برنامه‌ریزی بهینه انرژی و ذخیره یک ریزشبکه جزیره‌ای با درنظرگرفتن بارهای پاسخ‌گو و قیود امنیتی

[1] J. S. Vardakas,   N. Zorba,  and C. V. Verikoukis, “A survey on demand response programs in smart grids: pricing methods and optimization algorithms,”  IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 152 – 178, 2015.

[2] K. McKenna, and  A. Keane,  “Residential load modeling of price-based demand response for network impact studies,”IEEE Transactions on Smart Grid, vol. 7, no. 5, pp. 2285 – 2294, 2016.

[3] N. G. Paterakis,   A. Taşcıkaraoğlu,  O.  Erdinç,   A. G. Bakirtzis, and  J. P. S. Catalão, “Assessment of demand-response-driven load pattern elasticity using a combined approach for smart households,” IEEE Transactions on Industrial Informatics, vol. 12, no. 4, pp:1529 – 1539, 2016.

[4] E. Karangelos, and F. Bouffard, “Towards full integration of demand-side resources in joint forward energy/reserve electricity markets,” IEEE Trans. Power Syst., vol. 27, no. 1, pp. 280-289, 2010.

[5] J. Shan, A. Botterud, and S. M. Ryan, “Impact of demand response on thermal generation investment with high wind penetration,” IEEE Trans. Smart Grid, vol. 4, pp. 2374-2383, 2013.

[6] X. Peng, and P. Jirutitijaroen, “A stochastic optimization formulation of unit commitment with reliability constraints,” IEEE Trans. Smart Grid, vol. 4, pp. 2200-2008, 2013.

[7] N. Parhizi, M. Marzband, S. M. Mirhosseini Moghaddam, B. Mohammadi Ivatloo, and F. Azarinejadian, “The experimental implementation of an energy management system for a grid connected microgrid by using a multi-period imperialist competition algorithm”, Tabriz Journal of Electrical Eng., vol. 46, no. 1, 2016.

[8] M. Javadi, S. M. Mirhosseini Moghaddam, and M. Marzband, “Optimal energy management of microgrids in the retail market based on non-cooperative game theory considering the uncertainty,” Tabriz Journal of Electrical Eng., vol. 46, no. 1, 2016.

[9] علی مهدی‌زاده، نوید تقی‌زادگان کلانتری،"برنامه‌ریزی تصادفی ریزشبکه جزیره‌ای در حضور سیستم ذخیره‌ساز هیدروژنی و برنامه‌ی پاسخگویی بار" مجله مهندسی برق دانشگاه تبریز، صفحات 725-711، جلد 47، شماره 2، 1395.

[10] S. Talari,  M. Yazdaninejad, and M. R. Haghifam, “Stochastic-based scheduling of the microgrid operation including wind turbines, photovoltaic cells, energy storages and responsive loads,”  IET Generation, Transmission & Distribution, vol. 9, no. 12, pp. 1498 – 1509, 2015.

[11] N. Amjady, J. Aghaei, and H. A. Shayanfar, “Stochastic multiobjective market clearing of joint energy and reserves auctions ensuring power system security,”  IEEE Trans.Power Syst, vol. 24, pp. 1841-1854, 2009.

[12] N. Rezaei, and M. Kalantar, “Stochastic frequency-security constrained energy and reserve management of an inverter interfaced islanded microgrid considering demand response programs,” Int. J. Electr Power Energy Syst., vol. 69, pp. 273–286, 2015.

[13] N. Rezaei, and M.Kalantar, “Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework,” Energy Conversion and Management, vol. 92, pp. 287-301, 2015.

[14] M. Bayat, K. Sheshyekani, M. Hamzeh, and A. Rezazadeh, “Coordination of Distributed Energy Resources and Demand Response for Voltage and Frequency Support of MV Microgrids,” IEEE Trans. Power Syst., vol. 31, no. 1, pp. 506-516, 2016.

[15] J. Aghae, M. Karami, K.M. Muttaqi, H.A. Shayanfar, nd A. Ahmadi, “MIP-based stochastic security-constrained daily hydrothermal generation scheduling,”IEEE Syst J. vol. 9, no. 2, pp. 615-628, 2015.

[16] D. Arthur, S. Vassilvitskii, “K-means++: The advantages of careful seeding,” In Proc. 18th Annu. ACM-SIAM Symp. Discrete Algorithms (SODA ’07), New Orleans, LA, USA, pp. 1027-1035, 2007.

[17] A. J. Conejo, M. Carrion, and J. M. Morales, “Decision Making Under Uncertainty in Electricity Markets,” New York, NY, USA: Springer, 2010.

[18] اعلمی، حبیب الله، "مدل‌سازی پاسخ‌گویی بار مبتنی بر ضرایب حساسیت قیمتی تقاضا"، پایان‌نامه دکتری، دانشگاه تربیت مدرس، 1389.

[19] M. Alipour, B. Mohammadi-Ivatloo, and K. Zare, “Stochastic risk-constrained short-term scheduling industrial cogeneration systems in the presence of demand response programs,” Applied Energy, vol. 136, pp. 393-404, 2014.

[20] A. Moshari, A. Ebrahimi, M. Fotuhi-Firuzabad, “Short-term impacts of DR programs on reliability of wind integrated power systems considering demand-side uncertainties,” IEEE Trans. Power Syst., vol. 31, no. 3, pp. 2481-2490, 2016.

[21] A. Zakariazadeh, S. Jadid, and P. Siano, “Smart microgrid energy and reserve scheduling with demand response using stochastic optimization,” Electr. Power Energy Syst., vol.  63, pp. 523–533, 2014.

[22] N.G. Paterakis, O. Erdinc, A.G. Bakirtzis, and J.P.S. Catalão, “Load-Following Reserves Procurement Considering Flexible Demand-Side Resources under High Wind Power Penetration,” IEEE Trans. Power Syst., vol. 30, pp. 1337-1350, 2015.

[23] 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.

[24] “The General Algebraic Modeling System (GAMS) Software,” online available at: http://www.gams.com, accessed on 15 September 2016.