پیک‌سایی مشترکان صنعتی از طریق نصب ترکیبی نیروگاه خورشیدی و ذخیره‌ساز انرژی

محورهای موضوعی : مهندسی برق قدرت

مسلم فرهنگ نیا ¹ (دانشکده مهندسی برق، واحد نجف‌آباد، دانشگاه آزاد اسلامی، نجف‌آباد، ایران|مرکز تحقیقات ریزشبکه‌های هوشمند، واحد نجف‌آباد، دانشگاه آزاد اسلامی، نجف‌آباد، ایران)
فریبرز حقیقت دار فشارکی ² (دانشکده مهندسی برق، واحد نجف‌آباد، دانشگاه آزاد اسلامی، نجف‌آباد، ایران|مرکز تحقیقات ریزشبکه‌های هوشمند، واحد نجف‌آباد، دانشگاه آزاد اسلامی، نجف‌آباد، ایران)

تاریخ دریافت : 1402/08/06 تاریخ پذیرش : 1402/11/08 تاریخ انتشار : 1403/06/30

کلید واژه: نیروگاه خورشیدی, مشترک صنعتی, پیک‌سایی, ذخیره ساز باتری,

چکیده مقاله :

امروزه، افزایش هزینه انرژی الکتریکی به خصوص در زمان اوج بار در کنار مشکلات زیست محیطی ناشی از سوخت های فسیلی، مسئله پیک سایی به ‎کمک انرژی‎های پاک و تجدیدپذیر را در صنعت برق به امری مهم و حیاتی تبدل کرده است. از این‎رو در این مقاله از ترکیب نیروگاه خورشیدی و ذخیره ساز از نوع باتری برای حل مسئله پیک‎سایی استفاده شده است. در این راستا، یک فرمول‎بندی جدید جهت تعیین ظرفیت بهینه نیروگاه خورشیدی و ذخیره ساز باتری پیشنهاد شده است. در قیود مدنظر قرار گرفته برای فرمول‎بندی مزبور، مباحث فنی و مسائل اقتصادی با هم به نحو مناسبی ترکیب شده‌اند. علاوه بر آن حل مسئله بهینه با توجه به پروفیل بار مصرفی و هزینه ساعتی انرژی الکتریکی برای مشترک مورد مطالعه و همچنین با در نظر گرفتن نرخ تورم و هزینه انرژی الکتریکی در سال های پیش‎رو انجام شده است. پس از آن جواب حاصل از دیدگاه توجیه پذیری اقتصادی و تعاملی که با شبکه توزیع انرژی الکتریکی بالادست خواهد داشت، مورد ارزیابی قرار گرفته است. نکته قابل تامل دیگر آن‎که، در این مقاله از داده های حقیقی در یک شبکه واقعی به منظور شبیه سازی ها استفاده شده است. نتایج شبیه سازی، عملکرد مناسب و کارآیی روش پیشنهادی را تایید می نماید.

چکیده انگلیسی:

Nowadays, increasing the cost of electrical energy, especially at the peak load duration, besides the environmental caused by fossil fuels, have made the peak shaving problem by clean and renewable energies, one of the important as well as essential subjects in electric power industry. Hence, in this paper, combination of the photovoltaic power plant and the battery storage system is used to solve the peak shaving problem. In doing so, a new formulation is proposed for determining the optimal capacity of the photovoltaic power plant as well as battery storage. In the considered constraints in the mentioned formulation, technical issues and economic problems are combined together in an appropriate manner. Moreover, solving the optimization problem is performed regarding the consumption load profile as well as the hourly cost of the electrical energy of under-consideration costumer, and also the expected value of the inflation and the electrical energy cost in the future years. After that, the obtained solution is evaluated in terms of the economic feasibility and its interaction with the upstream electric power distribution network. Another considerable point in this paper is the use of the real data in an actual network for simulations. The simulation results, confirm the convenient performance as well as good efficiency of the proposed method.

منابع و مأخذ:

1. IRENA, Renewable Capacity Statistiques. 2023. [Online]. Available: www. irena.org


2. L. K. A. Halae, and M. M. Rezaei, “Optimum design of solar power plant in off-grid mode in order to reduce construction costs and the amount of unsupplied load by ALPSO algorithm,” Technovations in Electrical Engineering and Green Energy System, vol. 2, no. 1, pp. 96-116, June 2023, doi: 10.30486/teeges.2023.1972393.1049.


3. [Online] Available: https://www.farsnews.ir/news/14010129000915/


4. A. Kaabeche, and R. Ibtiouen, “Techno-economic optimization of hybrid photovoltaic/wind/diesel/battery generation in a stand-alone power system,” Solar Energy, vol. 103, pp. 171-182, May 2014, doi: 10.1016/j.solener.2014.02.017.


5. F. Braam, R. Hollinger, M. L. Engesser, S. Muller, R. Kohrs, and C. Wittwer, “Peak shaving with photovoltaic-battery systems,” in IEEE PES Innovative Smart Grid Technologies, Europe, 2014, pp. 1-5, doi: 10.1109/ISGTEurope.2014.7028748.


6. R. Luthander, J. Widén, J. Munkhammar, and D. Lingfors, “Self-consumption enhancement and peak shaving of residential photovoltaics using storage and curtailment,” Energy, vol. 112, pp. 221-231, Oct. 2016, doi: 10.1016/j.energy.2016.06.039.


7. N. Boyouk, N. Munzke, and M. Hiller, “Peak shaving of a grid connected-photovoltaic battery system at Helmholtz Institute Ulm (HIU),” in 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2018, pp. 1-5, doi: 10.1109/ISGTEurope.2018.8571616.


8. D. Dongol, T. Feldmann, M. Schmidt, and E. Bollin, “A model predictive control based peak shaving application of battery for a household with photovoltaic system in a rural distribution grid,” Sustainable Energy, Grids Networks, vol. 16, pp. 1-13, Dec. 2018, doi: 10.1016/j.segan.2018.05.001.


9. S. M. S. Danish, M. Ahmadi, M. S. S. Danish, P. Mandal, A. Yona, and T. Senjyu, “A coherent strategy for peak load shaving using energy storage systems,” Journal of Energy Storage, vol. 32, pp. 1-11, Dec. 2020, doi: 10.1016/j.est.2020.101823.


10. R. Manojkumar, C. Kumar, S. Ganguly, and J. P. S. Catalao, “Optimal peak shaving control using dynamic demand and feed-in limits for grid-connected PV sources with batteries,” IEEE System Journal, vol. 15, no. 4, pp. 5560-5570, Dec. 2021, doi: 10.1109/JSYST.2020.3045020.


11. E. W. Schaefer, G. Hoogsteen, J. L. Hurink, and R. P. van Leeuwen, “Sizing of hybrid energy storage through analysis of load profile characteristics: A household case study,” Journal of Energy Storage, vol. 52, pp. 1-19, Aug. 2022, doi: 10.1016/j.est.2022.104768.


12. Y. Guo, and Y. Xiang, “Cost–benefit analysis of photovoltaic-storage investment in integrated energy systems,” Energy Reports, vol. 8, pp. 66–71, Aug. 2022, doi: 10.1016/j.egyr.2022.02.158.


13. S. Rajamand, M. Shafie-khah, and P. S. Catal, “Energy storage systems implementation and photovoltaic output prediction for cost minimization of a Microgrid,” Electric Power System Research, vol. 202, pp. 1-15, Jan. 2021, doi: 10.1016/j.epsr.2021.107596.


14. Z. Song, X. Guan, and M. Cheng, “Multi-objective optimization strategy for home energy management system including PV and battery energy storage,” Energy Reports, vol. 8, pp. 5396-5411, Nov. 2022, doi: 10.1016/j.egyr.2022.04.023.


15. Y. He, H. Zhang, Y. You, J. Tao, H. Sheng, and Q. Zhu, “Research on hybrid configuration of photovoltaic and storage distribution network considering the power demand of important loads,”in 2022 5th International Conference on Energy, Electrical and Power Engineering (CEEPE), pp. 542-551, 2022, doi: 10.1109/CEEPE55110.2022.9783402.


16. G. Xu, C. Shang, S. Fan, X. Zhang, and H. Cheng, “Sizing battery energy storage systems for industrial customers with photovoltaic power,” Energy Procedia, vol. 158, pp. 4953-4958, Feb. 2019, doi: 10.1016/j.egypro.2019.01.693.


17. L. C. Yong, “Peak shaving mechanism employing a battery storage system (BSS) and solar forecasting,” ECTI Transactions on Electric Engineering Electronics and Communications, vol. 21, no.2, pp. 1-10, June 2023, doi: 10.37936/ecti-eec.2023212.249826.


18. R. Khezri, A. Mahmoudi, and M. H. Haque, “Optimal capacity of solar PV and battery storage for Australian grid-connected households,” IEEE Transactions on Industry Applications, vol. 56, no. 5, pp. 5319-5329, May 2020, doi: 10.1109/TIA.2020.2998668.


19. A. Abbasi, H. A. Khalid, H. Rehman, and A. U. Khan, “A novel dynamic load scheduling and peak shaving control scheme in community home energy management system based microgrids,” IEEE Access, vol. 11, pp. 32508–32522, March 2023, doi: 10.1109/ACCESS.2023.3255542.


20. Grid Energy Storage Report, [Online] Available: http://energy.gov/sites/prod/files/2014/09/f18/Grid Energy Storage December 2013.pdf


21. M. Uddin, M.F. Romlie, M. F. Abdullah, C. Tan, G. M. Sha, and A. H. A. Bakar, “A novel peak shaving algorithm for islanded microgrid using battery energy storage system,” Energy, vol. 196, pp. 1-13, April 2020, doi: 10.1016/j.energy.2020.117084.


22. S. Wei, S. Xu, A. Agrawral, S. Choudhury, Y. Lu, Z. Tu, L. Ma, and L. A. Archer, “A stable room-temperature sodium-sulfur battery,” Nature Communication, vol. 7, pp. 1-10, June 2016, doi: 10.1038/ncomms11722.


23. R. Fu, T. Remo, and R. Margolis, “Photovoltaics-plus-energy storage system costs benchmark,” [Online] Available: https://www.nrel.gov/docs/fy19osti/72401.pdf


24. T. K. Mukherjee, G. V. Henderson, “Capital budgeting process: theory and practice,” Interfaces, vol. 17, no. 2, April 1987, doi: 10.1287/inte.17.2.78.


25. M. M. Oskoonejad, “Basic Principles in Engineering Economics,” Engineering Economics (Economic Evaluation of Industrial Projects), Amirkabir University of Technology Publication, 1996, pp. 15-24, ISBN: 973-964-463-567-0.


26. C. Lehmann, M. Weeber, J. Böhner, and R. Steinhilper, “Techno-economical analysis of photovoltaic-battery storage systems for peak-shaving applications and self-consumption optimization in existing production plants,” Procedia CIRP, vol. 48, pp. 313-318, May 2016, doi: 10.1016/j.procir.2016.03.017.


27. K. H. Chua, Y. S. Lim, and S. Morris, “Energy storage system for peak shaving,” International Journal of Energy Sector Management, vol. 10, no. 1, pp. 3-18, Dec. 2016, doi: 10.1108/IJESM-01-2015-0003.


28. M. H. Abolhassani, and A. Safdarian, “Electric vehicles as mobile energy storage devices to alleviate network congestion,” in 2019 Smart Grid Conference (SGC), pp. 1-5, 2019, doi: 10.1109/SGC49328.2019.9056608.


29. M. Farivar, and S. H. Low, “Branch flow model : relaxations and convexi fi cation-part I,” IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 2554-2564, April 2013, doi: 10.1109/TPWRS.2013.2255317.


30. [Online] Available: https://modiremali.com/dictionary/


31. J. Alpizar-Castillo, L. Ramirez-Elizondo, and P. Bauer, “The effect of non-coordinated heating electrification alternatives on a low-voltage distribution network with high PV penetration,” in 2023 IEEE 17th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG), pp. 1-6, 2023, doi: 10.1109/CPE-POWERENG58103.2023.10227394.