مدیریت هم‌زمان انرژی منابع Micro-CHP و ذخیره‌سازهای انرژی در ریزشبکه‌ها با وجود بارهای پاسخگو

نویسندگان

1 دانشکده فنی مهندسی - گروه مهندسی برق - دانشگاه اصفهان

2 دانشکده فنی و مهندسی - گروه مهندسی برق - دانشگاه یاسوج

چکیده

پیاده‌سازی یک سیستم مدیریت انرژی مناسب جهت بهره‌برداری بهینه از منابع انرژی یک ریزشبکه با عدم‌قطعیت‌های موجود، از اهمیت زیادی برخوردار است. در این مقاله، یک سیستم مدیریت انرژی تصادفی با هدف کاهش هزینه و افزایش قابلیت اعتماد ریزشبکه، برای روز-پیشرو، ارائه شده‌است. سیستم مدیریت انرژی پیشنهادی، وظیفه تامین بار الکتریکی و حرارتی ریزشبکه را با هدف کاهش هزینه بهره‌برداری و افزایش قابلیت‌اعتماد برعهده دارد. در این روش از یک چهارچوب تصادفی مبتنی بر تولید سناریو جهت پوشش عدم‌قطعیت‌های موجود در بازار برق، بار الکتریکی و تولیدهای تجدیدپذیر، استفاده شده‌است. همچنین، برنامه‌های پاسخ تقاضا در قالب قراردادهای انتقال بار از سوی بهره‌بردار ریزشبکه به مصرف‌کنندگان، ارائه می‌شود. علاوه‌برآن، بهره‌برداری از ریزشبکه در دو حالت اتصال به شبکه بالادست و جزیره‌ای، مدنظر قرار می‌گیرد. با تحلیل نتایج به‌دست‌آمده از شبیه‌سازی یک ریزشبکه با سه فیدر و هفت واحد تولیدی، قابلیت روش پیشنهادی موردارزیابی قرار می‌گیرد.

کلیدواژه‌ها


عنوان مقاله [English]

Simultaneous Energy Management of Micro-CHP Units and Storage Systems in Microgrids Considering Responsive Loads

نویسندگان [English]

  • P. Firouzmakan 1
  • R. Hooshmand 1
  • A. Khodabakhshian 1
  • M. Bornapour 2
1 1- Faculty of Engineering, Department of Electrical Engineering, University of Isfahan, Isfahan, Iran
2 Faculty of Engineering, Electrical Engineering Department, Yasouj University, Yasouj, Iran
چکیده [English]

A suitable energy management system (EMS) is an essential tool for optimal operation of a Microgrid with different resources considering uncertainties. In this paper, a day-ahead stochastic EMS is proposed in order to minimize the cost operation and maximize the reliability of Microgrid. The proposed EMS should supply electrical and thermal loads of Microgrid. A stochastic framework based on scenario generation is used to response the uncertainties of electrical load, market price and renewable energy sources (RESs). Also demand response programs (DRPs) are provided based on various load shifting contracts to consumers. In addition, both islanding and grid-connected operations of Microgrid are handled. Capability of the proposed method is proved by simulation results of a 3-feeder Microgrid with 7 generation units.

کلیدواژه‌ها [English]

  • microgrid
  • renewable energy sources (RESs)
  • Micro-CHP
  • demand response (DR)
  • reliability
  • stochastic programming
[1] C. Chen, S. Duan, T. Cai, B. Liu, and G. Hu, "Smart energy management system for optimal microgrid economic operation," IET renewable power generation, vol. 5, pp. 258-267, 2011.
[2] ح. شکری، س. نجفی روادانق, "حل مسئله مشارکت بهینه واحدهای نیروگاهی در حضور منابع انرژی تجدیدپذیر," مجله مهندسی برق دانشگاه تبریز، جلد 45، شماره 1، صفحه 29-42، 1394.
[3] S. Tamalouzt, N. Benyahia, T. Rekioua, D. Rekioua, and R. Abdessemed, "Performances analysis of WT-DFIG with PV and fuel cell hybrid power sources system associated with hydrogen storage hybrid energy system," International Journal of Hydrogen Energy, vol. 41, pp. 21006-21021, 2016.
[4] R. Napoli, M. Gandiglio, A. Lanzini, and M. Santarelli, "Techno-economic analysis of PEMFC and SOFC micro-CHP fuel cell systems for the residential sector," Energy and Buildings, vol. 103, pp. 131-146, 2015.
[5] A. A. Moghaddam, A. Seifi, T. Niknam, and M. R. A. Pahlavani, "Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source," Energy, vol. 36, pp. 6490-6507, 2011.
[6] T. Niknam, F. Golestaneh, and A. Malekpour, "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, vol. 43, pp. 427-437, 2012.
[7] M. Parastegari, R.-A. Hooshmand, A. Khodabakhshian, and Z. Forghani, "Joint operation of wind farms and pump-storage units in the electricity markets: Modeling, simulation and evaluation," Simulation Modelling Practice and Theory, vol. 37, pp. 56-69, 2013.
[8] M. Bornapour and R.-A. Hooshmand, "An efficient scenario-based stochastic programming for optimal planning of combined heat, power, and hydrogen production of molten carbonate fuel cell power plants," Energy, vol. 83, pp. 734-748, 2015.
[9] T. Logenthiran, D. Srinivasan, and T. Z. Shun, "Demand side management in smart grid using heuristic optimization," IEEE transactions on smart grid, vol. 3, pp. 1244-1252, 2012.
[10] P. Yang, G. Tang, and A. Nehorai, "A game-theoretic approach for optimal time-of-use electricity pricing," IEEE Transactions on Power Systems, vol. 28, pp. 884-892, 2013.
[11] M. He, S. Murugesan, and J. Zhang, "A multi-timescale scheduling approach for stochastic reliability in smart grids with wind generation and opportunistic demand," IEEE Transactions on Smart Grid, vol. 4, pp. 521-529, 2013.
[12] M. Pantoš, "Stochastic optimal charging of electric-drive vehicles with renewable energy," Energy, vol. 36, pp. 6567-6576, 2011.
[13] J. A. Carta and S. Velázquez, "A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site," Energy, vol. 36, pp. 2671-2685, 2011.
[14] H.-G. Kwag and J.-O. Kim, "Reliability modeling of demand response considering uncertainty of customer behavior," Applied Energy, vol. 122, pp. 24-33, 2014.
[15] A. Salimbeni, M. Boi, I. Marongiu, M. Porru, and A. Damiano, "Integration of active filter and energy storage system for power quality improvement in microgrids," in Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), 2016 International Symposium on, pp. 709-714, 2016.
[16] M. Motevasel, A. R. Seifi, and T. Niknam, "Multi-objective energy management of CHP (combined heat and power)-based micro-grid," Energy, vol. 51, pp. 123-136, 2013.
[17] L. Dong, W. Cheng, H. Bao, and Y. Yang, "Probabilistic load flow analysis for power system containing wind farms," in Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific, pp. 1-4, 2010.
[18] S. Mohammadi, S. Soleymani, and B. Mozafari, "Scenario-based stochastic operation management of microgrid including wind, photovoltaic, micro-turbine, fuel cell and energy storage devices," International Journal of Electrical Power & Energy Systems, vol. 54, pp. 525-535, 2014.
[19] A. Kavousi-Fard and T. Niknam, "Multi-objective stochastic distribution feeder reconfiguration from the reliability point of view," Energy, vol. 64, pp. 342-354, 2014.
[20] M. Bornapour, R.-A. Hooshmand, A. Khodabakhshian, and M. Parastegari, "Optimal stochastic coordinated scheduling of proton exchange membrane fuel cell-combined heat and power, wind and photovoltaic units in micro grids considering hydrogen storage," Applied Energy, vol. 202, pp. 308-322, 2017.
[21] E. Farjah, M. Bornapour, T. Niknam, and B. Bahmanifirouzi, "Placement of combined heat, power and hydrogen production fuel cell power plants in a distribution network," Energies, vol. 5, pp. 790-814, 2012.
[22] D. Steen, M. Stadler, G. Cardoso, M. Groissböck, N. DeForest, and C. Marnay, "Modeling of thermal storage systems in MILP distributed energy resource models," Applied Energy, vol. 137, pp. 782-792, 2015.
[23] H. Mortaji, S. H. Ow, M. Moghavvemi, and H. A. Almurib, "Load Shedding and Smart-Direct Load Control Using Internet of Things in Smart Grid Demand Response Management," IEEE Transactions on Industry Applications, on line published, pp. 1-9, 2017.
[24] د. روشن‌دوست، ر.ا. هوشمند، ا. قلی‌پور، م. نصرت‌آبادی، "طراحی یک سیستم مدیریت انرژی برای یک ریزشبکه صنعتی مبتنی بر منابع CHP از طریق برنامه ریزی تولید و پاسخ تقاضا" مجله مهندسی برق دانشگاه تبریز، جلد 46، شماره 2، صفحه 197-209، 1395.