برنامهریزی بهینه اقتصادی یک ریزشبکه در حالت جزیرهای با در نظر گرفتن منابع تجدیدپذیر بادی و خورشیدی، باتری و سیستم ذخیرهساز هیدروژنی در حضور برنامه پاسخگویی بار
محورهای موضوعی : مهندسی برق و کامپیوترعلی مهدیزاده 1 , نوید تقیزادگان کلانتری 2
1 - دانشگاه شهید مدنی آذربایجان
2 - دانشگاه شهید مدنی آذربایجان
کلید واژه: باتری ذخیرهساز سیستم ذخیرهساز هیدروژنی و برنامه پاسخگویی بار ریزشبکه منابع انرژی تجدیدپذیر,
چکیده مقاله :
ریزشبکهها در سیستم توزیع با بهرهگیری از منابع انرژی پراکنده تجدیدپذیر قادر به تأمین بار خود در سیستم سطح ولتاژ پایین هستند و میتوانند در قسمتهایی که دسترسی به شبکه برق سراسری امکانپذیر نیست با هزینه سرمایهگذاری کمتر استفاده شوند. ریزشبکه مورد استفاده در این پژوهش دارای منابع تجدیدپذیر بادی و خورشیدی و سیستم ذخیرهساز هیدروژنی میباشد. این مقاله، استراتژی مدیریت انرژی جدید را در ریزشبکه با وجود سیستم ذخیرهساز هیدروژنی و با در نظر گرفتن عدم قطعیتهای منابع تجدیدپذیر ارائه داده است. مینیممکردن هزینه بهرهبرداری باتری، سیستم ذخیرهساز هیدروژنی، هزینه مربوط به انرژی تأمیننشده و مازاد انرژی با در نظر گرفتن قیود تأمین بار از اهداف این استراتژی جدید میباشد. محدودیتهای فنی در نظر گرفته شده در این مقاله شامل محدودیتهای منابع تولید پراکنده و سیستمهای ذخیرهساز هیدروژنی و باتری میباشد. سیستم ذخیرهساز هیدروژنی شامل الکترولایزر، تانکهای هیدروژنی و پیل سوختی میباشد. برنامه پاسخگویی طرف بار به منظور مسطحکردن نمودار بار و بهرهبرداری بهینه از ریزشبکه به کار گرفته شده است. با استفاده از نرمافزار GAMS مدل پیشنهادی روی یک ریزشبکه اجرا شده که خروجیهای حاصل از شبیهسازی این مدل روی ریزشبکه نشان میدهد استفاده از سیستم ذخیرهساز هیدروژنی و برنامه پاسخگویی بار باعث کاهش هزینههای بهرهبرداری ریزشبکه میشوند.
Microgrid (MG) supplied its local load with distributed energy resources at the low voltage system in distribution networks. Microgrid can be used in parts that are not allowed access to the electricity network with low investment cost. The used islanding MG in this research includes wind turbine and photovoltaic systems as renewable energy sources and hydrogen storage system (HSS). This paper proposes a new energy management strategy (EMS) for MG in the presence of the HSS considering the power uncertainties of renewable energy sources. The objective of proposed EMS is to minimize the operating costs of batteries, HSS and the costs associated with excess and undelivered energy considering the supplied load constraints. The considered technical constraints in this paper contain renewable energy sources limits and battery and HSS constraints. HSS includes electrolyzer (EL), hydrogen tanks and fuel cell (FC). Demand response program (DRP) is used to flat the load curve and optimal operation of MG. The proposed model on a MG is been implemented in GAMS software. The simulation results show that the operation cost of MG reduced by using of HSS and DRP.
[1] T. Hak, B. Moldan, andA. L. Dahl, Sustainability Indicators: A Scientific Assessment, Chapter 18, Island Press,S ept. 2012.
[2] S. Wang, Z. Li, L. Wu, M. Shahidehpour, and Z. Li, "New metrics for assessing the reliability and economics of microgrids in distribution system," IEEE Trans. on Power Systems, vol. 28, no. 3, pp. 2852-2861, Aug. 2013.
[3] P. S. Georgilakis and N. D. Hatziargyriou, "Optimal distributed generation placement in power distribution networks: models, methods, and future research," IEEE Trans. on Power Systems, vol. 28, no. 3, pp. 3420-3428, Aug. 2013.
[4] A. K. Basu, S. Chowdhury, and S. P. Chowdhury, "Impact of strategic deployment of CHP-based DERs on microgrid reliability," IEEE Trans. on Power Delivery, vol. 25, no. 3, pp. 1697-1705, Jul. 2010.
[5] T. Logenthiran, D. Srinivasan, and A. M. Khambadkone, "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, Jan. 2011.
[6] F. Ren, M. Zhang, and D. Sutanto, "A multi-agent solution to distribution system management by considering distributed generators," IEEE Trans. on Power Systems, vol. 28, no. 2, pp. 1442-1451, May 2013.
[7] R. H. Lasseter and P. Paigi, "Microgrid: a conceptual solution," in Proc. IEEE pf 35th Annual Power Electronics Specialists Conf., PESC 04, vol. 6, pp. 4285-4290, Jun. 2004.
[8] R. H. Lasseter and P. Piagi, "Extended microgrid using (DER) distributed energy resources," in Proc. IEEE Power Engineering Society General Meeting, 5 pp., Jun. 2007.
[9] R. H. Lasseter, "Microgrids," in Proc. IEEE Power Engineering Society Winter Meeting, , vol. 1, pp. 305-308, Jan. 2002.
[10] C. Marnay and G. Venkataramanan, "Microgrids in the evolving electricity generation and delivery infrastructure," in Proc. of IEEE Power Engineering Society General Meeting, , 5 pp., Oct. 2006.
[11] J. Lopes, C. L. Moreira, and A. G. Madureira, "Defining control strategies for microgrids islanded operation," IEEE Trans. on Power Systems, vol. 21, no. 2, pp. 916-924, May 2006.
[12] J. Lopes, C. L. Moreira, and A. G. Madureira, "Defining control strategies for microgrids islanded operation," IEEE Trans. on Power Systems, vol. 21, no. 2, pp. 916-924, May 2006.
[13] Y. Uno, et al., "Evaluation of micro-grid supply and demand stability for different interconnections," in Proc. IEEE Int. Power and Energy Conf., PECon'06, , pp. 612-617, Nov. 2006.
[14] A. Yilanci, I. Dincer, and H. K. Ozturk, "A review on solar-hydrogen/fuel cell hybrid energy systems for stationary applications," Progress in Energy and Combustion Science, vol. 35, no. 3, pp. 231-244, Jun. 2009.
[15] E. I. Zoulias, et al., "Integration of hydrogen energy technologies in stand-alone power systems analysis of the current potential for applications," Renewable and Sustainable Energy Reviews, vol. 10, no. 5, pp. 432-462, Oct. 2006.
[16] P. P. Edwards, V. L. Kuznetsov, W. I. F. David, and N. P. Brandon, "Hydrogen and fuel cells: towards a sustainable energy future," Energy Policy, vol. 36, no. 12, pp. 4356-4362, Dec. 2008.
[17] O. Ulleberg, "The importance of control strategies in PV-hydrogen systems," Solar Energy, vol. 76, no. 1, pp. 323-329, Mar. 2004.
[18] H. A. Aalami, M. Parsa Moghaddam, and G. R. Yousefi, "Modeling and prioritizing demand response programs in power markets," Electric Power Systems Research, vol. 80, no. 4, pp. 426-435, Apr. 2010.
[19] H. Aalami, M. Parsa Moghadam, and G. R. Yousefi, "Optimum time of use program proposal for Iranian power systems," in Proc. of Int. Conf. on Electric Power and Energy Conversion Systems, EPECS'09, 6 pp., Nov. 2009.
[20] S. Nojavan, H. Qesmati, K. Zare, and H. Seyyedi, "Large consumer electricity acquisition considering time-of-use rates demand response programs," Arabian J. for Science and Engineering, vol. 39, no. 12, pp. 8913-8923, Dec. 2014.
[21] R. Dufo-Lopez, J. L. Bernal-Agustin, and J. Contreras, "Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage," Renewable Energy, vol. 32, no. 7, pp. 1102-1126, Jun. 2007.
[22] The GAMS Software Website, 2015, http://www.gams.com/dd/docs/solvers/dicopt.pdf.
[23] A. Brooke, D. Kendrick, A. Meeraus, and R. Raman, GAMS: A User's Guide, Washington, DC: GAMS Development Corporation, 2008, http://www.gams.com/dd/docs/bigdocs/GAMSUsersGuide.pdf.
[24] G. Cau, D. Cocco, M. Petrollese, S. K. Kar, and C. Milan, "Energy management strategy based on short-term generation scheduling for a renewable microgrid using a hydrogen storage system," Energy Conversion and Management, vol. 87, pp. 820-831, Nov. 2014.
[25] N. D. Tung and L. B. Le, "Optimal bidding strategy for microgrids considering renewable energy and building thermal dynamics," Smart Grid, IEEE Trans. on, vol. 5, no. 4, pp. 1608-1620, Jul. 2014.
[26] H. A. Aalami and S. Nojavan, "Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation," IET Generation, Transmission, and Distribution, vol. 10, no. 1, pp. 107-114, Jan. 2016.
[27] S. Nojavan and H. A. Aalami, "Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program," Energy Conversion and Management, vol. 103, pp. 1008-1018, Oct. 2015.