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A two-stage stochastic optimization based-on monte carlo simulation for maximizing the profitability of a smart microgrid | ||
| Journal of Hyperstructures | ||
| دوره 7، Spec. 2nd CSC2017، شهریور 2018، صفحه 67-81 اصل مقاله (892.91 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22098/jhs.2018.2691 | ||
| نویسندگان | ||
| Mohammad Javad Salehpour* ؛ Seyed Masoud Moghaddas Tafreshi | ||
| Department of Electrical Engineering, University of Guilan, Rasht, Iran | ||
| چکیده | ||
| In this paper, a two-stage stochastic model for optimizing the profit of a smart microgrid is proposed in which the uncertainty of loads, electricity market price and renewable generation are modeled using developing stochastic scenarios with Monte Carlo simulation method. Also, in order to reduce solving time of optimization problem the number of stochastic scenarios is reduced by Kantorovich distance method. | ||
| کلیدواژه‌ها | ||
| Smart microgrid؛ Two-stage stochastic optimization؛ Monte Carlo simulation؛ Kantorovich distance؛ Uncertainty | ||
| مراجع | ||
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[1] J. Shahram and A. Zakariazadeh, Smart distribution systems, Iran University of Science and Technology press, 29 (2015), 15–30. [2] P. Agrawal, How ’Micro-grids’ are Poised To Alter The Power Delivery Land-scape, Utility Automation & Engineering T&D, 180 (2008) 1-10 [3] S. A. Alavi, A. Ahmadian, and M. Aliakbar-Golkar, Optimal probabilistic en-ergy management in a typical micro-grid based-on robust optimization and point estimate method. Energy Conversion and Management, 95 (2015), 314–325. [4] K. Liu, F. Gao, Z. Wang, X. Guan, Q. Zhai, and J. Wu, Self-balancing robust scheduling model for demand response considering electricity load uncertainty in enterprise micro-grid, IEEE PES General Meeting — Conference & Exposition (2014). [5] Y. Xiang, J. Liu, and Y. Liu, Robust Energy Management of Micro-grid With Uncertain Renewable Generation and Load, IEEE Transactions on Smart Grid,7 (2016), 1034–1043. [6] G. Liu, Y. Xu, and K. Tomsovic, Bidding Strategy for Micro-grid in Day-Ahead Market Based on Hybrid Stochastic/Robust Optimization, IEEE Transactions on Smart Grid, 7 (2016), 227–237. [7] S. Nojavan, K. Zare, and M. A. Ashpazi, A hybrid approach based on IGDTMPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market, International Journal of Electrical Power & Energy Systems, 69 (2015), 335–343. [8] M. Aien, A. Hajebrahimi, and M. Fotuhi-Firuzabad, A comprehensive review on uncertainty modeling techniques in power system studies, Renewable and Sus-tainable Energy Reviews, 57 (2016), 1077–1089. [9] N. Growe-Kuska, H. Heitsch, and W. Romisch, Scenario reduction and scenario tree construction for power management problems, IEEE Bologna Power Tech Conference Proceedings, 3 (2003), 1–12. [10] M. Carrion and J. M. Arroyo, A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem, IEEE Transactions on Power Systems, 21 (2006), 1371–1378. | ||
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آمار تعداد مشاهده مقاله: 19 تعداد دریافت فایل اصل مقاله: 18 |
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