Management of Fluctuating Output Power of Renewable Energy Resources by Optimum Charge/Discharge Scheduling of Electric Vehicles in Smart Parking Lots

Document Type : Original Article

Authors

1 Department of Electrical Engineering, Shahreza Campus, University of Isfahan, Isfahan, Iran

2 Department of Electrical Engineering, University of Isfahan, Isfahan, Iran

Abstract

Nowadays, due to the environmental pollution and shortage of non-renewable resources, specifically the fossil fuels, distributed power generations have been considerably developed. However, the output power of renewable resources fluctuates because of their random nature, which can negatively affect the grid. This problem can be resolved by installing battery energy storage systems (BESS). On the other hand, with the increasing development of electric vehicles (EVs), the scheduling of their presence in the distribution networks has become very important; because, any unplanned presence of EVs in the intelligent parking lots (IPLs) and their simultaneous charging may affect the performance of the grid, negatively. An optimum scheduling for charge/discharge actions of EVs can resolve this problem, and reduce the need for high cost BESSs. In this paper, the problem of maximizing the operator profit is formulated as a mixed integer linear programming (MILP) problem considering the constraints on the requested charge level of the EVs and the permissible exchanged power.  Then, the problem is optimally solved, in which a scheduling scheme is proposed for charge/discharge actions of the EVs in the SPLs in order to control the power fluctuations. Simulation results on the data of a typical parking lot in Tehran demonstrate that the proposed scheduling can reduce the number of required BESSs significantly, which decreases the high expenses of the BESS purchase and installation.

Keywords

References

[1]   J. Linssen, P. Stenzel, and J. Fleer, Techno-economic analysis of photovoltaic battery systems and the influence of different consumer load profiles, Applied Energy, Vol. 185, pp. 2019-2025, 2017.
[2]   A. Tummala, R. K. Velamati, D. K. Sinha, V. Indraja, and V. H. Krishna, A review on small scale wind turbines, Renewable and Sustainable Energy Reviews, Vol. 56, pp. 1351-1371, 2016.
[3]   I.-S. Han, S.-K. Park, and C.-B. Chung, Modeling and operation optimization of a proton exchange membrane fuel cell system for maximum efficiency, Energy Conversion and Management, Vol. 113, pp. 52-65, 2016.
[4]   S. Zhang and R. Xiong, Adaptive energy management of a plug-in hybrid electric vehicle based on driving pattern recognition and dynamic programming, Applied Energy, Vol. 155, pp. 68-78, 2015.
[5]   L. Jian, Y. Zheng, X. Xiao, and C. Chan, Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid, Applied Energy, Vol. 146, pp. 150-161, 2015.
[6]   A. S. Masoum, S. Deilami, P. Moses, M. Masoum, and A. Abu-Siada, Smart load management of plug-in electric vehicles in distribution and residential networks with charging stations for peak shaving and loss minimisation considering voltage regulation, IET generation, transmission & distribution, Vol. 5, No. 8, pp. 877-888, 2011.
[7]   R. J. Bessa and M. A. Matos, Economic and technical management of an aggregation agent for electric vehicles: a literature survey, European transactions on electrical power, Vol. 22, No. 3, pp. 334-350, 2012.
[8]   E. Heydarian-Forushani, M. E. Golshan, and M. Shafie-khah, Flexible interaction of plug-in electric vehicle parking lots for efficient wind integration, Applied energy, Vol. 179, pp. 338-349, 2016.
[9]   W. Kempton and J. Tomić, Vehicle-to-grid power implementation: From stabilizing the grid to supporting large-scale renewable energy, Journal of power sources, Vol. 144, No. 1, pp. 280-294, 2005.
[10] G. K. Venayagamoorthy, Dynamic, stochastic, computational, and scalable technologies for smart grids, IEEE Computational Intelligence Magazine, Vol. 6, No. 3, pp. 22-35, 2011.
[11] J. Gallardo-Lozano, E. Romero-Cadaval, V. Miñambres-Marcos, D. Vinnikov, T. Jalakas, and H. Hõimoja, Grid reactive power compensation by using electric vehicles, in 2014 Electric Power Quality and Supply Reliability Conference (PQ), 2014: IEEE, pp. 19-24.
[12] N. Masuch, J. Keiser, M. Lützenberger, and S. Albayrak, Wind power-aware vehicle-to-grid algorithms for sustainable EV energy management systems, in 2012 IEEE International Electric Vehicle Conference, 2012: IEEE, pp. 1-7.
[13] W. Hu, C. Su, Z. Chen, and B. Bak-Jensen, Optimal operation of plug-in electric vehicles in power systems with high wind power penetrations, IEEE Transactions on Sustainable Energy, Vol. 4, No. 3, pp. 577-585, 2013.
[14] D. B. Richardson, Electric vehicles and the electric grid: A review of modeling approaches, Impacts, and renewable energy integration, Renewable and Sustainable Energy Reviews, Vol. 19, pp. 247-254, 2013.
[15] F. Mwasilu, J. J. Justo, E.-K. Kim, T. D. Do, and J.-W. Jung, Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration, Renewable and sustainable energy reviews, Vol. 34, pp. 501-516, 2014.
[16] R. Sioshansi and P. Denholm, The value of plug-in hybrid electric vehicles as grid resources, The Energy Journal, pp. 1-23, 2010.
[17] S. Jang, S. Han, S. H. Han, and K. Sezaki, Optimal decision on contract size for V2G aggregator regarding frequency regulation, in 2010 12th International Conference on Optimization of Electrical and Electronic Equipment, 2010: IEEE, pp. 54-62.
[18] N. Rotering and M. Ilic, Optimal charge control of plug-in hybrid electric vehicles in deregulated electricity markets, IEEE Transactions on Power Systems, Vol. 26, No. 3, pp. 1021-1029, 2010.
[19] W. Tushar, W. Saad, H. V. Poor, and D. B. Smith, Economics of electric vehicle charging: A game theoretic approach, IEEE Transactions on Smart Grid, Vol. 3, No. 4, pp. 1767-1778, 2012.
[20] L. Gan, U. Topcu, and S. H. Low, Optimal decentralized protocol for electric vehicle charging, IEEE Transactions on Power Systems, Vol. 28, No. 2, pp. 940-951, 2012.
[21] A. S. Masoum, S. Deilami, M. A. Masoum, A. Abu-Siada, and S. Islam, Online coordination of plug-in electric vehicle charging in smart grid with distributed wind power generation systems, in 2014 IEEE PES General Meeting| Conference & Exposition, 2014: IEEE, pp. 1-5.
[22] A. Y. Saber and G. K. Venayagamoorthy, Resource scheduling under uncertainty in a smart grid with renewables and plug-in vehicles, IEEE systems journal, Vol. 6, No. 1, pp. 103-109, 2011.
[23] G. Li and X.-P. Zhang, Modeling of plug-in hybrid electric vehicle charging demand in probabilistic power flow calculations, IEEE Transactions on Smart Grid, Vol. 3, No. 1, pp. 492-499, 2012.
[24] S. M. Ross, Introduction to Probability Models (10/E), ed: Academic Press, 2009.
[25] S. Bae and A. Kwasinski, Spatial and temporal model of electric vehicle charging demand, IEEE Transactions on Smart Grid, Vol. 3, No. 1, pp. 394-403, 2011.
[26] J. Soares, H. Morais, T. Sousa, Z. Vale, and P. Faria, Day-ahead resource scheduling including demand response for electric vehicles, IEEE Transactions on Smart Grid, Vol. 4, No. 1, pp. 596-605, 2013.
[27] S. Deilami, A. S. Masoum, P. S. Moses, and M. A. Masoum, Real-time coordination of plug-in electric vehicle charging in smart grids to minimize power losses and improve voltage profile, IEEE Transactions on Smart Grid, Vol. 2, No. 3, pp. 456-467, 2011.
[28] J. Zhao, F. Wen, Z. Y. Dong, Y. Xue, and K. P. Wong, Optimal dispatch of electric vehicles and wind power using enhanced particle swarm optimization, IEEE Transactions on industrial informatics, Vol. 8, No. 4, pp. 889-899, 2012.
[29] A. Sheikhi, S. Bahrami, A. Ranjbar, and H. Oraee, Strategic charging method for plugged in hybrid electric vehicles in smart grids; a game theoretic approach, International Journal of Electrical Power & Energy Systems, Vol. 53, pp. 499-506, 2013.
[30] H. Lund and W. Kempton, Integration of renewable energy into the transport and electricity sectors through V2G, Energy policy, Vol. 36, No. 9, pp. 3578-3587, 2008.
[31] T. Wu, Q. Yang, Z. Bao, and W. Yan, Coordinated energy dispatching in microgrid with wind power generation and plug-in electric vehicles, IEEE Transactions on Smart Grid, Vol. 4, No. 3, pp. 1453-1463, 2013.
[32] M. Raoofat, M. Saad, S. Lefebvre, D. Asber, H. Mehrjedri, and L. Lenoir, Wind power smoothing using demand response of electric vehicles, International Journal of Electrical Power & Energy Systems, Vol. 99, pp. 164-174, 2018.
[33] J. Jannati and D. Nazarpour, Multi-objective scheduling of electric vehicles intelligent parking lot in the presence of hydrogen storage system under peak load management, Energy, Vol. 163, pp. 338-350, 2018.
[34] S. H. Shamsdin, A. Seifi, M. Rostami-Shahrbabaki, and B. Rahrovi, Plug-in Electric Vehicle Optimization and Management Charging in a Smart Parking Lot, in 2019 IEEE Texas Power and Energy Conference (TPEC), 2019: IEEE, pp. 1-7.
[35] J. Jannati and D. Nazarpour, Optimal performance of electric vehicles parking lot considering environmental issue, Journal of cleaner production, Vol. 206, pp. 1073-1088, 2019.
[36] A. Arzani and G. K. Venayagamoorthy, Integration of SmartParks in a Power System with Utility-Scale PV Plant, in 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 2018: IEEE, pp. 1-9.
[37] M. Latifi, A. Khalili, A. Rastegarnia, and S. Sanei, A Bayesian Real-Time Electric Vehicle Charging Strategy for Mitigating Renewable Energy Fluctuations, IEEE Transactions on Industrial Informatics, Vol. 15, No. 5, pp. 2555-2568, 2018.
[38] M. Maigha and M. Crow, A Transactive Operating Model for Smart Airport Parking Lots, IEEE Power and Energy Technology Systems Journal, Vol. 5, No. 4, pp. 157-166, 2018.
[39] Y. Sun, X. Tang, X. Sun, D. Jia, and G. Zhang, Microgrid tie-line power fluctuation mitigation with virtual energy storage, The Journal of Engineering, Vol. 2019, No. 16, pp. 1001-1004, 2019.
[40] Z. Zhaoyun et al., Application of micro-grid control system in smart park, The Journal of Engineering, Vol. 2019, No. 16, pp. 3116-3119, 2019.

Files

History

  • Receive Date: 19 July 2021
  • Revise Date: 05 April 2022
  • Accept Date: 14 October 2022

Share

How to cite

Statistics