Optimization of the Microgrid Scheduling with Considering Contingencies in an Uncertainty Environment

International Journal of Smart Electrical Engineering

مقاله 5، دوره 02، شماره 2، مرداد 2013، صفحه 95-101   

نویسندگان

Saber Talari¹؛ Mahmoud Reza Haghifam²؛ Ali Akhavein³

¹Electrical Engineering Department of Islamic Azad University-South Tehran Branch, Tehran, Iran

²Electrical and Computer Engineering Islamic Azad University-South Tehran Branch, Tehran, Iran.

³Electrical Engineering Department of Islamic Azad University-South Tehran Branch, Tehran, Iran.

چکیده

In this paper, a stochastic two-stage model is offered for optimization of the day-ahead scheduling of the microgrid. System
uncertainties including dispatchable distributed generation and energy storage contingencies are considered in the stochastic
model. For handling uncertainties, Monte Carlo simulation is employed for generation several scenarios and then a reduction
method is used to decrease the number of scenarios. The scenarios are used in second stage of the stochastic model to check
the system security. The amount of spinning reserve and energy are optimized in the first stage by minimizing the total cost
of operation. A sample microgrid is used to compare the offered stochastic model with the deterministic one

کلیدواژه‌ها

DER uncertainty؛ Energy storage؛ Microgrid؛ Stochastic security constrained unit commitment

مراجع

[1]

A. Vaccaro, M. Popov, D. Villacci, V. Terzija, "An Integrated Framework for Smart MicrogridsModeling, Monitoring, Control, Communication, Proceedings of the IEEE,Vol.99, No.1, pp.119 - 132, 2011.

[2]

P.M. Costa, M. Matos, "Assessing the contribution of microgrids to the reliability of distribution networks", Electrical Power & Energy Systems, Vol.79, No.2, pp.382–389, 2009.

[3]

F. Katiraei, , et al., "Microgrid Management", IEEE Power and Energy Magazine, Vol.6, No.3, pp.54-65, 2008.

[4]

Logenthiran, T., Srinivasan, D., Khambadkone, M., "Multi-agent system for energy resource scheduling of integrated

microgrids in a distributed system", Electric Power Systems Research, Vol.81, No.1, pp. 138-148, 2011.

[5]

Tsikalakis, A.G., Hatziargyriou, N.D., "Operation of multi agent system for microgrid control". IEEE Trans. Power Syst., Vol. 20, No. 3, pp. 1447 - 55, 2005.

[6]

Tsikalakis, A.G., Hatziargyriou, N.D., "Centralized control for optimizing microgrids operation", IEEE Trans. Energy Convers., Vol.23, No.1, pp. 241 - 248, 2008.

[7]

Ross, M., Hid Energy storage system scheduling for an isolated microgrid", IET Renew. Power Gener., Vol.5, No.2, pp. 117 - 123, 2011.

[8]

Mohamed, F., A, Koivo, H.N., "System modeling and online optimal management of MicroGrid using Mesh Adaptive Direct Search", Electrical Power & Energy Systems, Vol.32, No.5, pp. 398–407, 2010.

[9]

Bouffard, F., Galiana, F.D., "An electricity market with a probabilistic spinning reserve criterion", IEEE Trans. Power Syst., Vol.19, No.1, pp. 300- 307, 2004.

[10]

Bouffard, F., Galiana, F.D., Conejo, A.J., "Market-clearing with stochastic security-part I: formulation", IEEE Trans. Power Syst., Vol.20, No.4, pp. 1818- 1826, 2005.

[11]

Aminifar, F., Fotuhi-Firuzabad, M., Shahidehpour, M., "Unit commitment with probabilistic spinning reserve and interruptible load considerations", IEEE Trans. Power Syst., Vol.24, No.1, pp. 388- 397, 2009.

[12]

Yazdaninejad, M., Haghifam, M.R., "Evaluation of responsive load participation in optimal satisfying system security constraints", IEEE Power and Energy Society General Meeting, San Diego, CA., pp. 1-8, 2012.

[13]

Valenzuela, J., Mazumdar, M., "Monte Carlo computation of power generation production costs under operating constraints", IEEE Trans. Power Syst., Vol.16, No.4, pp. 671- 677, 2001.

[14]

Lei, W., Shahidehpour, M., Tao, L., "Stochastic security-constrained unit commitment", IEEE Trans. Power Syst., Vol.22, No.2, pp. 800- 811, 2007.

[15]

Khodayar, M.E., Barati, M., Shahidehpour, M., "Integration of high reliability distribution system in microgrid operation", IEEE Trans. Smart Grid, Vol.3, No.4, pp. 1997-2006, 2012.

[16]

Parvania, M., Fotuhi-Firuzabad, M., "Demand response scheduling by stochastic SCUC", IEEE Trans. Smart Grid, Vol.1, No.1, pp. 89-98, 2010.

[17]

Li, Y., Zio, E., "Uncertainty analysis of the adequacy assessment model of a distributed generation system", Renewable Energy, Vol.41, No.1, pp. 235–244, 2012.

[18]

Jun, Z., Junfeng, L., Jie, W., Ngan, H.W., "A multi-agent solution to energy management in hybrid renewable energy generation system". Renewable Energy, Vol.36, No.1, pp. 1352-63, 2011.

[19]

Niknama, T., Golestaneh, F., Malekpourb, A., "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational search algorithm", Energy, No.43, Vol.1, pp. 427–437, 2012.

[20]

N. Amjady, J. Aghaei, H. A. Shayanfar, "Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security", IEEE Trans. Power Syst., Vol. 24, No. 4, pp. 1841-1854 ,2009

[21]

Heitsch, H., Roemisch, W., "Scenario tree reduction for multistage stochastic programs", Comput. Manag. Sci., 6, (2), pp.117–133, 2009.

[22]

Scenred2/Gams documentation [Online] available from: www.gams.com/dd/docs/solvers/scenred2.pdf accessed April 2013.