Impact of Electric Vehicles and Demand Response Program on Optimal Operation of Distribution System in the Framework of a New Bi-level Model

Document Type : Power Article

Authors

1 Faculty of Electrical and Computer Engineering, University of Kurdistan, Sanandaj

2 University of Beira Interior, R. Fonte do Lameiro, Covilha, Portugal

Abstract

Abstract: In this paper, the impact of electric vehicles (EVs) and a price-based and an incentive-based demand response programs and the combination of both programs, has been investigated on the optimal operation of the distribution system, which owns a wind unit, in the framework of a new bi-level model. In this model, simultaneously, uncertainty of wind unit and electric vehicles are also considered. The aim of both levels is to maximization the profits. In the upper-level, the distribution system, due to the existence of a wind unit and the vehicle to grid capability of EVs, gains more profit by not purchasing the electrical energy from the upstream network. At the lower-level, owner of the EVs parking lots is obtained more benefit, due to the selling of energy to EVs owners and distribution system. Forasmuch as this model is converted to single-level mix-integer linear problem by using of Karush–Kuhn–Tucker (KKT) conditions and auxiliary binary variables and is solved by GAMS software. The presented model is tested on the IEEE 15-bus distribution system over a 24-h period and results prove the effectiveness of the model.

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Main Subjects


مراجع
[1] de Hoog, J., Alpcan, T., Brazil, M., Thomas, D. A., & Mareels, I. (2016). A market mechanism for Electric Vehicle charging under network constraints. IEEE Transactions on Smart Grid, 7(2), 827-836.
[2] Zhang, T., Chen, W., Han, Z., & Cao, Z. (2014). Charging scheduling of electric vehicles with local renewable energy under uncertain electric vehicle arrival and grid power price. IEEE Transactions on Vehicular Technology, vol. 63, no. 6, pp. 2600-2612.
[3] Godina, R., Rodrigues, E. M., Paterakis, N. G., Erdinc, O., & Catalao, J. P. (2016). Innovative impact assessment of electric vehicles charging loads on distribution transformers using real data. Energy Conversion and Management, 120, 206-216.
[4] Karakitsios, I., Karfopoulos, E., & Hatziargyriou, N. (2016). Impact of dynamic and static fast inductive charging of electric vehicles on the distribution network. Electric Power Systems Research, 140, 107-115.
[5] Hernández, J. C., Ruiz-Rodriguez, F. J., & Jurado, F. (2017). Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems. Energy.
[6] Park, W. J., Song, K. B., & Park, J. W. (2013). Impact of electric vehicle penetration-based charging demand on load profile. Journal of Electrical
Engineering and Technology, vol. 8, no. 2,
pp. 224-251.
[7] Mirzaei, M. J., Kazemi, A., & Homaee, O. (2016). A probabilistic approach to determine optimal capacity and location of electric vehicles parking lots in distribution networks. IEEE Transactions on Industrial Informatics, vol. 12, no. 5, pp. 1963-1972.
[8] Neyestani, N., Damavandi, M. Y., Shafie-Khah, M., Contreras, J., & Catalão, J. P. (2015). Allocation of plug-in vehicles' parking lots in distribution systems considering network-constrained objectives. IEEE Transactions on Power Systems, vol. 30, no. 5, pp. 2643-2656.
 [9] Sattarpour, T., & Farsadi, M. (2017). Parking lot allocation with maximum economic benefit in a distribution network. International Transactions on Electrical Energy Systems, 27(1).
 [10] Kazemi, M. A., Sedighizadeh, M., Mirzaei, M. J., & Homaee, O. (2016). Optimal siting and sizing of distribution system operator owned EV parking lots. Applied Energy, 179, 1176-1184.
[11] FERC, “Regulatory commission survey on demand response and time based rate programs/tariffs”. www.FERC.gov, August 2006.
[12] Moghaddam, M. P., Abdollahi, A., & Rashidinejad, M. (2011). Flexible demand response programs modeling in competitive electricity markets. Applied Energy, vol. 88, no. 9, pp. 3257-3269.
[13] Aalami, H. A., Moghaddam, M. P., & Yousefi, G. R. (2010). Modeling and prioritizing demand response programs in power markets. Electric Power Systems Research, vol. 80, no. 4, pp. 426-435.
[14] Rahmani-andebili, M. (2016). Modeling nonlinear incentive-based and price-based demand response programs and implementing on real power markets. Electric Power Systems Research, vol. 132, pp. 115-124.
[15] Shafie-khah, M., Heydarian-Forushani, E., Osório, G. J., Gil, F. A., Aghaei, J., Barani, M., & Catalão, J. P. (2016). Optimal behavior of electric vehicle parking lots as demand response aggregation agents. IEEE Transactions on Smart Grid, vol. 7, no. 6, pp. 2654-2665.
[16] Afshan, R., & Salehi, J. (2017). Optimal operation of distribution networks with presence of distributed generations and battery energy storage systems considering uncertainties and risk analysis. Journal of Renewable and Sustainable Energy, vol. 9, no. 1.
[17] Zakariazadeh, A., Jadid, S., & Siano, P. (2014). Stochastic operational scheduling of smart distribution system considering wind generation and demand response programs. International Journal of Electrical Power & Energy Systems, vol. 63, pp. 218-225.
[18] Tabatabaee, S., Mortazavi, S. S., & Niknam, T. (2016). Stochastic Scheduling of Local Distribution Systems Considering High Penetration of Plug-in Electric Vehicles and Renewable Energy Sources. Energy. vol. 121, pp. 480-490.
[19] Lv, T., Ai, Q., & Zhao, Y. (2016). A bi-level multi-objective optimal operation of grid-connected micro grids. Electric Power Systems Research, vol. 131, pp. 60-70.
[20] Bahramara, S., Moghaddam, M. P., & Haghifam, M. R. (2015). Modeling hierarchical decision making framework for operation of active distribution
grids. IET Generation, Transmission & Distribution, vol. 9, no. 16, pp. 2555-2564.
[21] Bahramara, S., Moghaddam, M. P., & Haghifam, M. R. (2016). A bi-level optimization model for operation of distribution networks with micro-grids. International Journal of Electrical Power & Energy Systems, vol. 82, pp. 169-178.
]22[ فلقی، ح.، رمضانی، م.، حقی­فام،م. (1391) ، تحلیل تاثیر نیروگاه­های بادی بر قابلیت تبادل شبکه های انتقال در سیستم قدرت، مجله علمی و پژوهشی مدل­سازی در مهندسی، دانشگاه سمنان، سال 10، شماره 30.
]23[ احمدی گرجی، م.، امجدی، ن. (1394) ، برنامه­ریزی توسعه پویای شبکه­های توزیع در حضور منابع تولید پراکنده با استفاده از یک الگوریتم بهینه­سازی جدید دو سطحی، مجله علمی و پژوهشی مدل­سازی در مهندسی، دانشگاه سمنان، سال 13، شماره 43.
 [24] Shafie-khah, M., Siano, P., Fitiwi, D. Z., Mahmoudi, N., & Catalão, J. P. (2017). An Innovative Two-Level Model for Electric Vehicle Parking Lots in Distribution Systems with Renewable Energy. IEEE Transactions on Smart Grid.
[25] Rueda-Medina, A. C., Franco, J. F., Rider, M. J., Padilha-Feltrin, A., & Romero, R. (2013). A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems. Electric power systems research, vol. 97, pp. 133-143.
[26] Ruiz, C., Conejo, A.J. and Smeers, Y. (2012). Equilibrium in an oligopolistic electricity pool with stepwise offer curves. IEEE Transactions on Power Systems, vol. 27, no. 2, pp. 752-761.
[27] Dempe, S., Kalashnikov, V., Pérez-Valdés, G.A. and Kalashnykova, N., Bilevel programming problems: theory, algorithms and applications to energy networks. Springer Publishing. 2015.
]28[ دهقان، ش.، امجدی، ن. (1395) ، برنامه­ریزی غیرقطعی توسعه­ی چندساله­ی سیستم قدرت با در نظر گرفتن مزرعه­های بادی به کمک ترکیب برنامه­ریزی تصادفی و معیار حداقل- حداکثر پشیمانی، مجله علمی و پژوهشی مدل­سازی در مهندسی، دانشگاه سمنان، سال 14، شماره 47.
[30] Liu, Z., Wen, F., & Ledwich, G. (2011). Optimal siting and sizing of distributed generators in distribution systems considering uncertainties. IEEE Transactions on power delivery, vol. 26, no. 4, pp. 2541-2551.
[31] Talari, S., Yazdaninejad, M., & Haghifam, M. R. (2015). Stochastic-based scheduling of the micro grid operation including wind turbines, photovoltaic cells, energy storages and responsive loads. IET Generation, Transmission & Distribution, vol. 9, no. 12, pp. 1498-1509.