Stochastic Operation Scheduling of a Microgrid With Multi Connection Points Considering Risk Constraint in the presence of Responsive Loads

Document Type : Original Article

Authors

1 Department of Electrical and Computer Engineering, Babol Noshivani University of Technology, Babol, Iran

2 HV Substations Research Group, Department of Electrical and Computer Engineering, Babol Noshivani University of Technology, Babol, Iran

Abstract

Nowadays optimal operation of micro grids is important. A micro grid is an energy system that provides consumers with electricity through renewable-based or traditional resources. In this paper, it is supposed that the micro grid is capable of being immediately separated from the main grid due to disturbance and connected to the adjacent micro grid to meet the demand through buying electric power from the adjacent operator. In addition to this, stochastic operation scheduling of power resources is proposed the objective function of which is to minimize operating cost. Also, outage few scenarios including main grid outage and the uncertainties associated with wind generation and load are considered. Then, we use a scenario reduction technique to reduce the number of scenarios. Considering risk constraint, the effect of different levels of risk on the operating cost and resources commitment is analyzed and compared in grid-connected mode. The case studies results clearly state the effect of demand response and energy storage on operating cost reduction especially in occurrence of upstream outage and unavailability of adjacent micro grid capacity or due to connection status.

Keywords


[1]      A. Khodaei, “Resiliency-oriented microgrid optimal scheduling,” IEEE Trans. on Smart Grid, vol. 5, no. 4, pp. 1584–1591, 2014.
[2]      A. Majzoobi, and A. Khodaei, “Application of Microgrids in Supporting Distribution Grid Flexibility,” IEEE Trans. on Power Systems, vol. 61, pp. 335–345, 2016
F. Wu, X. Li, F. Feng and H. B. Gooi, “Modified Cascaded Multilevel Gird-Connected Inverter to Enhance European Efficiency,” IEEE Trans. Ind. Informatics, vol. 11, no. 6, pp.1358-1365, 2015
[3]      Z. Chen, L. Wu, and Y. Fu, “Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization,” IEEE Trans. on Smart Grid, vol. 3, no. 4, pp. 1822–1831, 2012.
[4]      M. Mazidi, A. Zakariazadeh, and S. Jadid, “Integrated Scheduling of Renewable Generation and Demand Response Programs in a Microgrid,” Energy Conversion and Management, vol. 86, pp. 1118-1127, 2014.
[5]      جمیل جنتی و داریوش نظرپور، «مدیریت انرژی پارکینگ هوشمندخودروهای برقی در یک ریزشبکه با نظر گرفتن اثرات برنامه پاسخگویی بار»، مجله مهندسی برق دانشگاه تبریز، دوره 47، شماره 2، صفحه 467-455، 1396.
[6]      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.
[7]      A. Khodaei, “Microgrid optimal scheduling with multi-period islanding constraints,” IEEE Trans. on Power Systems, vol. 29, no. 3, pp. 1383-1392, 2014.
[8]      علی مهدی‌زاده و نوید تقی‌زادگان کلانتری، «برنامه‌ریزی تصادفی ریزشبکه جزیره‌ای در حضور سیستم ذخیره‌ساز هیدروژنی و برنامه پاسخگویی بار»، مجله مهندسی برق دانشگاه تبریز، دوره 47، شماره 2، صفحه 725-711، 1396.
[9]      M. Rouholamini and M. Mohammadian, “Energy management of a grid-tied residential-scale hybrid renewable generation system incorporating fuel cell and electrolyzer,” Energy and Buildings, vol. 102, pp. 406-416, 2015.
[10]      M. Rouholamini and M. Mohammadian, “Energy management of a grid-tied residential-scale hybrid renewable generation system incorporating fuel cell and electrolyzer,” Renewable Energy, vol. 96, pp. 354-365, 2016.
A. Khodaei, “Provisional micogrids,” IEEE Trans.on Smart Grid, vol. 6, no. 3, pp. 1107-1115, 2015.
[11]      A. Gholami, T. Shekari, F. Aminifar, and M. Shahidepour, “Microgrid scheduling with uncertainty: The Quest for Resilience,” IEEE Trans. on Smart Grid, vol. 7, no. 6, pp. 2849 - 2858, 2016.
[12]      R. T. Rockafellar and S. Uryasev, “Conditional value-at-risk for general loss distributions,” Journal of Banking and Finance, vol. 26, no. 7, pp. 1443–1471, 2002.
[13]      A. J. Conejo, M. Carrión, and J. M. Morales, Decision making under uncertainty in electricity markets vol. 1: Springer, 2010.
[14]      M. Carrion, A. J. Conejo, and J. M. Arroyo, “Forward contracting and selling price determination for a retailer,” IEEE Trans. on Power Systems., vol. 22, no. 4, pp. 2105–2114, 2007.
[15]      A. J. Conejo, R. Garcia-Bertrand, M. Carrion, A. Caballero, and A. de Andres, “Optimal involvement in futures markets of a power producer,” IEEE Trans. on Power Systems, vol. 23, no. 2, pp. 703–711, 2012.
[16]      A. Safdarian, M. Fotuhi-Firuzabad and M. Lehtonen, “A Stochastic Framework for Short-Term Operation of Distribution Company,” IEEE Trans. on Power Systems, vol. 28, no. 4, pp. 4712-4721, 2013.
[17]      M. Carrion, A. B. Philpott, A. J. Conejo, and J. M. Arroyo, “A stochastic programming approach to electric energy procurement for large consumers,” IEEE Trans. on Power Systems., vol. 22, no. 2, pp. 744–754, 2007.
[18]      J. Aghaei, M. Barani, M. Shafi-khah, A. A. Sanchez de la Nieta and J. Catalao, “Risk-constrainted offering strategy for aggregated hybrid power plant including wind power producer and demand response provider,” IEEE Trans. on Sustainable Energy, vol. 7, no. 2, pp. 513–525, 2016.
[19]      Y. Zhang, N. Gatsis, and G. Ginnakis. “Robust Energy Management for Microgrids with High Penetration Renewables,” IEEE Trans. on Sustainable Energy, vol. 4, no. 4, pp. 944-953, 2013.
[20]      H. Geramifar, M. Shahabi, and T. Barforoshi, “Coordination of energy storage systems and DR resources for optimal scheduling of microgrids under uncertainties,” IET Renewable Power Generation, vol. 11, no. 2, pp. 378-388, 2017.
[21]      National Renewable Energy Laboratory: Western Wind ResourcesDataset, http://wind.nrel.gov/ web_nrel.
[22]      PJM website, http://pjm.com/markets-and-operations.aspx
[23]      IBM Corporation, IBM ILOG CPLEX, version 12.0, User's Manual, Aug, 2013, ftp://public.dhe.ibm.com.