Document Type : Research Article


Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, P. O. Box: 395007, Surat, India.



In this study, energy management of grid-connected Multi-Microgrid (MMG) is performed through joint optimization of the energy and ancillary service market. The test system comprises the IEEE 30 bus system as the main grid and the 16-bus system as an MMG. The MMG is comprised of dispatchable and non-dispatchable generation and loads. The non-dispatchable generators are based on renewable energy sources (RES) such as solar and wind.  The uncertainty modeling for wind and solar is performed by Weibull and beta probability distribution function. The strategic integration of RES helps MMG deliver both energy and ancillary services to the utility grid. This research aims to reduce the total energy cost while reducing reserve cost by maximizing the use of RES under normal operation and during contingency conditions. It is observed that if MMG is incorporated into the system, then the total generation cost, reserve cost, and power losses are reduced to 0.11%, 0.325%, and 1.201%, respectively, in normal operating conditions. Under contingency, when Generator 5 is out of service and the main grid is operating alone, the total generation cost increased significantly from 22118.92 $ day-1 to 22435.68 $ day-1 and the real power loss increased from 233.35 MW day-1 to 245.11 MW day-1. However, by interconnecting MMG with the main grid, generation cost and power loss get reduced to 22375.60 $ day-1 and 243.35 MW day-1, respectively. It is analyzed that participation of MMG provides techno-economic benefits during normal operation and contingency conditions.


Main Subjects

[1]           J. Wang, H. Zhong, W. Tang, R. Rajagopal, Q. Xia, C. Kang, et al., "Optimal bidding strategy for microgrids in joint energy and ancillary service markets considering flexible ramping products," Applied Energy, vol. 205, pp. 294-303, 2017.
[2]           I. G. Sardou, M. E. Khodayar, K. Khaledian, M. Soleimani-Damaneh, and M. T. Ameli, "Energy and reserve market clearing with microgrid aggregators," IEEE Transactions on Smart Grid, vol. 7, pp. 2703-2712, 2015.
[3]           Z. Guo, P. Pinson, S. Chen, Q. Yang, and Z. Yang, "Chance-constrained peer-to-peer joint energy and reserve market considering renewable generation uncertainty," IEEE Transactions on Smart Grid, vol. 12, pp. 798-809, 2020.
[4]           R. Jain and V. Mahajan, "Technical and Fiscal benefits of committing DG in Energy Market during contingency," in 2018 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), 2018, pp. 1-5.
[5]           K. W. Cheung, P. Shamsollahi, D. Sun, J. Milligan, and M. Potishnak, "Energy and ancillary service dispatch for the interim ISO New England electricity market," in Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No. 99CH36351), 1999, pp. 47-53.
[6]           Q. Hu, Z. Zhu, S. Bu, K. W. Chan, and F. Li, "A multi-market nanogrid P2P energy and ancillary service trading paradigm: Mechanisms and implementations," Applied Energy, vol. 293, p. 116938, 2021.
[7]           K. Zhang, S. Troitzsch, S. Hanif, and T. Hamacher, "Coordinated market design for peer-to-peer energy trade and ancillary services in distribution grids," IEEE Transactions on Smart Grid, vol. 11, pp. 2929-2941, 2020.
[8]           F. S. Gazijahani, A. Ajoulabadi, S. N. Ravadanegh, and J. Salehi, "Joint energy and reserve scheduling of renewable powered microgrids accommodating price responsive demand by scenario: A risk-based augmented epsilon-constraint approach," Journal of Cleaner Production, vol. 262, p. 121365, 2020.
[9]           Z. Tang, Y. Liu, L. Wu, J. Liu, and H. Gao, "Reserve Model of Energy Storage in Day-Ahead Joint Energy and Reserve Markets: A Stochastic UC Solution," IEEE Transactions on Smart Grid, vol. 12, pp. 372-382, 2020.
[10]         S. Roy, A. Banshwar, N. K. Sharma, and Y. R. Sood, "Simultaneous optimization of renewable energy based pumped storage scheme in energy and ancillary services market under deregulated power sector," Journal of Intelligent & Fuzzy Systems, vol. 35, pp. 5033-5043, 2018.10.3233/JIFS-169787
[11]         B. Lasseter, "Microgrids [distributed power generation]," in 2001 IEEE power engineering society winter meeting. Conference proceedings (Cat. No. 01CH37194), 2001, pp. 146-149.
[12]         M. Rahmani, F. Faghihi, H. Moradi CheshmehBeigi, and S. M. Hosseini, "Frequency control of islanded microgrids based on fuzzy cooperative and influence of STATCOM on frequency of microgrids," Journal of Renewable Energy and Environment, vol. 5, pp. 27-33, 2018.
[13]         V. Mahajan and R. Jain, "Energy Management in Deregulated Power Market with Integration of Microgrid," in Deregulated Electricity Structures and Smart Grids, ed: CRC Press, pp. 47-62.
[14]         T. T. Teo, T. Logenthiran, W. L. Woo, K. Abidi, T. John, N. S. Wade, et al., "Optimization of fuzzy energy-management system for grid-connected microgrid using NSGA-II," IEEE transactions on cybernetics, vol. 51, pp. 5375-5386, 2020.
[15]         S. Kumar, R. Saket, D. K. Dheer, P. Sanjeevikumar, J. B. Holm‐Nielsen, and F. Blaabjerg, "Layout optimisation algorithms and reliability assessment of wind farm for microgrid integration: A comprehensive review," IET Renewable Power Generation, 2021.
[16]         R. Sabzehgar, M. Kazemi, M. Rasouli, and P. Fajri, "Cost optimization and reliability assessment of a microgrid with large-scale plug-in electric vehicles participating in demand response programs," International Journal of Green Energy, vol. 17, pp. 127-136, 2020.
[17]         Y. Chen, J. Li, and L. He, "Tradeoffs in cost competitiveness and emission reduction within microgrid sustainable development considering price-based demand response," Science of The Total Environment, vol. 703, p. 135545, 2020.
[18]         M. Hannan, M. Faisal, P. J. Ker, R. Begum, Z. Dong, and C. Zhang, "Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications," Renewable and Sustainable Energy Reviews, vol. 131, p. 110022, 2020.
[19]         F. Habibi, F. Khosravi, S. Kharrati, and S. Karimi, "Utilizing RDPSO Algorithm for Economic-Environmental Load Dispatch Modeling Considering Distributed Energy Resources," Electrica Journal, vol. 12, p. 15,
[20]         M. Shahidehpour, "Role of smart microgrid in a perfect power system," in IEEE PES General Meeting, 2010, pp. 1-1.
[21]         M. Makkiabadi, S. Hoseinzadeh, M. Mohammadi, S. A. Nowdeh, S. Bayati, U. Jafaraghaei, et al., "Energy feasibility of hybrid PV/wind systems with electricity generation assessment under Iran environment," Applied Solar Energy, vol. 56, pp. 517-525, 2020.
[22]         M. A. Nazari, M. E. H. Assad, S. Haghighat, and A. Maleki, "Applying TOPSIS method for wind farm site selection in Iran," in 2020 Advances in Science and Engineering Technology International Conferences (ASET), 2020, pp. 1-4.
[23]         L. K. Abidoye, E. Bani-Hani, M. El Haj Assad, M. AlShabi, B. Soudan, and A. T. Oriaje, "Effects of environmental and turbine parameters on energy gains from wind farm system: Artificial neural network simulations," Wind Engineering, vol. 44, pp. 181-195, 2020.
[24]         M. AlShabi, C. Ghenai, M. Bettayeb, F. F. Ahmad, and M. El Haj Assad, "Multi-group grey wolf optimizer (MG-GWO) for estimating photovoltaic solar cell model," Journal of Thermal Analysis and Calorimetry, vol. 144, pp. 1655-1670, 2021.
[25]         C. S. Solanki, Solar photovoltaics: fundamentals, technologies and applications: Phi learning pvt. Ltd., 2015.
[26]         M. Gheyrati, A. Akram, and H. Ghasemi-Mobtaker, "Optimum Orientation of the Multi-Span Greenhouse for Maximum Capture of Solar Energy in Central Region of Iran," Journal of Renewable Energy and Environment, 2022.
[27]         A. A. Hachicha, I. Al-Sawafta, and Z. Said, "Impact of dust on the performance of solar photovoltaic (PV) systems under United Arab Emirates weather conditions," Renewable Energy, vol. 141, pp. 287-297, 2019.
[28]         P. Malik, R. Chandel, and S. S. Chandel, "A power prediction model and its validation for a roof top photovoltaic power plant considering module degradation," Solar Energy, vol. 224, pp. 184-194, 2021.
[29]         S. S. C. Ghadikolaei, "Solar photovoltaic cells performance improvement by cooling technology: An overall review," International Journal of Hydrogen Energy, vol. 46, pp. 10939-10972, 2021.
[30]         R. K. Pachauri, J. Bai, I. Kansal, O. P. Mahela, and B. Khan, "Shade dispersion methodologies for performance improvement of classical total cross‐tied photovoltaic array configuration under partial shading conditions," IET Renewable Power Generation, vol. 15, pp. 1796-1811, 2021.
[31]         C. Hou, X. Hu, and D. Hui, "Hierarchical control techniques applied in micro-grid," in 2010 International Conference on Power System Technology, 2010, pp. 1-5.
[32]         S. Gupta, A. Maulik, D. Das, and A. Singh, "Coordinated stochastic optimal energy management of grid-connected microgrids considering demand response, plug-in hybrid electric vehicles, and smart transformers," Renewable and Sustainable Energy Reviews, p. 111861, 2021.
[33]         S. Sharma, Y. R. Sood, N. K. Sharma, M. Bajaj, H. M. Zawbaa, R. A. Turky, et al., "Modeling and sensitivity analysis of grid-connected hybrid green microgrid system," Ain Shams Engineering Journal, vol. 13, p. 101679, 2022.
[34]         S. Zeinal-Kheiri, A. M. Shotorbani, and B. Mohammadi-Ivatloo, "Real-time energy management of grid-connected microgrid with flexible and delay-tolerant loads," Journal of Modern Power Systems and Clean Energy, vol. 8, pp. 1196-1207, 2020.
[35]         P. Arumugam and V. Kuppan, "A GBDT‐SOA approach for the system modelling of optimal energy management in grid‐connected micro‐grid system," International Journal of Energy Research, vol. 45, pp. 6765-6783, 2021.
[36]         N. Hatziargyriou, G. Contaxis, M. Matos, J. P. Lopes, G. Kariniotakis, D. Mayer, et al., "Energy management and control of island power systems with increased penetration from renewable sources," in 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No. 02CH37309), 2002, pp. 335-339.
[37]         J. Oyarzabal, J. Jimeno, J. Ruela, A. Engler, and C. Hardt, "Agent based micro grid management system," in 2005 International Conference on Future Power Systems, 2005, pp. 6 pp.-6.
[38]         B. Zhou, J. Zou, C. Y. Chung, H. Wang, N. Liu, N. Voropai, et al., "Multi-Microgrid Energy Management Systems: Architecture, Communication, and Scheduling Strategies," Journal of Modern Power Systems and Clean Energy, 2021.
[39]         T. Logenthiran, D. Srinivasan, A. M. Khambadkone, and H. N. Aung, "Multiagent system for real-time operation of a microgrid in real-time digital simulator," IEEE Transactions on smart grid, vol. 3, pp. 925-933, 2012.
[40]         J. Kaur, Y. R. Sood, and R. Shrivastava, "A two-layer optimization approach for renewable energy management of green microgrid in deregulated power sector," Journal of Renewable and Sustainable Energy, vol. 9, p. 065905, 2017.
[41]         N. Gupta, "A review on the inclusion of wind generation in power system studies," Renewable and sustainable energy reviews, vol. 59, pp. 530-543, 2016.
[42]         J. Li and W. Wei, "Probabilistic evaluation of available power of a renewable generation system consisting of wind turbines and storage batteries: A Markov chain method," Journal of Renewable and Sustainable Energy, vol. 6, p. 013139, 2014.
[43]         N. Gupta, "Gauss-Quadrature-Based Probabilistic Load Flow Method With Voltage-Dependent Loads Including WTGS, PV, and EV Charging Uncertainties," IEEE Transactions on Industry Applications, vol. 54, pp. 6485-6497, 2018.
[44]         O. Alsac and B. Stott, "Optimal load flow with steady-state security," IEEE transactions on power apparatus and systems, pp. 745-751, 1974.
[45]         R. D. Zimmerman, C. E. Murillo-Sánchez, and D. Gan, "MATPOWER: A MATLAB power system simulation package," Manual, Power Systems Engineering Research Center, Ithaca NY, vol. 1, 1997
[46]         A. G. Tsikalakis and N. D. Hatziargyriou, "Centralized control for optimizing microgrids operation," in 2011 IEEE power and energy society general meeting, 2011, pp. 1-8.
[47]         N. D. Catalog. Available:
[48]         V. K. Prajapati and V. Mahajan, "Demand response based congestion management of power system with uncertain renewable resources," International Journal of Ambient Energy, pp. 1-14, 2019.