshini Balasubramanyam, Faculty of Engineering and Applied Science, Ontario Tech University, Oshawa, ON L1G 0C5, Canada

Priyadarshini Balasubramanyam received the B.Eng. degree in Electrical & Electronics Engineering from University College of Engineering, Osmania University, India in 2018. She is currently working towards the Master’s degree in Electrical & Computer Engineering from Ontario Tech University, Canada. Her research interests include microgrids and its operation and control, energy management systems, optimization, and renewable energy.

Vijay K. Sood, Faculty of Engineering and Applied Science, Ontario Tech University, Oshawa, ON L1G 0C5, Canada

Vijay K. Sood obtained his Ph.D. in Power Electronics from the University of Bradford, England in 1977. From 1969–76, he was employed at the Railway Technical Centre, Derby, U.K. From 1976–2007, he was a Senior Researcher at IREQ (Hydro-Québec Research Institute) in Montreal, Quebec. In 2007, he joined Ontario Tech University in Oshawa, Ontario where he is now the Chair of the Department of Electrical, Computer and Software Engineering.

He is a Member of the Professional Engineers Ontario, a Life Fellow of the Institute of Electrical and Electronic Engineers (IEEE), a Fellow of the Engineering Institute of Canada (EIC) and Emeritus Fellow of the Canadian Academy of Engineering (CAE). His research interests are in the monitoring, control and protection of power systems using artificial intelligence techniques. Dr. Sood has published over 200 articles, 10 book chapters and written two books on HVDC Transmission.

References

W. Yuan, Y. Wang, D. Liu, F. Deng and Z. Chen, “Impacts of Inductor Nonlinear Characteristic in Multiconverter Microgrids: Modeling, Analysis, and Mitigation,” in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 8, no. 4, pp. 3333–3347, Dec. 2020.

Q. Jiang, M. Xue and G. Geng, “Energy Management of Microgrid in Grid-Connected and Stand-Alone Modes,” in IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 3380–3389, Aug. 2013.

I. U. Nutkani, P. C. Loh, P. Wang and F. Blaabjerg, “Decentralized Economic Dispatch Scheme with Online Power Reserve for Microgrids,” in IEEE Transactions on Smart Grid, vol. 8, no. 1, pp. 139–148, Jan. 2017.

I. U. Nutkani, P. C. Loh and F. Blaabjerg, “Droop Scheme with Consideration of Oper-ating Costs,” in IEEE Transactions on Power Electronics, vol. 29, no. 3, pp. 1047–1052, March 2014.

Carvallo, Juan, Schnitzer, Daniel, Lounsbury, Deepa, Deshmukh, Ranjit, Apt, Jay and Kammen, Daniel. (2014). Microgrids for Rural Electrification: A critical review of best practices based on seven case studies.

Aftab Ahmad Khan, Muhammad Naeem, Muhammad Iqbal, Saad Qaisar, Alagan Anpalagan, “A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids,” Renewable and Sustainable Energy Re-views, Volume 58, 2016, Pages 1664–1683, ISSN 1364-0321.

J. Raya-Armenta, N. Bazmohammadi, J. Avina-Cervantes, D. Saez, J. Vasquez, and J. Guerrero, “Energy management system optimization in islanded microgrids: An over-view and future trends,” Renew. Sustain. Energy Rev., vol. 149, pp. 1–20, Dec. 2021.

K. Zhou, S. Yang, Z. Chen, and S. Ding, “Optimal load distribution model of microgrid in the smart grid environment,” Renew. Sustain. Energy Rev., vol. 35, pp. 304–310, Jul. 2014.

V. V. S. N. M. Vallem and A. Kumar, “Retracted: Optimal energy dispatch in microgrids with renewable energy sources and demand response,” Int. Trans. Electr. Energy Syst., vol. 30, no. 5, pp. 1–27, May 2020.

S. A. Arefifar, Y. A.-R. I. Mohamed, and T. H. M. EL-Fouly, “Optimum microgrid de-sign for enhancing reliability and supply-security,” IEEE Trans. Smart Grid, vol. 4, no. 3, pp. 1567–1575, Sep. 2013.

J. Sachs and O. Sawodny, “A two-stage model predictive control strategy for economic diesel-PV-battery island microgrid operation in rural areas,” IEEE Trans. Sustain. Energy, vol. 7, no. 3, pp. 903–913, Jul. 2016.

M. Combe, A. Mahmoudi, M. H. Haque, and R. Khezri, “Cost-effective sizing of an AC mini-grid hybrid power system for a remote area in South Australia,” IET Gener., Transmiss. Distrib., vol. 13, no. 2, pp. 277–287, Jan. 2019.

S. Ferahtia, A. Djeroui, H. Rezk, A. Houari, S. Zeghlache, and M. Machoum, “Optimal control and implementation of energy management strategy for a DC microgrid,” Energy, vol. 238, Jan. 2021, Art. no. 121777.

A. Maulik and D. Das, “Optimal power dispatch considering load and renewable generation uncertainties in an AC–DC hybrid microgrid,” IET Gener., Transmiss. Distrib., vol. 13, no. 7, pp. 1164–1176, Apr. 2019.

A. Kumar, M. Alaraj, M. Rizwan and U. Nangia, “Novel AI Based Energy Management System for Smart Grid with RES Integration,” in IEEE Access, vol. 9, pp. 162530–162542, 2021.

A. Zakariazadeh, S. Jadid, and P. Siano, “Smart microgrid energy and reserve scheduling with demand response using stochastic optimization,” Int. J. Electr. Power Energy Syst., vol. 63, pp. 523–533, Dec. 2014.

V. Bui, A. Hussain, and H.-M. Kim, “A multiagent-based hierarchical energy management strategy for multi-microgrids considering adjustable power and demand response,” IEEE Trans. Smart Grid, vol. 9, no. 2, pp. 1323–1333, Mar. 2018.

X. Li and S. Wang, “Energy management and operational control methods for grid battery energy storage systems,” in CSEE Journal of Power and Energy Systems, vol. 7, no. 5, pp. 1026–1040, Sept. 2021.

Y. Li, P. Wang, H. B. Gooi, J. Ye and L. Wu, “Multi-Objective Optimal Dispatch of Microgrid Under Uncertainties via Interval Optimization,” in IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 2046–2058, March 2019, doi: 10.1109/TSG.2017.2787790.

Zwe-Lee Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator constraints,” in IEEE Transactions on Power Systems, vol. 18, no. 3, pp. 1187–1195, Aug. 2003.

N. Augustine, S. Suresh, P. Moghe, and K. Sheikh, “Economic dispatch for a microgrid considering renewable energy cost functions,” 2012 IEEE PES Innov. Smart Grid Technol., pp. 1–7, 2012.

M. Bhoye, S. N. Purohit, I. N. Trivedi, M. H. Pandya, P. Jangir and N. Jangir, “Energy management of Renewable Energy Sources in a microgrid using Cuckoo Search Algorithm,” 2016 IEEE Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, 2016, pp. 1–6.

Premalatha, Kandasamy & Natarajan, A. (2009). Hybrid PSO and GA for global maximization. Int J Open Prob Compt Math. 2.

J. Zhao, S. Liu, M. Zhou, X. Guo and L. Qi, “Modified cuckoo search algorithm to solve economic power dispatch optimization problems,” in IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 4, pp. 794–806, July 2018, doi: 10.1109/JAS.2018.7511138.

“Time of Use,” opuc.on.ca. http://www.https://www.opuc.on.ca/time-of-use/ (accessed: March. 15, 2022).

Zwe-Lee Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator constraints,” in IEEE Transactions on Power Systems, vol. 18, no. 3, pp. 1187–1195, Aug. 2003.

X. -S. Yang and Suash Deb, “Cuckoo Search via Lévy flights,” 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009, pp. 210–214.

M. Y. Ali, F. Khan and V. K. Sood, “Energy Management System of a Microgrid using Particle Swarm Optimization and Wireless Communication System,” 2018 IEEE Electrical Power and Energy Conference (EPEC), 2018, pp. 1–7.

Downloads

Published

2023-05-18

How to Cite

Balasubramanyam, P. ., & Sood, V. K. . (2023). A Novel Hybrid Swarm Intelligence and Cuckoo Search Based Microgrid EMS for Optimal Energy Scheduling. Distributed Generation &Amp; Alternative Energy Journal, 38(04), 1119–1148. https://doi.org/10.13052/dgaej2156-3306.3843

Issue

2023: Vol 38 Iss 4

Section

Articles