Journal of Renewable Energy and Environment

Quarterly Publication

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Publication Ethics

Indexing and Abstracting

Editorial Board

Journal Staff

Related Links

FAQ

Paper Preparation Guide

Paper Template

Journal Forms

Reviewer

Peer Review Process

Energy Management of Multi-Microgrids in Joint Energy and Ancillary Service Market Considering Uncertainties of Renewables

Document Type : Research Article

Authors

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

Abstract

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.

Keywords

Main Subjects

References
  1. Wang, J., Zhong, H., Tang, W., Rajagopal, R., Xia, Q., Kang, C. and Wang, Y., "Optimal bidding strategy for microgrids in joint energy and ancillary service markets considering flexible ramping products", Applied Energy, Vol. 205, (2017), 294-303. (https://doi.org/10.1016/j.apenergy.2017.07.047).
  2. Sardou, I.G., Khodayar, M.E., Khaledian, K., Soleimani-Damaneh, M. and Ameli, M.T., "Energy and reserve market clearing with microgrid aggregators", IEEE Transactions on Smart Grid, Vol. 7, (2015), 2703-2712. (https://doi.org/10.1109/TSG.2015.2408114).
  3. Guo, Z., Pinson, P., Chen, S., Yang, Q. and Yang, Z., "Chance-constrained peer-to-peer joint energy and reserve market considering renewable generation uncertainty", IEEE Transactions on Smart Grid, Vol. 12, (2020), 798-809. (https://doi.org/10.1109/TSG.2020.3019603).
  4. Jain, R. and Mahajan, V., "Technical and fiscal benefits of committing DG in energy market during contingency", Proceedings of IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), Chennai, India, (2018), 1-5. (https://doi.org/10.1109/PEDES.2018.8707584).
  5. Cheung, K.W., Shamsollahi, P., Sun, D., Milligan, J. and Potishnak, M., "Energy and ancillary service dispatch for the interim ISO New England electricity market", Proceedings of the 21st International Conference on Power Industry Computer Applications. Connecting Utilities. PICA 99. To the Millennium and Beyond (Cat. No. 99CH36351), Santa Clara, CA, USA, (1999), 47-53. (https://doi.org/10.1109/PICA.1999.779384).
  6. Hu, Q., Zhu, Z., Bu, S., Chan, K.W. and Li, F., "A multi-market nanogrid P2P energy and ancillary service trading paradigm: Mechanisms and implementations", Applied Energy, Vol. 293, (2021), 116938. (https://doi.org/10.1016/j.apenergy.2021.116938).
  7. Zhang, K., Troitzsch, S., Hanif, S. and Hamacher, T., "Coordinated market design for peer-to-peer energy trade and ancillary services in distribution grids", IEEE Transactions on Smart Grid, Vol. 11, No. 4, (2020), 2929-2941. (https://doi.org/10.1109/TSG.2020.2966216).
  8. Gazijahani, F.S., Ajoulabadi, A., Ravadanegh, S.N. and Salehi, J., "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, (2020), 121365. (https://doi.org/10.1016/j.jclepro.2020.121365).
  9. Tang, Z., Liu, Y., Wu, L., Liu, J. and Gao, H., "Reserve model of energy storage in day-ahead joint energy and reserve markets: A stochastic uc solution", IEEE Transactions on Smart Grid, Vol. 12, No. 1, (2020), 372-382. (https://doi.org/10.1109/TSG.2020.3009114).
  10. Roy, S., Banshwar, A., Sharma, N. K. and Sood, Y.R., "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, 5033-5043. (https://doi.org/10.3233/JIFS-169787).
  11. Lasseter, B., "Microgrids [distributed power generation]", Proceedings of IEEE Power Engineering Society Winter Meeting (Cat. No. 01CH37194), Columbus, OH, USA, (2001), 146-149. (https://doi.org/10.1109/PESW.2001.917020).
  12. Rahmani, M., Faghihi, F., Moradi CheshmehBeigi, H. and Hosseini, S.M., "Frequency control of islanded microgrids based on fuzzy cooperative and influence of STATCOM on frequency of microgrids", Journal of Renewable Energy and Environment (JREE), Vol. 5, No. 4, (2018), 27-33. (https://dx.doi.org/10.30501/jree.2018.94119).
  13. Mahajan, V. and Jain, R., "Energy management in deregulated power market with integration of microgrid", Deregulated electricity structures and smart grids, CRC Press, (2022), 47-62. (https://www.taylorfrancis.com/chapters/edit/10.1201/9781003278030-3/energy-management-deregulated-power-market-integration-microgrid-vasundhara-mahajan-ritu-jain).
  14. Teo, T.T., Logenthiran, T., Woo, W.L., Abidi, K., John, T., Wade, N.S., Greenwood, D.M., Patsios, C. and Taylor, P.C., "Optimization of fuzzy energy-management system for grid-connected microgrid using NSGA-II", IEEE Transactions on Cybernetics, Vol. 51, No. 11, (2020), 5375-5386. (https://doi.org/10.1109/TCYB.2020.3031109).
  15. Kumar, S., Saket, R., Dheer, D.K., Sanjeevikumar, P., Holm‐Nielsen, J.B. and Blaabjerg, F., "Layout optimisation algorithms and reliability assessment of wind farm for microgrid integration: A comprehensive review", IET Renewable Power Generation, Vol. 15, No. 10, (2021), 2063-2084. (https://doi.org/10.1049/rpg2.12060).
  16. Sabzehgar, R., Kazemi, M., Rasouli, M. and Fajri, P., "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, No. 2, (2020), 127-136. (https://doi.org/10.1080/15435075.2019.1700125).
  17. Chen, Y., Li, J. and He, L., "Tradeoffs in cost competitiveness and emission reduction within microgrid sustainable development considering price-based demand response", Science of The Total Environment, Vol. 703, 135545. (https://doi.org/10.1016/j.scitotenv.2019.135545).
  18. Hannan, M., Faisal, M., Ker, P.J., Begum, R., Dong, Z. and Zhang, C., "Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications", Renewable and Sustainable Energy Reviews, Vol. 131, 110022. (https://doi.org/10.1016/j.rser.2020.110022).
  19. Habibi, F., Khosravi, F., Kharrati, S. and Karimi, S., "Utilizing RDPSO algorithm for economic-environmental load dispatch modeling considering distributed energy resources", Electrica Journal, Vol. 21, No. 3, 444-457. (https:/doi.org/10.5152/electr.2021.21025).
  20. Shahidehpour, M., "Role of smart microgrid in a perfect power system", Proceedings of IEEE PES General Meeting, Minneapolis, MN, USA, (2010). (https://doi.org/10.1109/PES.2010.5590068).
  21. Makkiabadi, M., Hoseinzadeh, S., Mohammadi, M., Nowdeh, S.A., Bayati, S., Jafaraghaei, U., Mirkiai, S.M. and Assad, M.E.H., "Energy feasibility of hybrid PV/wind systems with electricity generation assessment under Iran environment", Applied Solar Energy, Vol. 56, (2021), 517-525. (https://doi.org/10.3103/S0003701X20060079).
  22. Nazari, M.A., El Haj Assad, M., Haghighat, S. and Maleki, A., "Applying TOPSIS method for wind farm site selection in Iran", Proceedings of 2020 Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates, (2020), 1-4. (https://doi.org/10.1109/ASET48392.2020.9118223).
  23. Abidoye, L.K., Bani-Hani, E., El Haj Assad, M., AlShabi, M., Soudan, B. and Oriaje, A.T., "Effects of environmental and turbine parameters on energy gains from wind farm system: Artificial neural network simulations", Wind Engineering, Vol. 44, (2020), 181-195. (https://doi.org/10.1177%2F0309524X19849834).
  24. AlShabi, M., Ghenai, C., Bettayeb, M., Ahmad, F.F. and A El Haj Assad, M., "Multi-group grey wolf optimizer (MG-GWO) for estimating photovoltaic solar cell model", Journal of Thermal Analysis and Calorimetry, Vol. 144, (2021), 1655-1670. (https://doi.org/10.1007/s10973-020-09895-2).
  25. Solanki, C.S., Solar photovoltaics: Fundamentals, technologies and applications, Phi learning pvt. Ltd., (2015). (https://www.google.com/books/edition/Solar_Photovoltaics/y1W2CAAAQBAJ?hl=en&gbpv=1&printsec=frontcover).
  26. Gheyrati, M., Akram, A. and Ghasemi-Mobtaker, H., "Optimum orientation of the multi-span greenhouse for maximum capture of solar energy in central region of Iran", Journal of Renewable Energy and Environment (JREE), Vol. 9, No. 3, (2022), 65-74. (https://dx.doi.org/10.30501/jree.2022.305780.1259).
  27. Hachicha, A.A., Al-Sawafta, I. and Said, Z., "Impact of dust on the performance of solar photovoltaic (PV) systems under United Arab Emirates weather conditions", Renewable Energy, Vol. 141, (2019), 287-297. (https://doi.org/10.1016/j.renene.2019.04.004).
  28. Malik, P., Chandel, R. and Chandel, S.S., "A power prediction model and its validation for a roof top photovoltaic power plant considering module degradation", Solar Energy, Vol. 224, (2021), 184-194. (https://doi.org/10.1016/j.solener.2021.06.015).
  29. Ghadikolaei, S.S.C., "Solar photovoltaic cells performance improvement by cooling technology: An overall review", International Journal of Hydrogen Energy, Vol. 46, (2021), 10939-10972. (https://doi.org/10.1016/j.ijhydene.2020.12.164).
  30. Pachauri, R.K., Bai, J., Kansal, I., Mahela, O.P. and Khan, B., "Shade dispersion methodologies for performance improvement of classical total cross‐tied photovoltaic array configuration under partial shading conditions", IET Renewable Power Generation, Vol. 15, (2021), 1796-1811. (https://doi.org/10.1049/rpg2.12147).
  31. Hou, C., Hu, X. and Hui, D., "Hierarchical control techniques applied in micro-grid", Proceedings of International Conference on Power System Technology, Zhejiang, China, (2010), 1-5. (https://doi.org/10.1109/POWERCON.2010.5666418).
  32. Gupta, S., Maulik, A., Das, D. and Singh, A., "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, Vol. 155, (2021), 111861. (https://doi.org/10.1016/j.rser.2021.111861).
  33. Sharma, S., Sood, Y.R., Sharma, N.K., Bajaj, M., Zawbaa, H.M., Turky, R.A. and Kamel, S., "Modeling and sensitivity analysis of grid-connected hybrid green microgrid system", Ain Shams Engineering Journal, Vol. 13, No. 4, (2022), 101679. (https://doi.org/10.1016/j.asej.2021.101679).
  34. Zeinal-Kheiri, S., Shotorbani, A.M. and Mohammadi-Ivatloo, B., "Real-time energy management of grid-connected microgrid with flexible and delay-tolerant loads", Journal of Modern Power Systems and Clean Energy, Vol. 8, (2020), 1196-1207. (https://doi.org/10.35833/MPCE.2018.000615).
  35. Arumugam, P. and Kuppan, V., "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, No. 5, (2021), 6765-6783. (https://doi.org/10.1002/er.6270).
  36. Hatziargyriou, N., Contaxis, G., Matos, M., Lopes, J.P., Kariniotakis, G., Mayer, D., Halliday, J., Dutton, G., Dokopoulos, P., Bakirtzis, A. and Stefanakis, J., "Energy management and control of island power systems with increased penetration from renewable sources", Proceedings of IEEE Power Engineering Society Winter Meeting. (Cat. No. 02CH37309), New York, NY, USA, (2002), 335-339. (https://doi.org/10.1109/PESW.2002.985008).
  37. Oyarzabal, J., Jimeno, J., Ruela, J., Engler, A. and Hardt, C., "Agent based micro grid management system", Proceedings of International Conference on Future Power Systems, Amsterdam, Netherlands, (2005), 6. (https://doi.org/10.1109/FPS.2005.204230).
  38. Zhou, B., Zou, J., Chung, C.Y., Wang, H., Liu, N., Voropai, N. and Xu, D., "Multi-Microgrid energy management systems: Architecture, communication, and scheduling strategies", Journal of Modern Power Systems and Clean Energy, Vol. 9, No. 3, (2021), 463-476. (https://doi.org/10.35833/MPCE.2019.000237).
  39. Logenthiran, T., Srinivasan, D., Khambadkone, A.M. and Aung, H.N., "Multiagent system for real-time operation of a microgrid in real-time digital simulator", IEEE Transactions on Smart Grid, Vol. 3, No. 2, (2012), 925-933. (https://doi.org/10.1109/TSG.2012.2189028).
  40. Kaur, J., Sood, Y.R. and Shrivastava, R., "A two-layer optimization approach for renewable energy management of green microgrid in deregulated power sector", Journal of Renewable and Sustainable Energy, Vol. 9, No. 6, (2017), 065905. (https://doi.org/10.1063/1.4986342).
  41. Gupta, N., "A review on the inclusion of wind generation in power system studies", Renewable and Sustainable Energy Reviews, Vol. 59, (2016), 530-543. (https://doi.org/10.1016/j.rser.2016.01.009).
  42. Li, J. and Wei, W., "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, (2014), 013139. (https://doi.org/10.1063/1.4866259).
  43. Gupta, N., "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, No. 6, (2018), 6485-6497. (https://doi.org/10.1109/TIA.2018.2855164).
  44. Alsac, O. and Stott, B., "Optimal load flow with steady-state security", IEEE Transactions on Power Apparatus and Systems, Vol. PAS-93, No. 3, (1974), 745-751. (https://doi.org/10.1109/TPAS.1974.293972).
  45. Zimmerman, R.D., Murillo-Sánchez, C.E. and Gan, D., "MATPOWER: A MATLAB power system simulation package", Manual, Power Systems Engineering Research Center, Ithaca NY, Vol. 1, (1997). (https://matpower.org/).
  46. Tsikalakis, A.G. and Hatziargyriou, N.D., "Centralized control for optimizing microgrids operation", Proceedings of IEEE Power and Energy Society General Meeting, Detroit, MI, USA, (2011), 1-8. (https://doi.org/10.1109/PES.2011.6039737).
  47. N. D. Catalog, Available: (https://data.nrel.gov/).
  48. Prajapati, V.K. and Mahajan, V., "Demand response based congestion management of power system with uncertain renewable resources", International Journal of Ambient Energy, Vol. 43, (2019), 1-14. (https://doi.org/10.1080/01430750.2019.1630307).
  49. Papathanassiou, S., Hatziargyriou, N. and Strunz, K., "A benchmark low voltage microgrid network", Proceedings of the CIGRE Symposium: Power Systems with Dispersed Generation, Vol. 1, Paris, CIGRE, (2005), 1-8 (https://www.academia.edu/download/39917771/A_Benchmark_Low_Voltage_Microgrid_Networ20151111-16466-zv17xp.pdf).
  50. P. ISO, Available: (https://www.pjm.com/markets-and-operations/energy.aspx).
Journal of Renewable Energy and Environment
Volume 10, Issue 2
May 2023
Pages 95-107
Files
History
  • Receive Date: 14 February 2022
  • Revise Date: 05 August 2022
  • Accept Date: 07 August 2022
Share
How to cite
Statistics