Market-based Real Time Congestion Management in a Smart Grid Considering Reconfiguration and Switching Cost

Document Type : Original Article

Authors

Department of Electrical and Electronic Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran

Abstract

Network Real-Time Congestion (RTC) is a bottleneck that limits energy transfer from the generation units or up-grid to the loads. Some factors, such as intermittent generation of renewable resources and forced outages of generating units and load forecasting errors, can lead to Real-Time Congestion Management (RTCM) in a smart grid network. RTCM is a set of methods to eliminate congestion in real-time. To implement RTCM, some approaches can be employed, including network reconfiguration by Remote Control Switches (RCS), load shedding generation and up-grid power rescheduling. In this paper, a two-stage programming model is proposed to find the optimal solution for RTCM using the integration of reconfiguration and market-based approaches. Therefore, following the occurrence of congestion, at the first stage, microgrid central controller (MGCC) or central energy manager implements reconfiguration as the lowest-cost approach to mitigating RTC. The Soccer League (SL) algorithm is employed at the first stage to find the optimal network topology. Subsequently, based on the results obtained from the first stage, a programming model is applied at the second stage to completely eliminate the RTC. The proposed model minimizes a weighted objective function that includes the generation and up-grid rescheduling cost, load shedding cost, switching cost, and congestion clearing time. In order to model switching costs, a new index is defined to prevent risky switching and the depreciation caused by frequent switching. This index is determined based on the critical locations in the network and the age of RCSs. The numerical results demonstrate the efficacy of the proposed model.

Keywords

References

  1. Barbulescu, C., Kilyeni, S., Cristian, D.P. and Jigoria-Oprea, D., "Congestion management using open power market environment electricity trading", in 45th international universities power engineering conference UPEC2010, IEEE., (2010), 1-6.
  2. Babagheibi, M., Jadid, S. and Kazemi, A., "Distribution locational marginal pricing for congestion management of an active distribution system with renewable-based microgrids under a privacy-preserving market clearing approach and load models", Sustainable Energy, Grids and Networks, Vol. 32, (2022), 100935. https://doi.org/10.1016/j.segan.2022.100935
  3. Biegel, B., Andersen, P., Stoustrup, J. and Bendtsen, J., "Congestion management in a smart grid via shadow prices", IFAC Proceedings Volumes, Vol. 45, No. 21, (2012), 518-523. https://doi.org/10.3182/20120902-4-FR-2032.00091
  4. Fattaheian-Dehkordi, S., Rajaei, A., Abbaspour, A., Fotuhi-Firuzabad, M. and Lehtonen, M., "Distributed transactive framework for congestion management of multiple-microgrid distribution systems", IEEE Transactions on Smart Grid, Vol. 13, No. 2, (2021), 1335-1346. https://doi.org/10.3182/201209024-FR-2032.00091
  5. Li, R., Wu, Q. and Oren, S.S., "Distribution locational marginal pricing for optimal electric vehicle charging management", IEEE Transactions on Power Systems, Vol. 29, No. 1, (2013), 203-211. https://doi.org/10.1109/TPWRS.2013.2278952
  6. O’Connell, N., Wu, Q., Østergaard, J., Nielsen, A.H., Cha, S.T. and Ding, Y., "Day-ahead tariffs for the alleviation of distribution grid congestion from electric vehicles", Electric Power Systems Research, Vol. 92, (2012), 106-114. https://doi.org/10.1016/j.epsr.2012.05.018
  7. Verzijlbergh, R.A., De Vries, L.J. and Lukszo, Z., "Renewable energy sources and responsive demand. Do we need congestion management in the distribution grid?", IEEE Transactions on Power Systems, Vol. 29, No. 5, (2014), 2119-2128. https://doi.org/10.1109/TPWRS.2014.2300941
  8. Huang, S. and Wu, Q., "Dynamic subsidy method for congestion management in distribution networks", IEEE Transactions on Smart Grid, Vol. 9, No. 3, (2016), 2140-2151. https://doi.org/10.1109/TSG.2016.2607720
  9. Andersen, P.B., Hu, J. and Heussen, K., "Coordination strategies for distribution grid congestion management in a multi-actor, multi-objective setting", in 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), IEEE. (2012), 1-8.
  10. Hu, J., You, S., Lind, M. and Østergaard, J., "Coordinated charging of electric vehicles for congestion prevention in the distribution grid", IEEE Transactions on Smart Grid, Vol. 5, No. 2, (2013), 703-711. https://doi.org/10.1109/TSG.2013.2279007
  11. Zhang, C., Ding, Y., Nordentoft, N.C., Pinson, P. and Østergaard, J., "Flech: A danish market solution for dso congestion management through der flexibility services", Journal of Modern Power Systems and Clean Energy, Vol. 2, No. 2, (2014), 126-133. https://doi.org/10.1007/s40565-014-0048-0
  12. Aljohani, T.M., Ebrahim, A.F. and Mohammed, O.A., "Dynamic real-time pricing mechanism for electric vehicles charging considering optimal microgrids energy management system", IEEE Transactions on Industry Applications, Vol. 57, No. 5, (2021), 5372-5381. https://doi.org/10.1109/TIA.2021.3099083
  13. Vergara-Fernandez, L., Aguayo, M.M., Moran, L. and Obreque, C., "A milp-based operational decision-making methodology for demand-side management applied to desalinated water supply systems supported by a solar photovoltaic plant: A case study in agricultural industry", Journal of Cleaner Production, Vol. 334, (2022), 130123. https://doi.org/10.1016/j.jclepro.2021.130123
  14. Huang, S. and Wu, Q., "Real-time congestion management in distribution networks by flexible demand swap", IEEE Transactions on Smart Grid, Vol. 9, No. 5, (2017), 4346-4355. https://doi.org/10.1109/TSG.2017.2655085
  15. Daroj, K. and Limpananwadi, W., "Reactive power dispatch scheme evaluation for synchronous based distributed generators to reduce real power loss in distribution systems", in 2008 IEEE International Conference on Sustainable Energy Technologies, IEEE., (2008), 1178-1183.
  16. Viawan, F.A. and Karlsson, D., "Voltage and reactive power control in systems with synchronous machine-based distributed generation", IEEE Transactions on Power Delivery, Vol. 23, No. 2, (2008), 1079-1087. https://doi.org/10.1109/TPWRD.2007.915870
  17. Ramesh, G. and Ranjith Babu, V., "Combined facts and microgrid-based congestion management in transmission lines", in Advances in Electrical and Computer Technologies: Select Proceedings of ICAECT 2020, Springer., (2021), 1063-1073.
  18. Thakar, S., Vijay, A. and Doolla, S., "System reconfiguration in microgrids", Sustainable Energy, Grids and Networks, Vol. 17, (2019), 100191. https://doi.org/10.1016/j.segan.2019.100191
  19. Huang, S., Wu, Q., Liu, Z. and Nielsen, A.H., "Review of congestion management methods for distribution networks with high penetration of distributed energy resources", IEEE PES Innovative Smart Grid Technologies, Europe, (2014), 1-6. https://doi.org/10.1109/ISGTEurope.2014.7028811
  20. Keshavarz, M., Doroudi, A., Kazemi, M. and Mahdian Dehkordi, N., "A new consensus-based distributed adaptive control for islanded microgrids", International Journal of Engineering, Transactions A: Basics, Vol. 34, No. 7, (2021), 1725-1735.oi. https://doi.org/10.5829/ije.2021.34.07a.17
  21. Merlin, A. and Back, H., "Search for a minimal-loss operating spanning tree configuration in an urban power distribution system", in Proc. 5th Power System Computation Conf., Cambridge, UK., (1975), 1-18.
  22. Mendoza, J., López, R., Morales, D., López, E., Dessante, P. and Moraga, R., "Minimal loss reconfiguration using genetic algorithms with restricted population and addressed operators: Real application", IEEE Transactions on Power Systems, Vol. 21, No. 2, (2006), 948-954. https://doi.10.1109/TPWRS.2006.873124
  23. Shirmohammadi, D. and Hong, H.W., "Reconfiguration of electric distribution networks for resistive line losses reduction", IEEE Transactions on Power Delivery, Vol. 4, No. 2, (1989), 1492-1498. https://doi.10.1109/61.25637
  24. Glamocanin, V., "Optimal loss reduction of distributed networks", IEEE Transactions on Power Systems, Vol. 5, No. 3, (1990), 774-782. https://doi.10.1109/59.65905
  25. Toune, S., Fudo, H., Genji, T., Fukuyama, Y. and Nakanishi, Y., "Comparative study of modern heuristic algorithms to service restoration in distribution systems", IEEE Transactions on Power Delivery, Vol. 17, No. 1, (2002), 173-181. https://doi.10.1109/61.974205
  1. Nara, K., Shiose, A., Kitagawa, M. and Ishihara, T., "Implementation of genetic algorithm for distribution systems loss minimum re-configuration", IEEE Transactions on Power Systems, Vol. 7, No. 3, (1992), 1044-1051. https://doi.10.1109/59.207317
  2. Savier, J. and Das, D., "A multi-objective method for network reconfiguration", International Journal of Engineering, Transactions A: Basics, , Vol. 22, No. 4, (2009).
  3. Shariatkhah, M.H. and Haghifam, M.R., "Using feeder reconfiguration for congestion management of smart distribution network with high dg penetration", (2012). https://doi.10.1049/cp.2012.0863
  4. Franco, J.F., Rider, M.J., Lavorato, M. and Romero, R., "A mixed-integer lp model for the reconfiguration of radial electric distribution systems considering distributed generation", Electric Power Systems Research, Vol. 97, (2013), 51-60. https://doi.org/10.1016/j.epsr.2012.12.005
  5. Abur, A., "A modified linear programming method for distribution system reconfiguration", International Journal of Electrical Power & Energy Systems, Vol. 18, No. 7, (1996), 469-474. https://doi.org/10.1016/0142-0615(96)00005-1
  6. Baran, M.E. and Wu, F.F., "Network reconfiguration in distribution systems for loss reduction and load balancing", IEEE Transactions on Power Delivery, Vol. 4, No. 2, (1989), 1401-1407. https://doi.10.1109/61.25627
  7. Enacheanu, B., Raison, B., Caire, R., Devaux, O., Bienia, W. and HadjSaid, N., "Radial network reconfiguration using genetic algorithm based on the matroid theory", IEEE Transactions on Power Systems, Vol. 23, No. 1, (2008), 186-195. https://doi.10.1109/PES.2008.4596321
  8. Shariatkhah, M., Haghifam, M.-R. and Arefi, A., "Load profile based determination of distribution feeder configuration by dynamic programming", in 2011 IEEE Trondheim PowerTech, IEEE., (2011), 1-6.
  9. Esfahani, M.M. and Yousefi, G.R., "Real time congestion management in power systems considering quasi-dynamic thermal rating and congestion clearing time", IEEE Transactions on Industrial Informatics, Vol. 12, No. 2, (2016), 745-754. https://doi.10.1109/TII.2016.2530402
  10. 738, I.S., "Ieee standard for calculating the current temperature relationship of bare overhead conductors", (2006). https://doi.10.1109/IEEESTD.2013.6692858
  11. Esmaeili, S., Anvari-Moghaddam, A., Jadid, S. and Guerrero, J.M., "A stochastic model predictive control approach for joint operational scheduling and hourly reconfiguration of distribution systems", Energies, Vol. 11, No. 7, (2018), 1884. https://doi.org/10.3390/en11071884
  12. Kavousi-Fard, A. and Khodaei, A., "Efficient integration of plug-in electric vehicles via reconfigurable microgrids", Energy, Vol. 111, (2016), 653-663. https://doi.org/10.1016/j.energy.2016.06.018
  13. Moosavian, N. and Roodsari, B.K., "Soccer league competition algorithm, a new method for solving systems of nonlinear equations", International Journal of Intelligence Science, Vol. 4, No. 01, (2013), 7. https://doi.10.4236/ijis.2014.41002
  14. Dutta, S. and Singh, S., "Optimal rescheduling of generators for congestion management based on particle swarm optimization", IEEE Transactions on Power Systems, Vol. 23, No. 4, (2008), 1560-1569. https://doi.10.1109/TPWRS.2008.922647
International Journal of Engineering
Volume 36, Issue 5
TRANSACTIONS B: Applications
May 2023
Pages 842-857

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