تعداد نشریات | 27 |
تعداد شمارهها | 362 |
تعداد مقالات | 3,209 |
تعداد مشاهده مقاله | 4,711,418 |
تعداد دریافت فایل اصل مقاله | 3,220,361 |
Optimal Decision Making Framework of an Electric Vehicle Aggregator in Future and Pool markets | ||
Journal of Operation and Automation in Power Engineering | ||
مقاله 2، دوره 6، شماره 2، اسفند 2018، صفحه 157-168 اصل مقاله (856.21 K) | ||
نوع مقاله: Research paper | ||
شناسه دیجیتال (DOI): 10.22098/joape.2006.3608.1288 | ||
نویسندگان | ||
H. Rashidizadeh-Kermani1؛ H. R. Najafi* 1؛ A. Anvari-Moghaddam2؛ J. M. Guerrero2 | ||
1Department of Electrical & Computer Engineering, University of Birjand, Birjand, Iran | ||
2Department of Energy Technology, Aalborg University, Aalborg, Denmark | ||
چکیده | ||
Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain optimal decision making of an EV aggregator. To deal with mentioned uncertainties, the aggregator’s risk aversion is applied using conditional value at risk (CVaR) method in the proposed model. The proposed two-stage risk-constrained decision-making problem is applied to maximize EV aggregator’s expected profit in an uncertain environment. The aggregator can participate in the future and pool market to buy the required energy of EVs and offer optimal charge/discharge prices to the EV owners. In this model, in order to assess the effects of EVs owners’ reaction to the aggregator’s offered prices on the purchases from electricity markets, a sensitivity analysis over risk factor is performed. The numerical results demonstrate that with the application of the proposed model, the aggregator can supply EVs with lower purchases from markets. | ||
کلیدواژهها | ||
Aggregator؛ Conditional Value at Risk (CVaR)؛ Electric Vehicle؛ future market؛ Pool market | ||
مراجع | ||
[1] H. Rashidizadeh-Kermani, M. Vahedipour-Dahraie, H. R. Najafi, A. Anvari- Moghaddam, J. M. Guerrero, “A stochastic bi-level scheduling approach for participation of EV aggregators in competitive electricity markets,” Appl. Sci., vol. 7, no. 10, pp. 1-16, 2017. [2] M. Carrión, J. M. Arroyo, A. J. Conejo, “A bilevel stochastic programming approach for retailer futures market trading,” IEEE Trans. Power Syst., vol. 24, no. 3, pp.1446-1456, 2009. [3] H. Niu, R. Baldick, G. D. Zhu, “Supply function equilibrium bidding strategies with fixed forward contracts,” IEEE Trans. Power Syst. vol. 20, no. 4, pp. 1859-1867, 2005. [4] M. Vahedipour-Dahraie, H. Rashidizaheh-Kermani, H.R. Najafi, A. Anvari-Moghaddam, J. M. Guerrero, “Coordination of EVs participation for load frequency control in isolated microgrids,” Appl. Sci., vol.7, no.6, 539, pp.1-16, 2017. [5] D. Pengwei, L. Ning, “Appliance commitment for household load scheduling,” IEEE Trans. Smart Grid, vol. 2, no. 2, pp. 411-419, 2011. [6] S. Aghajani, M. Kalantar, “Operational scheduling of electric vehicles parking lot integrated with renewable generation based on bi-level programming approach,” Energy, vol. 139, pp. 422-432, 2017. [7] M. Vahedipour-Dahraie, H. R. Najafi, A. Anvari- Moghaddam, J. M. Guerrero, “Study of the effect of time-based rate demand response programs on stochastic day-ahead energy and reserve scheduling in islanded residential microgrids,” Appl. Sci., vol. 7, no. 4, pp. 1-19, 2017. [8] A. Badri, K. Hoseinpour Lonbar, “A short-term optimal decision making framework of an electricity retailer considering optimized EVs charging model,” Int. Trans. Electr. Energy Syst., vol. 26, no. 8, pp. 1705-1724, 2016. [9] E. Sortomme, M. A. El-Sharkawi, “Optimal charging strategies for unidirectional vehicle-to-grid,” IEEE Trans. Smart Grid, vol. 2, no. 2, pp. 131-138, 2011. [10] R. Bessa, M. Matos, F. Soares, J. Lopes, “Optimized bidding of a EV aggregation agent in the electricity market,” IEEE Trans. Smart Grid, vol. 3, no.1, pp. 443-452, 2012. [11] R. Bessa, M. Matos, “Optimization models for EV aggregator participation in a manual reserve market,” IEEE Trans. Power Syst., vol. 28, no.3, pp. 3085-3095, 2013. [12] M. G. Vaya, G. Andersson, “Optimal bidding strategy of a plug-in electric vehicle aggregator in day-ahead electricity markets under uncertainty,” IEEE Trans. Power Syst., vol. 30, no. 5, pp. 2375-2385, 2015. [13] N. Rotering, M. Ilic, “Optimal charge control of plug-in hybrid electric vehicle in deregulated electricity markets,” IEEE Trans. Power Syst., vol. 26, no.3, pp. 1021-1029, 2011. [14] A. Al-Awami, E. Sortomme, “Coordinating vehicle-to-grid services with energy trading,” IEEE Trans. Smart Grid, vol. 3, no.1, pp. 453-462, 2012. [15] Z. Tan, P. Yang, A. Nehorai, “An optimal and distributed demand response strategy with electric vehicles in the smart grid,” IEEE Trans. Smart Grid, vol. 5, no. 2, pp. 861-869, 2014. [16] S. Nojavan, K. Zare, B. Mohammadi-Ivatloo, “Risk-based framework for supplying electricity from renewable generation-owning retailers to price-sensitive customers using information gap decision theory,” Electr. Power Energy Syst., vol. 93, pp. 156-170, 2017. [17] I. Momber, A. Siddiqui, T. Gómez, L. Söder, “Risk averse scheduling by a PEV aggregator under uncertainty,” IEEE Trans. Power Syst., vol. 30, no.2, pp. 882-891, 2015. [18] G. N. Bathurst, G. Strbac, “Value of combining energy storage and wind in short-term energy and balancing markets,” Electr. Power Syst. Res., vol. 67, no.1, pp. 1-8, 2003. [19] H. Wu, M. Shahidehpour, A. Alabdulwahab, A. Abusorrah, “A game theoretic approach to risk-based optimal bidding strategies for electric vehicle aggregators in electricity markets with variable wind energy resources,” IEEE Trans. Sustain. Energy, vol. 7, no.1, pp. 374-385, 2016. [20] M. Zugno, J. M. Morales, P. Pinson, H. Madsen, “Pool strategy of a price-maker wind power producer,” IEEE Trans. Power Syst., vol. 28, no.3, pp. 3440-3450, 2013. [21] L. Baringo, A. J. Conejo, “Strategic offering for a wind power producer,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4645-4654, 2013. [22] J. M. Morales, A. J. Conejo, J. Perez-Ruiz, “Short-term trading for a wind power producer,” IEEE Trans. Power Syst., vol. 25, no.1, pp. 554-564, 2010. [23] Vahedipour-Dahraie, M., Rashidizadeh-Kermani, H., Najafi, H.R, A. Anvari-Moghaddam and J.M. Guerrero, “Stochastic security and risk-constrained scheduling for an autonomous microgrid with demand response and renewable energy resources,” IET Renewable Power Gener., vol. 11, no. 14, pp. 1812- 1821, 2017. [24] S. Aghajani, M. Kalantar, “A cooperative game theoretic analysis of electric vehicles parking lot in smart grid,” Energy, vol. 137, pp.129-139, 2017. [25] A. Zakariazadeh, S. Jadid, P. Siano. “Integrated operation of electric vehicles and renewable generation in a smart distribution system,” Energy Convers. Manage., vol.89, pp. 99-110, 2015. [26] A. Badri, K. Hoseinpour Lonbar, “Stochastic multiperiod decision making framework of an electricity retailer considering aggregated optimal charging and discharging of electric vehicles,” J. Oper. Autom. Power Eng., vol. 3, no. 1, pp. 34-46, 2015. [27] E. Heydarian-Forushani1, H. A. Aalami, “Multi objective scheduling of utility-scale energy storages and demand response programs portfolio for grid integration of wind power,” J. Oper. Autom. Power Eng., vol. 4, no. 2, pp. 104-116, 2016. [28] N. G. Paterakis, A. A. Sánchez de la Nieta, A. G. Bakirtzis, J. Contreras, J. P. S. Catalão, “Effect of risk aversion on reserve procurement with flexible demand side resources from the iso point of view, ” IEEE Trans. Sust. Energy, vol. 8, no.3, pp. 1040-1050, 2017. [29] M. Alipour, B. Mohammadi-Ivatloo, M. Moradi-Dalvand, K Zare, “Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets,” Energy, vol. 118, pp. 1168-1179, 2017. [30] M. Pantos, “Exploitation of electric-drive vehicles in electricity markets,” IEEE Trans. Power Syst., vol. 27, no.2, pp. 682-694, 2012. [31] D. Wu, D. Aliprantis D., L. Ying, “Load scheduling and dispatch for aggregators of plug-in electric vehicles,” IEEE Trans. Smart Grid, vol.3, no.1, pp. 368-376, 2012. [32] M. Shafie-Khah, M. Parsa Moghaddam , M. K. Sheikh-El-Eslami, M. Rahmani-Andebili “Modeling of interacti-ons between market regulations and behavior of plug-in electric vehicle aggregators in a virtual power market environment,” Energy, vol. 40, no.1, pp. 139-150, 2012. [33] I. Momber, S. Wogrin, T. Gómez San Román, “Retail Pricing: A bilevel program for PEV aggregator decisions using indirect load control,” IEEE Trans. Power Syst. vol. 31, no.1, pp. 464-473, 2016. [34] T. Dai, W. Qiao, “Optimal bidding strategy of a strategic wind power producer in the short-term market,” IEEE Trans. Sustain. Energy, vol.6, no.3, pp. 707-719, 2015. [35] A. J. Conejo, M. Carrión and J. M. Morales, Decision making under uncertainty in electricity markets, Springer, 2010, pp. 80-90. [36] The ILOG CPLEX, 2008. [Online]. Available: http://www.ilog.com/ products/cplex/. Products /cplex/. [37] A. Brooke, D. Kendrick, A. Meeraus, and R. Raman, GAMS: A User’s Guide. Washington, DC: GAMS Development Corporation, 1998. | ||
آمار تعداد مشاهده مقاله: 1,093 تعداد دریافت فایل اصل مقاله: 765 |