بررسی حضور سیستم‌های ذخیره‌ساز انرژی روی تاب‌آوری، قابلیت اطمینان و عملکرد اقتصادی ریزشبکه‌ها

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی برق، واحد علوم تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

چکیده

سیستمهای ذخیره ساز انرژی (ESS) می‌توانند در ریزشبکه‌ها نصب شوند و تأمین بار و رزرو را بر عهده بگیرند.این سیستمها کاربردهای گسترده‌ای را به شبکه قدرت مانند کاهش مشکلات نوسان و قطعی منابع انرژی تجدیدپذیر،تبعیت از بار،پایداری ولتاژ و فرکانس،مدیریت بار پیک و بهبود کیفیت توان سیستم ارایه می‌کنند.همچنین به عنوان منابع تولیدی در برنامه‌ریزی روزانه،سود زیادی از تبادل انرژی ریزشبکه با شبکه اصلی بدست می‌آید.با توجه به هزینه‌های سرمایه گذاری بالای ESS،در این مقاله برای توجیه اقتصادی و جلوگیری از بهره‌برداری کم یا بیش از حد آن،مدلی دقیق برای تعیین اندازه بهینه‌ای ذخیره‌ساز ارائه شده است.برای لحـاظ عدم قطعیتهای سیستم فوتوولتائیک،توربین بادی و بارهای الکتریکی،از شبیه‌سازی مونت کارلو برای تولید سناریوها و الگوریتم K-means برای کاهش آنها استفاده شده است.از طرفی جهت یافتن راهکاری برای کاهش آسیب‌پذیری شبکه و بهبود عملکرد فنی و اقتصادی آن،توجه به قابلیت اطمینان و تاب‌آوری بسیار حائز اهمیت است.ESSها موجب مدیریت بهتر انرژی در ساعات پیک بار و زمان وقوع اغتشاش می‌گردند.مدل ارائه شده در این مقاله،نقش ESS در سیستمهای انرژی جهت کاهش هزینه بهره‌برداری،بهبود تاب‌آوری و قابلیت اطمینان شبکه را بررسی می‌کند.معیار تاب‌آوری که برای کاهش اثرات وقوع حوادث شدید روی شبکه است به عنوان یک ترم از تابع هدف در نظرگرفته می‌شود.شاخص قابلیت اطمینان سیستم که برای اطمینان از عملکرد مطمئن شبکه در برابر خطاهای کوچک و خرابیهای زودگذر می‌باشد به عنوان یک قید در مسئله مطرح شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Examining the Role of Energy Storage Systems on the Resilience, Reliability and Economic Performance of Microgrids

نویسندگان [English]

  • Shaghayegh Nayebi
  • Seyed Ebrahim Afjei
Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
چکیده [English]

Energy storage systems (ESSs) can be installed in microgrids and used for reserving and feeding loads. These systems provide a wide range of applications to the power grid, such as reducing the problems of fluctuating and outages of renewable energy sources, load compliance, voltage and frequency stability, peak load management and improving power quality. Also, as production resources in daily planning, a lot of profit is obtained from the energy exchange of the microgrid with the main grid. Considering the high investment costs of ESS, in this article, to justify the economy and prevent its under- or over-utilization, a precise model is presented to determine the optimal size of the storage device. Moreover, to consider the uncertainties of the photovoltaic system, wind turbine, and electric loads, Monte Carlo simulation has been used to generate scenarios and the K-means algorithm to reduce them. However, in order to find a solution to reduce the grid vulnerability and improve its technical and economic performance, it is crucial to pay attention to reliability and resilience. ESSs lead to better energy management during peak hours and when disturbances occur. The model presented in this article examines the role of ESS in energy systems to reduce operating costs, and improve network resilience and reliability. Resilience measure that is used to reduce the effects of severe incidents on the network is considered as a term of the objective function. The system reliability index, which is to ensure the reliable operation of the network against small errors and short-term failures, is proposed as a constraint in the model. An accurate and practical ESS model improves the performance of the system in terms of economy and security, and the simulation results show the efficiency of the presented model.

کلیدواژه‌ها [English]

  • Microgrid
  • Energy storage system
  • Energy management
  • Resilience
  • Reliability
[1] S. Bahramirad, W. Reder, and A. Khodaei. "Reliability-constrained optimal sizing of energy storage system in a microgrid." IEEE Transactions on Smart Grid 3, no. 4 (2012): 2056-2062.
[2] K. Jalilpoor, R. Khezri, A. Mahmoudi, and A. Oshnoei. "Optimal sizing of energy storage system." 2019.
[3] S. Saha, M.I. Saleem, and T.K. Roy. "Impact of high penetration of renewable energy sources on grid frequency behaviour." International Journal of Electrical Power & Energy Systems 145 (2023): 108701.
[4] X. Liu, T. Zhao, H. Deng, P. Wang, J. Liu, and F. Blaabjerg. "Microgrid energy management with energy storage systems: A review." CSEE Journal of Power and Energy Systems 9, no. 2 (2022): 483-504.
[5] H. Tian, K. Wang, X. Cui, Z. Chen, E. Zhao, and S. Saeedi. "Multi-objective planning of microgrid based on renewable energy sources and energy storage system." Journal of Energy Storage 68 (2023): 107803.
[6] M.A. Jirdehi, V. Sohrabi Tabar, S. Ghassemzadeh, and S. Tohidi. "Different aspects of microgrid management: A comprehensive review." Journal of Energy Storage 30 (2020): 101457.
[7] S.S.K.R. Vaka, and S.K. Matam. "Optimal sizing of hybrid renewable energy systems for reliability enhancement and cost minimization using multiobjective technique in microgrids." Energy Storage 5, no. 4 (2023): e419.
[8] N. Kumar, S. Dahiya, and K.P. Singh Parmar. "Multi-objective economic emission dispatch optimization strategy considering battery energy storage system in islanded microgrid." Journal of Operation and Automation in Power Engineering 12, no. 4 (2024): 296-311.
[9] A. Bhatt, and W. Ongsakul. "Optimal techno-economic feasibility study of net-zero carbon emission microgrid integrating second-life battery energy storage system." Energy Conversion And Management 266 (2022): 115825.
[10] I. Alsaidan, A. Khodaei, and W. Gao. "A comprehensive battery energy storage optimal sizing model for microgrid applications." IEEE Transactions on Power Systems 33, no. 4 (2017): 3968-3980.
[11] P.N.D. Premadasa, and D.P. Chandima. "An innovative approach of optimizing size and cost of hybrid energy storage system with state of charge regulation for stand-alone direct current microgrids." Journal of Energy Storage 32 (2020): 101703.
[12] A. Alamri, M. Alowaifeer, and A.P.S. Meliopoulos. "Energy storage sizing and probabilistic reliability assessment for power systems based on composite demand." IEEE Transactions on Power Systems 37, no. 1 (2021): 106-117.
[13] H. Masrur, M.M. Gamil, M.R. Islam, K.M. Muttaqi, M.H. Lipu, and T. Senjyu. "An optimized and outage-resilient energy management framework for multicarrier energy microgrids integrating demand response." IEEE Transactions on Industry Applications 58, no. 3 (2022): 4171-4180.
[14] L. Xu, K. Feng, N. Lin, A.T.D. Perera, H. Vincent Poor, L. Xie, C. Ji, X. Andy Sun, Qinglai Guo, and M. O’Malley. "Resilience of renewable power systems under climate risks." Nature Reviews Electrical Engineering 1, no. 1 (2024): 53-66.
[15] A.M. Amani, and M. Jalili. "Power grids as complex networks: Resilience and reliability analysis." Ieee Access 9 (2021): 119010-119031.
[16] E. Hossain, S. Roy, N. Mohammad, N. Nawar, and D.R. Dipta. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters." Applied Energy 290 (2021): 116709.
[17] M.T. Ameli, K. Jalilpoor, M.M. Amiri, and S. Azad. "Reliability analysis and role of energy storage in resiliency of energy systems." In Energy Storage in Energy Markets, pp. 399-416. Academic Press, 2021.
[18] M.S. Khomami, K. Jalilpoor, M. Tourandaz Kenari, and M.S. Sepasian. "Bi‐level network reconfiguration model to improve the resilience of distribution systems against extreme weather events." IET Generation, Transmission & Distribution 13, no. 15 (2019): 3302-3310.
[19] Y. Guo, C. Guo, and J. Yang. "A resilience-oriented restoration model against attacks on cyber-physical power systems." CSEE Journal of Power and Energy Systems (2024).
[20] K. Jalilpoor, A. Oshnoei, B. Mohammadi-Ivatloo, and A. Anvari-Moghaddam. "Network hardening and optimal placement of microgrids to improve transmission system resilience: A two-stage linear program." Reliability Engineering & System Safety 224 (2022): 108536.
[21] S. Choudhury. "Review of energy storage system technologies integration to microgrid: Types, control strategies, issues, and future prospects." Journal of Energy Storage 48 (2022): 103966.
[22] M.H. Elkholy, T. Senjyu, H. Metwally, M.A. Farahat, A.S. Irshad, A.M. Hemeida, and M.E. Lotfy. "A resilient and intelligent multi-objective energy management for a hydrogen-battery hybrid energy storage system based on MFO technique." Renewable Energy 222 (2024): 119768.
[23] S.S. Fazlhashemi, M. Sedighizadeh, and M.E. Khodayar. "Day-ahead energy management and feeder reconfiguration for microgrids with CCHP and energy storage systems." Journal of Energy Storage 29 (2020): 101301.
[24] M. Sedighizadeh, S.S. Fazlhashemi, H. Javadi, and M. Taghvaei. "Multi-objective day-ahead energy management of a microgrid considering responsive loads and uncertainty of the electric vehicles." Journal of Cleaner Production 267 (2020): 121562.
[25] K. Jalilpoor, S. Nikkhah, M.S. Sepasian, and M. Ghobadi Aliabadi. "Application of precautionary and corrective energy management strategies in improving networked microgrids resilience: A two-stage linear programming." Electric Power Systems Research 204 (2022): 107704.
[26] S. Bahramirad, and E. Camm. "Practical modeling of Smart Grid SMS™ storage management system in a microgrid." In PES T&D 2012, pp. 1-7. IEEE, 2012.
[27] K. Jalilpoor, M.T. Ameli, S. Azad, and Z. Sayadi. "Resilient energy management incorporating energy storage system and network reconfiguration: A framework of cyber‐physical system." IET Generation, Transmission & Distribution 17, no. 8 (2023): 1734-1749.