برنامه‌ریزی توسعه احتمالاتی ذخیره سازهای انرژی در شبکه انتقال با در نظر گرفتن محدودیت‌های سیکل شارژ و دشارژ و عمق دشارژ
محورهای موضوعی : مهندسی برق قدرترضا ابراهیمی ابیانه 1 , جواد علمایی 2 , سید مصطفی عابدی 3
1 - گروه مهندسی برق، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
2 - گروه مهندسی برق، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
3 - گروه مهندسی برق، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران
کلید واژه: برنامه‌ریزی احتمالاتی, توسعه ذخیره¬سازها, سیکل‌های شارژ و دشارژ,
چکیده مقاله :
با افزایش نفوذ منابع تولید تجدیدپذیر و همچنین پیشرفت تکنولوژی باتری‌ها، برنامه‌ریزی توسعه ذخیره¬سازهای با ظرفیت بالا در سیستم‌های قدرت اهمیت پیدا کرده است. در اين مقاله، به ارائه یک مدل جدید برای توسعه احتمالاتی ذخیره¬سازها در شبکههای انتقال پرداخته شده است. در روش پیشنهادی، تولید واحد بادی بر مبنای سناریو و احتمالاتی مدل شده است. در این روش، علاوه بر روابط مرسوم در فرمول‌بندی مسأله توسعه بهینه ذخیره¬سازها، به مدل‌سازی محدودیت قابلیت شارژ و دشارژ ذخیره¬سازها نیز پرداخته شده است. در مدل پیشنهادی، رابطه‌ای جدید برای تعیین قابلیت سیکل‌های شارژ و دشارژ ذخیره¬سازها، پیشنهاد شده است. همچنین رابطه بین حداکثر قابلیت سیکل‌های شارژ و دشارژ و عمق دشارژ ارائه شده و به فرمول‌بندی‌های قبل اضافه شده است. روابط غیرخطی در مدل پیشنهادی، خطی شده و به‌صورت یک مسأله خطی در آمده است. مسأله بهینه‌سازی تولیدشده توسط نرم‌افزار گمز حل شده است. به‌منظور نمایش توانایی روش پیشنهادی، این روش بر روی شبکه تست 14 شین IEEE پیاده شده که نتایج شبیه‌سازی، توانایی آن را نشان می‌دهد.
As the penetration of renewable energy resources increases, as well as advances in battery technologies, optimal expansion planning of the high-capacity batteries in power systems has become important. In this manuscript, a new model for the stochastic development of the batteries in transmission networks is presented. In the proposed method, the production of the wind unit is probabilistically modeled based on scenarios. In this method, in addition to the conventional relationships in the formulation of the problem of optimal energy storage systems expansion planning, the limitation of charging and discharging capability of storage devices has also been addressed. In the proposed model, a new relationship is proposed to determine the capability of charging and discharging cycles of storage devices. Also, the relationship between the maximum capability of charge and discharge cycles and the depth of discharge is presented and added to the previous formulations. The nonlinear relations in the proposed model are linearized and become a linear problem. The optimization problem generated by GAMs software has been solved. In order to demonstrate the capability of the proposed method, this method has been implemented on the 14-bus IEEE test network, which the simulation results show its capability.
[1] D. Akinyele and R. Rayudu “Review of energy storage technologies for sustainable power networks,”Sustainable Energy
Technologies and Assessments. Vol. 8, pp. 74–91, 2014, DOI:10.1016/j.seta.2014.07.004. [2] T. R. Ayodele and A. S. O. Ogunjuyigbe, “Mitigation of Wind Power Intermittency: Storage Technology Approach,” Renewable and Sustainable Energy Reviews, Vol. 44, pp. 447– 456, 2015
. [3] A. Zahedi, “Maximizing Solar PV Energy Penetration Using Energy Storage Technology,” Renewable and Sustainable Energy Reviews, Vol.15, NO.1, pp. 866–870,2011
. [4] S. K. Kamali, V. V. Tyagi, N. A. Rahim, N. L. Panwar, H. Mokhlis, “Emergence of Energy Storage Technologies as the Solution for Reliable Operation of Smart Power Systems: A Review,” Renewable and Sustainable Energy Reviews, Vol. 25, 2013, pp. 135– 165, doi.org/10.1016/j.rser.2013.03.056
. [5] D.O. Akinyele, and R.K. Rayudu, “Review of energy storage technologies for sustainable power networks,” Sustainable Energy Technologies and Assessments, Vol. 8, pp. 74–9, 2014
. [6] D. Rastler, “Electricity energy storage technology options. A White Paper Primer on Applications, Costs, and Benefits Energy,” Electric Power Research Institute (EPRI), Technical Update, December 2010
. [7] E. Alegria, T. Brown, E. Minear, and R. Lasseter, “CERTS microgrid demonstration with large-scale energy storage and renewable generation,” IEEE Transactions on Smart Grid, Vol. 5, NO. 2, pp. 937– 943, 2014
. [8] A. Poullikkas, “A comparative overview of large-scale battery systems for electricity storage,” Renewable and Sustainable Energy Reviews, Vol. 27, pp. 778–788, 2013
. [9] H. Doughty, H, C. Butler, P, A. Akhil, A, H. Clark, N, and D. Boyes, J, “Batteries for large-scale stationary electrical energy storage,” The Electrochemical Society Interface, Fall 2010
. [10] T. Qiu, B. Xu, Y. Wang, et al., “Stochastic Multi-Stage Co-Planning of Transmission Expansion and Energy Storage,” IEEE Transactions on Power Systems, Vol. 32, NO. 1, pp. 643–651, 2017
. [11] Y. Dvorkin, R. Fernández-Blanco, Y. Wang, et al., “Co-planning of Investments in Transmission and Merchant Energy Storage,” IEEE Transactions on Power Systems, Vol. 33, NO. 1, pp. 245–256, 2018
. [12] W. Gan, X. Ai, J. Fang, et al., “Security constrained co-planning of transmission expansion and energy storage,” Applied Energy, Vol. 239, pp.383–394, 2019
. [13] S. Mahmoudi, M. Mirhosseini Moghaddam, and B. Alizadeh, “Transmission and energy storage–expansion planning in the presence of correlated wind farms,” International Transactions Electronic Energy Systems, Vol. 29, NO. 5, pp. 1–14, 2019
. [14] Y. Zhang, Z. Yang Dong, F. Luo, Y. Zheng, K. Meng, and K. Po Wong, “Optimal allocation of battery energy storage systems in distribution networks with high wind power penetration,” IET Generation, Transmission & Distribution, Vol. 10, NO. 8, pp. 1105–1113, 2016
. [15] I. Gonzalez-RomeroSonja, S. Wogrin and T. Gomes, “Proactive transmission expansion planning with storage considerations,” Energy Strategy Reviews, Vol. 24, pp. 154–165, 2019
. [16] M. Kazemi, and M.R. Ansari, “An integrated transmission expansion planning and battery storage systems placement - A security and reliability perspective,” Electrical Power and Energy Systems, Vol. 134, 2022
. [17] C. A. Mora, O. M. Montoya, and E. R. Trujillo, “Mixed-Integer Programming Model for Transmission Network Expansion Planning with Battery Energy Storage Systems (BESS),” Energies, Vol. 13, 2020
. [18] Z. Luburic, H. Pandzic, and M. Carrion, “Transmission Expansion Planning Model Considering Battery Energy Storage, TCSC and Lines Using AC OPF,” IEEE Access, Vol. 8, pp. 203429 – 203439, 2020
. [19] M. Moradi-Sepahvand, and T. Amraee, “Integrated expansion planning of electric energy generation, transmission, and storage for handling high shares of wind and solar power generation,” Applied Energy, Vol. 298, 2021
. [20] K. R. Mallon, F. Assadian, and B. Fu, “Analysis of On-Board Photovoltaics for a Battery Electric Bus and Their Impact on Battery Lifespan,” Energies, Vol. 10, NO. 943, 2017
. [21] F. Aminifar, M. Fotuhi-Firuzabad, and M. Shahidehpour, “Unit commitment with probabilistic spinning reserve and interruptible load considerations,” IEEE Transactions on Power Systems, Vol. 24, NO. 1, pp. 388-397, 2009
. [22] E. Hajipour, Bozorg, and M. Fotuhi-Firuzabad, “Stochastic Capacity Expansion Planning of Remote Microgrids with Wind Farms and Energy Storage,” IEEE Transactions on Sustainable Energy, Vol. 6, NO. 2, 491-498, 2015
. [23] M. Hosseini-Firouz, “Optimal offering strategy considering the risk management for wind power producers in electricity market,” International Journal of Electrical Power & Energy Systems, Vol. 49, pp. 359-368, 2013
. [24] Z. Tan, L. Ju, H. Li, J. Li, and H. Zhang, “A two-stage scheduling optimization model and solution algorithm for wind power and energy storage system considering uncertainty and demand response,” International Journal of Electrical Power & Energy Systems, Vol. 63, pp. 1057– 1069, 2104
. [25] L. Huaiwei, “Power system Harmonic state estimation and observability analysis via sparsity maximization,” IEEE Trans. Power Systems, Vol. 22, NO. 1, pp. 15– 23, 2007
.
