مشارکت دو هدفه هاب‌های انرژی و شبکه‌های توزیع در بازارهای عمده و خرده‌فروشی انرژی مبنی بر تصمیم‌گیری فازی

روش‌های هوشمند در صنعت برق

مقاله 5، دوره 15، شماره 58، شهریور 1403، صفحه 67-84   

نوع مقاله: مقاله پژوهشی

نویسندگان

امید کهنسال؛ محمود زاده باقری^* ؛ محمدجواد کیانی؛ صمد نجاتیان

دانشکده فنی و مهندسی- واحد یاسوج، دانشگاه آزاد اسلامی، یاسوج، ایران

چکیده

این مقاله مشارکت بهینه هم‌زمان شبکه­های انرژی وهاب‌های انرژی در بازارهای انرژی روز- بعد در دو طرح عمده‌فروشی و خرده­فروشی را ارائه می­دهد. طرح پیشنهادی در قالب بهینه­سازی دو هدفه بیان می­شود. در یک تابع هدف کمینه­سازی هزینه انرژی شبکه­های الکتریکی، گازی و حرارتی به­صورت شرکت­های توزیع خصوصی در بازارهای یادشده مدنظر است. در تابع هدف دیگر، کمینه­سازی هزینه انرژی (برابر با ما تفاوت خرید و فروش انرژی) هاب­ها در بازار خرده­فروشی به‌عنوان تابع هدف منظور می­شود. این طرح مقید به معادلات پخش توان بهینه شبکه­های مذکور و مدل بهره­برداری منابع و بارهای اکتیو در قالب هاب انرژی است. سپس بهینه­سازی پارتو مبنی بر روش توابع وزن­دار بر پایه تصمیم­گیری فازی یک راه­حل مصالحه بهینه استخراج می­کند. درنهایت با اجرای طرح پیشنهادی بر روی سیستم تست نمونه، نتایج عددی به‌دست‌آمده تأییدکننده قابلیت طرح پیشنهادی در بهبود وضعیت اقتصادی هاب­های انرژی و بهبود هم‌زمان شرایط اقتصادی و بهره­برداری شبکه­های بیان‌شده است.

کلیدواژه‌ها

بازار انرژی روز- بعد؛ بازار عمده‌فروشی و خرده‌فروشی؛ بهینه‌سازی دو هدفه؛ تصمیم‌گیری فازی؛ شرکت توزیع خصوصی؛ هاب انرژی متصل به شبکه

مراجع

[1] F. Khalafian, “Robust planning of the islanded hybrid system including renewable and non-renewable sources and stationary and mobile storages”, Journal of Intelligent Procedures in Electrical Technology, vol. 14, no. 53, pp. 15-32, Sept. 2022 (in Persian) (dor: 20.1001.1.23223871.1402.14.53.2.6).

[2] O. Kohansal, M. Zadehbagheri, M.J. Kiani, S. Nejatian, “Participation of grid-connected energy hubs and energy distribution companies in the day-ahead energy wholesale and retail markets constrained to network operation indices”, International Trans. on Electrical Energy Systems, vol. 2022, Article Number: 2463003, Aug. 2022 (doi: 10.1155/2022/2463003).

[3] M. Kazemi, T. Niknam, B. Bahmani-Firouzi, M. Nafar, “Coordinated energy management strategy in scheme of flexible grid-connected hubs participating in energy and reserve markets”, Journal of Intelligent and Fuzzy Systems, vol. 41, no. 2, pp. 4005-4020, May 2021 (doi: 10.3233/JIFS-201284).

[4] M. Enayati, G. Derakhshan, S.M. Hakimi, “Optimal energy scheduling of storage-based residential energy hub considering smart participation of demand side”, Journal of Energy Storage, vol. 49, Article Paper: 104062, May 2022 (doi: 10.1016/j.est.2022.104062).

[5] Y. Zhou, M. Shahidehpour, Z. Wei, G. Sun, S. Chen, “Multistage robust look-ahead unit commitment with probabilistic forecasting in multi-carrier energy systems”, IEEE Trans. on Sustainable Energy, vol. 12, no. 1, pp. 70-82, Jan. 2021 (doi: 10.1109/TSTE.2020.2979925).

[6] H. Zafarani, S.A. Taher, M. Shahidehpour, “Robust operation of a multicarrier energy system considering EVs and CHP units”, Energy, vol. 192, Article Number: 116703, Feb. 2020 (doi: 10.1016/j.en­ergy.20­19.1­16­7­03).

[7] A. Heidari, S.S. Mortazavi, R.C. Bansal, “Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies”, Applied Energy, vol. 261, Article Number: 14393, March 2020 (doi: 10.1016/j.apenergy.2019.114393).

[8] M.H. Shams, M. Shahabi, M.M. Lakouraj, M.R. Shafie-khah, J.P.S. Catalao, “Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids”, Energy, vol. 222, Article Number: 119894, May 2021 (doi: 10.1016/j.energy.2021.119894).

[9] M. Jalilia, M. Sedighizadeha, A. SheikhiFinib, “Stochastic optimal operation of a microgrid based on energy hub including a solar-powered compressed air energy storage system and an ice storage conditioner”, Journal of Energy Storage, vol. 33, Article Number: 102089, Jan. 2021 (doi: 10.1016/j.est.2020.102089).

[10] M. Zare-Oskouei, B. Mohammadi-Ivatloo, M. Abapour, M. Shafiee, A. Anvari-Moghaddam, “Techno-economic and environmental assessment of the coordinated operation of regional grid-connected energy hubs considering high penetration of wind power”, Journal of Cleaner Production, vol. 280, Article Number: 124275, Jan. 2021 (doi: 10.1016/j.jclepro.2020.124275).

[11] J. Faraji, H. Hashemi-Dezaki, A. Ketabi, “Stochastic operation and scheduling of energy hub considering renewable energy sources uncertainty and N-1 contingency”, Sustainable Cities and Society, vol. 65, Article Number: 102578, Feb.2021 (doi:10.1016/j.scs.2020.102578).

[12] K. Afrashi, B. Bahmani-Firouzi, M. Nafar, “Multicarrier energy system management as mixed integer linear programming”, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 45, pp. 619–631, June 2021 (doi:10.1007/s40998-020-00373-x).

[13] K. Afrashi, B. Bahmani-Firouzi, M. Nafar, “IGDT-based robust optimization for multicarrier energy system management” , Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 45, pp. 155–169, March 2021(doi:10.1007/s40998-020-00356-y).

[14] A. Dini, S. Pirouzi, M.A. Norouzi, M. Lehtonen, “”, Energy, vol. 188, pp. 1-12, Grid-connected energy hubs in the coordinated multi-energy management based on day-ahead market framework Dec. 2019 (doi: 10.10­16/j.en­ergy.2019.116055).

[15] R. Li, W. Wei, S. Mei, Q. Hu and Q. Wu, “Participation of an energy hub in electricity and heat distribution markets: An MPEC approach”, IEEE Trans. on Smart Grid, vol. 10, no. 4, pp. 3641-3653, July 2019 (doi: 10.1109/TSG.2018.2833279).

[16] T. Zhao, X. Pan, S. Yao, C. Ju, L. Li, “Strategic bidding of hybrid AC/DC microgrid embedded energy hubs: A two-stage chance constrained stochastic programming approach”, IEEE Trans. on Sustainable Energy, vol. 11, no. 1, pp. 116-125, Jan. 2020 (doi: 10.1109/TSTE.2018.2884997).

[17] S. Moazeni, A.H. Miragha , B. Defourny, “A risk-averse stochastic dynamic programming approach to energy hub optimal dispatch”, IEEE Trans. on Power Systems, vol. 34, no. 3, pp. 2169-2178, May 2019 (doi: 10.11­09/TP­WRS.2018.2882549).

[18] M.R. AkbaiZadeh, T. Niknam, A. Kavousi-Fard, “Adaptive robust optimization for the energy management of the grid-connected energy hubs based on hybrid meta-heuristic algorithm”, Energy, vol. 235, Article Number: 12117, Nov. 2021 (doi:10.1016/j.energy.2021.121171).

[19] A. Dini, A.R. Hassankashi, S. Pirouzi, M. Lehtonen, B. Arandian, A.A. Baziar , “A flexible-reliable operation optimization model of the networked energy hubs with distributed generations energy storage systems and demand response”, Energy, vol. 239, Article Number: 121923, Jan. 2022 (doi: 10.1016/j.en­ergy.2­021.1­21­923).

[20] S.M.H. Zanjani, H. Shahinzadeh, Z. Pourmirza, E. Kabalci, S.M. Muyeen, M. Benbouzid, “Optimal operation of a residential energy hub in the presence of an electric vehicle using whale optimization algorithm”, Proceeding of the EPDC, pp. 84-89, Tehran, Iran, May 2022 (doi: 10.1109/EPDC56235.2022.9817265).

[21] M. Kafaei, D. Sedighizadeh, M. Sedighizadeh, A.R. Sheikhi Fini, “An IGDT/scenario based stochastic model for an energy hub considering hydrogen energy and electric vehicles: A case study of Qeshm Island, Iran”, International Journal of Electrical Power and Energy Systems, vol. 135, Article Number: 107477, Feb. 2022 (doi: 10.1016/j.ijepes.2021.107477).

[22] S. Wogrin, D.F. Gayme, “Optimizing storage siting, sizing and technology portfolios in transmission-constrained networks”, IEEE Trans. on Power Systems, vol. 30, no. 6, pp. 3304-3313, Nov. 2015 (doi: 10.11­09/­TPWRS.­2014.2379931).

[23] R. Homayoun, B. Bahmani-Firouzi, T. Niknam, “Multi‐objective operation of distributed generations and thermal blocks in microgrids based on energy management system“, IET Generation, Transmission and Distribution, vol. 15, no. 9, pp. 1451-1462, May 2021 (doi: 10.1049/gtd2.12112).

[24] P. Fortenbacher, A. Ulbig , G. Andersson, “Optimal placement and sizing of distributed battery storage in low voltage grids using receding horizon control strategies”, IEEE Trans. on Power Systems, vol. 33, no. 3, pp. 2383-2394, May 2018 (doi: 10.1109/TPWRS.2017.2746261).

[25] H. Kiani, K.L. Hesami, A. Azarhooshang, Pirouzi, S. Safaee, “Adaptive robust operation of the active distribution network including renewable and flexible sources”, Sustainable Energy, Grids and Networks, vol. 26, Article Number: 100476, June 2021 (doi: 10.1016/j.segan.2021.100476).

[26] S. Abrisham, L. Bagherzadeh, S. Pirouzi, M. Norouzi, “A new two-layer model for energy management in the smart distribution network containing flexi-renewable virtual power plant“, Electric Power Systems Research, vol. 194, Article Number: 107085, May 2021 (doi:10.1016/j.epsr.2021.107085).

[27] H. Hamidpour, J. Aghaei, S. Dehghan, S. Pirouzi, T. Niknam, “Integrated resource expansion planning of wind integrated power systems considering demand response programmers“, IET Renewable Power Generation, vol. 13, no. 4, pp. 519-529, Jan. 2019 (doi: 10.1049/iet-rpg.2018.5835).

[28] W. Jakob, C. Blume, “Pareto optimization or cascaded weighted sum: A comparison of concepts”, Algorithms, vol. 7, pp. 166-185, July 2014 (doi: 10.3390/a7010166).

[29] Z. Zhidong, O. Suzuki, N.H. March, “Clifford algebra approach of 3D Ising model”, Advances in Applied Clifford Algebras, vol. 29, no. 1, pp. 1-28, Dec. 2019 (doi:10.1007/s00006-018-0923-2).

[30] S.A. Mirjalili, S.M. Mirjalili, A. Lewis, “Grey wolf optimizer” , Advances in Engineering Software, vol. 69, pp. 46-61, 2014 (doi:10.1016/j.advengsoft.2013.12.007).

[31] K. Sarwagya, P.K. Nayak, S. Ranjan , “Optimal coordination of directional overcurrent relays in complex distribution networks using sine cosine algorithm”, Electric Power Systems Research, vol. 187, Article Number: 106435, Oct. 2020 (doi: 10.1016/j.epsr.2020.106435).

[32] A. Askarzadeh, “A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm (CSA)”, Computers and Structures, vol. 169, pp. 1-12, June 2016 (doi: 10.1016/j.com­pstr­uc.2016.03.001).

[33] R. Rani, D. Ramyachitra, “Krill Herd Optimization algorithm for cancer feature selection and random forest technique for classification”, Proceeding of the IEEE/ICSESS, pp. 109-113, Beijing, China, Nov. 2017 (doi: 10.1109/ICSESS.2017.8342875).