مدل‌سازی خرده‌فروش در برنامه‌ریزی بهینه و تاب آور ظرفیت شبکه‌های هوشمند، با درنظرگرفتن منابع مدیریت سمت تقاضا و عدم‌قطعیت‌ها
الموضوعات :
احسان خوش کردار
1
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عبداله راستگو
2
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سعید خراطی
3
1 - دانشکده مهندسی برق- واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران
2 - دانشکده مهندسی برق- واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران
3 - دانشکده مهندسی برق- واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران
الکلمات المفتاحية: تاب‌آوری, خرده‌فروش, شبکه هوشمند, مدل‌سازی ظرفیت. ,
ملخص المقالة :
هر ساله در سراسر جهان خاموشی‌های بسیاری به دلیل فجایع طبیعی رخ می‌دهند که هزینه‌های بسیاری به منظور بازیابی شبکه تحمیل می‌کنند. از این‌رو مفهوم تاب‌آوری تعریف و تلاش‌ها برای عملکرد تاب‌آور شبکه‌های برق شدت گرفت. یکی از موارد مهم در طراحی شبکه‌های برق تاب‌آور، تامین ظرفیت مورد نیاز سیستم با در نظرگرفتن موضوع تاب‌آوری است که مدنظر این مقاله است. از آنجا که با توجه به دلایل اقتصادی حضور بیشتر ارائه دهندگان ظرفیت سبب ایجاد رقابت و بهبود کارایی بازار می‌شود، باید از منابع مدیریت سمت مصرف نیز در بازار ظرفیت استفاده شود. با توجه به این‌که حضور پایدار و کارای منابع مدیریت سمت مصرف در بازار ظرفیت تنها با مشارکت شرکت‌های تامین‌کننده بار، که در این مقاله شرکت‌های خرده‌فروشی در نظر گرفته شده‌اند، امکان‌پذیر است، باید پارامترهای تاثیرگذار بر رفتار آنها و نحوه تعامل آنها با دو بخش بازار (مدیریت بازار و مشترکین) در هر دو سمت بازار مدل‌سازی شود. از این‌رو در این مقاله مدل‌سازی و ارزیابی شده است که مشارکت خرده‌فروش در بازار ظرفیت چگونه است و تا چه میزان می‌تواند بر کاهش هزینه‌های قابلیت‌اطمینان و تاب‌آوری در بازار ظرفیت موثر باشد. طبیعی است که باید سود خرده‌فروش در این تجارت نیز محاسبه شود و اطمینان حاصل شود که خرده‌فروش با کسب سود قابل قبول در این بازار حضور خواهد یافت تا شبکه نیز از حضور او بهرهمند شود. نتایج عددی نشان داده است که به‌کارگیری خرده‌فروش به عنوان نماینده منابع سمت مصرف در بازار ظرفیت سبب کاهش هزینه‌های خاموشی به اندازه 5/1 درصد معادل با صرفه جویی 297638 دلار در سال خواهد شد، این در حالی است که خرده‌فروش نیز از این تجارت به‌طور متوسط روزانه حدود 3716 دلار سود خواهد برد.
[1] M. Doostizadeh, H. Jalili, A. Babaei, "A decentralized framework to improve resilience in microgrids based on peer-to-peer transactions, considering independence and privacy”, Journal of Intelligent Procedures in Electrical Technology, vol. 15, no. 57, pp. 31-50, June 2024 (in Persian) (dor: 20.1001.1.2¬3223871¬.1403¬.15.¬57.3.2).
[2] G. Hou, K.K. Muraleetharan, V. Panchalogaranjan, P. Moses, A. Javid, H. Al-Dakheeli, R. Bulut, R. Campos, P.S. Harvey, G. Miller, K. Boldes, M. Narayanan, "Resilience assessment and enhancement evaluation of power distribution systems subjected to ice storms", Reliability Engineering and System Safety, vol. 230, Article Number: 108964, Feb. 2023 (doi: 10.1016/j.ress.2022.108964).
[3] M. Panteli, P. Mancarella, "Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies", Electric Power Systems Research, vol. 127, pp. 259-270, Oct. 2015 (doi: 10.1016/j.epsr.2015.06.012).
[4] A. Ankit, Zh. Liu, S. B. Miles, Y. Choe, "U.S. resilience to large-scale power outages in 2002-2019”, Journal of Safety Science and Resilience, vol. 3, pp. 128-135, June 2022 (doi: 10.1016/j.jnlssr.2022.02.002).
[5] Y. Yao, W. Liu, R. Jain, B. Chowdhury, J. Wang R. Cox, “Quantitative metrics for grid resilience evaluation and optimization”, IEEE Transactions on Sustainable Energy, vol. 14, pp. 1244-1258, April 2023 (doi: 10.1109/TSTE.2022.3230019).
[6] Z. M. Haider, Kh. Kh. Mehmood, M. K. Rafique, S. U. Khan, S. J. Lee, Ch. H. Kim, “Water-filling algorithm-based approach for management of responsive residential loads”, Journal of Modern Power Systems and Clean Energy, vol. 6, pp. 118-131, Jan. 2018 (doi: 10.1007/s40565-017-0340-x).
[7] M. Panteli, D. N. Trakas, P. Mancarella, N. D. Hatziargyriou, "Power systems resilience assessment: Hardening and smart operational enhancement strategies", IEEE Proceedings, vol. 105, pp. 1202-1213, July. 2017 (doi: 10.1109/JPROC.2017.2691357).
[8] H. Xie, X. Sun, Ch. Chen, Zh. Bie, J. P. S. Catalao, “Resilience metrics for integrated power and natural gas systems”, IEEE Transactions on Smart Grid, vol. 13, pp. 2483-2486, Jan. 2022.
[9] T. Cheng, Zh. Tan, H. Zhong, “Exploiting flexibility of integrated demand response to alleviate power flow violation during line tripping contingency”, Journal of Modern Power Systems and Clean Energy, Early Access, pp. 1-11, Feb. 2022 (10.35833/MPCE.2021.000535).
[10] X. Lambin, “Integration of demand response in electricity market capacity mechanisms”, Utilities Policy, vol. 64, Article Number: 101033, June 2020 (doi: 10.1016/j.jup.2020.101033).
[11] B. F. Hobbs, M. Hu, J. G. Inon, S. E. Stoft, M. P. Bhavaraju, “A dynamic analysis of a demand curve-based capacity market proposal: The PJM reliability pricing model”, IEEE Transactions on Power Systems, vol. 22, pp. 3-14, Jan. 2007 (doi: 10.1109/TPWRS.2006.887954).
[12] Y. Xiao, Q. Su, B. C. Chiu, J. Bastian, A. Angle, “Demand response modeling in PJM capacity market”, IEEE General Meeting on Power and Energy Society, pp. 1-7, Nov. 2012 (doi: 10.1109/PESGM.2012.6345733).
[13] Y. Xiao, Y. Y. Lee, F. S. Bresler, J. Bastian, A. Angle, “Integration of demand response into PJM capacity market incremental auction”, IEEE General Meeting on Power and Energy Society, pp. 1-5, Mar. 2013 (doi: 10.1109/PESGM.2013.6342514).
[14] J. Ma, B. Venkatesh, “New real-time demand response market co-optimized with conventional energy market”, IEEE Systems Journal, vol. 16, pp. 6381-6392, Jan. 2022 (doi: 10.1109/JSYST.2021.3132786).
[15] C. L. Anderson, J. B. Cardell, “A decision framework for optimal pairing of wind and demand response resources”, IEEE Systems Journal, vol. 8, pp. 1104-1111, June 2014 (doi: 10.1109/JSYST.2014.2326898).
[16] A. Roudbari, et. al., “Resilience oriented operation of smart grids by rescheduling of energy resources and electric vehicles management during extreme weather condition”, Sustainable Energy, Grids and Networks, vol. 28. Article Number: 100547, Dec. 2021 (doi: 10.1016/j.segan.2021.100547).
[17] B. Kashanizadeh, H. M. Shourkaei, M. Fotuhi-Firuzabad, “Short-term resilience-oriented enhancement in smart multiple residential energy system using local electrical storage system, demand side management and mobile generators”, Journal of Energy Storage, vol. 52, Article Number: 104825, Aug. 2022 (doi: 10.1016/j.est.2022.104825).
[18] S. Rahgozar, A. Zare, P. Siano, “A resilience-oriented planning of energy hub by considering demand response program and energy storage systems”, Journal of Energy Storage, vol. 52, Article Number: 104841, Aug. 2022 (doi: 10.1016/j.est.2022.104841).
[19] M. W. Tian, P. Talebizadehsardari, “Energy cost and efficiency analysis of building resilience against power outage by shared parking station for electric vehicles and demand response program”, Energy, vol. 215, Article Number: 119058, Jan. 2021 (doi: 10.1016/j.energy.2020.119058).
[20] A. Younesi, H. Shayeghi, P. Siano, A. Safari, “A multi-objective resilience economic stochastic scheduling method for microgrid”, International Journal of Electrical Power and Energy Systems, vol. 131, Article Number: 106974, Oct. 2021 (doi: 10.1016/j.ijepes.2021.106974).
[21] A. Younesi, H. Shayeghi, A. Safari, P. Siano, “Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation”, Energy, vol. 207, Article Number: 118220, Sep. 2020 (doi: 10.1016/j.energy.2020.118220).
[22] A. Shakeri Kahnamouei, S. Lotfifard, “Enhancing resilience of distribution networks by coordination microgrids and demand response programs in service restoration”, IEEE Systems Journal, vol. 16, pp. 1-12, June 2021 (doi: 10.1109/JSYST.2021.3097263).
[23] S. Chanda, A. K. Srivastava, “Defining and enabling resilience of electric distribution systems with multiple microgrids”, IEEE Trans. on Smart Grid, vol. 7, pp. 2859-2868, May 2016 (doi: 10.1109/TSG.2016.2561303).
[24] H. Masrur, A. Sharifi, M. R. Islam, M. A. Hossain, T. Senjyu, “Optimal and economic operation of microgrids to leverage resilience benefits during grid outages”, International Journal of Electrical Power and Energy Systems, vol. 132, Article Number: 107137, Nov. 2021 (doi: 10.1016/j.ijepes.2021.107137).
[25] M. H. Amirioun, F. Aminifar, H. Lesani, “Resilience oriented proactive management of microgrids against windstorms”, IEEE Trans. on Power Systems, vol. 33, pp. 4275-4284, July 2018 (doi: 10.1109/TPWRS.2017.2765600).
[26] K. S. A. Sedzro, A. J. Lamadrid, L. F. Zuluaga, “Allocation of resources using a microgrid formation approach for resilient electric grids”, IEEE Trans. on Power Systems, vol. 33, pp. 2633-2643, May 2018 (doi: 10.1109/TPWRS.2017.2746622).
[27] S. Mousavizadeh, M. R. Haghifam, M. H. Shariatkhah, “A linear two stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources”, Applied Energy, vol. 211, pp. 443-460, Feb. 2018 (doi: 10.1016/j.apenergy.2017.11.067).
[28] Y. Xu, Y. Xing, Q. Huang, J. Li, G. Zhang, O. Bamisile, Q. Huang, “A review of resilience enhancement strategies in renewable power system under HILP events”, Energy Reports, vol. 9, pp. 200-209, May 2023 (doi.org/10.1016/j.egyr.2022.12.128).
[29] A. Grochowicz, K. V. Greevenbroek, F. E. Benth, M. Zeyringer, “Intersecting near-optimal spaces: European power systems with more resilience to weather variability”, Energy Economics, vol. 118, Aiticle Number: 106496, Feb. 2023 (doi.org/10.1016/j.eneco.2022.106496).
[30] F. Dehghani, M. Mohammadi, M. Karimi, “Age-dependent resilience assessment and quantification of distribution systems under extreme weather events”, International Journal of Electrical Power and Energy Systems, vol. 150, Article Number: 109089, Aug. 2023 (doi.org/10.1016/j.ijepes.2023.109089).
[31] H. G. Kwag, J. Kim, “Optimal combined scheduling of generation and demand response with demand resource constraints”, Applied Energy, vol. 96, pp. 161-170, Aug. 2012 (doi: 10.1016/j.apenergy.2011.12.075).
[32] A. Ghaderi, M. Parsa Moghaddam, M. K. Sheikh-El Eslami, “Energy efficiency resource modeling in generation expansion planning”, Energy, vol. 68, pp. 529-537, April 2014 (doi: 10.1016/j.energy.2014.02.028).
[33] M. Hekkenberg, R. M. J. Benders, H. C. Moll, A. J. M. Schoot Uiterkamp, “Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands”, Energy Policy, vol. 37, pp. 1542-1551, April 2009 (doi: 10.1016/j.enpol.2008.12.030).
[34] H. Jalili, M.K. Sheikh-El-Eslami, M.P. Moghaddam, P. Siano, "Modeling of retailer’s behavior for participation in the capacity market", International Transactions on Electrical Energy Systems, vol. 29, pp. 1-29, June 2019 (doi: 10.1002/2050-7038.12056).
[35] Y. Ding, P. Wang, "Reliability and price risk assessment of a restructured power system with hybrid market structure”, IEEE Transactions on Power Systems, vol. 21, no. 1, pp. 108-116, Feb. 2006 (doi: 10.1109/TPWRS.20¬05.8¬57835).
[36] R. Nesaei Kalati, M. K. Sheikh-El-Eslami, “Determination of DSM strategy to participate in the capacity market (in Persian)”, M. S. Thesis, Tarbiat Modares University, 2015.
[37] A. Abdollahi, M. Parsa Moghaddam, M. Rashidinejad, M. K. Sheikh-El-Eslami, “Investigation of economic and environmental-driven demand response measures incorporating UC”, IEEE Transactions on Smart Grid, vol. 3, pp. 12-25, Dec. 2012 (doi: 10.1109/TSG.2011.2172996).
[38] A. Askarizadeh, E. Mashhour, M. Saniei, "A multi-objective optimization model based on genetic algorithm for voltage management of radial distribution networks in tropical areas of south of Iran using a combination of fixed capacitors and voltage regulators", Journal of Intelligent Procedures in Electrical Technology, vol. 15, no. 60, pp. 171-194, March 2025 (in Persian).
[39] M. Karimi, M. Ehasan, F. Faghihi, "Coordination of protection equipment in synchronous generator-based microgrids with regards to maintaining first swing stability", Journal of Intelligent Procedures in Electrical Technology, vol. 14, no. 54, pp. 91-108, June 2023 (in Persian) (dor: 20.1001.1.23223871.1402.14.54.6.2).
[40] P. Wang, Y. Xiao, Y. Ding, “Nodal Market Power Assessment in Electricity Markets”, IEEE Trans. on Power Systems, vol. 19, pp. 1373-1379, Aug. 2004 (doi: 10.1109/TPWRS.2004.831695).
