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عباسی, شهریار. (1404). افزایش نفوذ تولید توان بادی در سیستم های قدرت برای کمینه سازی تلفات خطوط انتقال. نشریه هنرهای کاربردی, 23(شماره ویژه 81), 77-90. doi: 10.22075/jme.2024.32138.2552
شهریار عباسی. "افزایش نفوذ تولید توان بادی در سیستم های قدرت برای کمینه سازی تلفات خطوط انتقال". نشریه هنرهای کاربردی, 23, شماره ویژه 81, 1404, 77-90. doi: 10.22075/jme.2024.32138.2552
عباسی, شهریار. (1404). 'افزایش نفوذ تولید توان بادی در سیستم های قدرت برای کمینه سازی تلفات خطوط انتقال', نشریه هنرهای کاربردی, 23(شماره ویژه 81), pp. 77-90. doi: 10.22075/jme.2024.32138.2552
عباسی, شهریار. افزایش نفوذ تولید توان بادی در سیستم های قدرت برای کمینه سازی تلفات خطوط انتقال. نشریه هنرهای کاربردی, 1404; 23(شماره ویژه 81): 77-90. doi: 10.22075/jme.2024.32138.2552

افزایش نفوذ تولید توان بادی در سیستم های قدرت برای کمینه سازی تلفات خطوط انتقال

مدل سازی در مهندسی
دوره 23، شماره ویژه 81، تیر 1404، صفحه 77-90    اصل مقاله (915.6 K)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22075/jme.2024.32138.2552
نویسنده
شهریار عباسی*
گروه مهندسی برق، دانشگاه ملی مهارت، تهران، ایران
تاریخ دریافت: 01 آبان 1402،  تاریخ بازنگری: 06 اسفند 1402،  تاریخ پذیرش: 10 شهریور 1403 
چکیده
افزایش تقاضای برق و نگرانی در مورد تغییرات آب و هوایی منجر به افزایش نفوذ تولید توان بادی به سیستم‌های قدرت شده است. با این حال، زیرساخت‌های سیستم انتقال برای چنین انتقالی تجهیز نشده‌اند. خطوط انتقال وظیفه انتقال انرژی الکتریکی از بخش تولید به مراکز بار و مصرف‌کنندگان را بر عهده دارند. در این فرآیند انتقال، خطوط انتقال متحمل تلفاتی می‌شوند که بر کیفیت توان اثر گذاشته و افزایش قیمت را نیز به دنبال دارد. بنابراین، باید چنین تلفاتی را به حداقل رساند تا کیفیت توان بهبود یافته و بهره‌وری اقتصادی نیز بهبود یابد. با افزایش نرخ نفوذ تولید توان بادی در سیستم‌های قدرت، تلفات خطوط انتقال نیز افزایش می‌یابد. برای رفع این مشکل، در این مقاله، یک طرح اقدام اصلاحی (RAS) برای افزایش نفوذ تولید توان بادی در سیستم‌های قدرت با حداقل تلفات انتقال پیشنهاد شده است. بدین منظور، روش پیشنهادی از یک مسئله بهینه‌سازی چندهدفه استفاده می‌کند که با استفاده از الگوریتم ژنتیک حل می‌گردد. برای تغییر تلفات انتقال، در مسئله بهینه‌سازی چندهدفه، تولید بهینه ژنراتورهای بادی محاسبه می‌شود. روش پیشنهادی روی سیستم 39 شینه نیوانگلند آزمایش شده و نتایج شبیه‌سازی موید کارایی آن در به حداکثر رساندن تزریق تولید توان بادی است.
کلیدواژه‌ها
تولید توان بادی؛ تلفات خطوط انتقال؛ الگوریتم ژنتیک (GA)؛ بهینه سازی چند هدفه
عنوان مقاله [English]
Increasing Wind Power Penetration in Power Systems for Minimizing Transmission Line Losses
نویسندگان [English]
Shahriar Abbasi
Department of Electrical Engineering, National University of Skills (NUS), Tehran, Iran.
چکیده [English]
Increase in electricity demand and the concern about climate change have led to an increase in penetration of wind power generation into the power systems. However, the transmission network infrastructure is not equipped for such amount of wind power generation. Transmission grids are responsible for transferring electrical energy from generation section to load centers and consumers. In this transmission process, the transmission lines suffer losses that affect the power quality and increase the energy final price. Therefore, such losses should be minimized to improve power quality and economic efficiency. Along with increase in the rate of penetration of wind power generation into power systems, the losses of transmission lines also increase. To tackle this problem, in this paper, a Remedial Action Scheme (RAS) is proposed to increase the penetration of wind power generation into power systems with minimal transmission losses. For this purpose, the proposed method uses a multi-objective optimization problem that is solved using genetic algorithm (GA). To change the transmission losses, a multi-objective optimization problem determines the optimal generation of wind power generators. The proposed method is tested on the New England 39-bus system and the simulation results confirm its efficiency in maximizing the injection of wind power generation.
کلیدواژه‌ها [English]
Wind power generation, Transmission line loss, Genetic Algorithm (GA), Multi-Objective optimization
مراجع
  1.  W. Wang, L. Liu, J. Liu, and Z. Chen. "Energy management and optimization of vehicle-to-grid systems for wind power integration." CSEE Journal of Power and Energy Systems 7, no. 1 (2020): 172-180.
  2.  S. Abbasi, and H. Abdi. "Return on investment in transmission network expansion planning considering wind generation uncertainties applying non-dominated sorting genetic algorithm." Journal of Operation and Automation in Power Engineering 6, no. 1 (2018): 89-100.
  3.  S. Abbasi, H. Abdi, S. Bruno, and M. La Scala. "Transmission network expansion planning considering load correlation using unscented transformation." International Journal of Electrical Power & Energy Systems 103 (2018): 12-20.
  4.  S. Abbasi, and H. Abdi. "Multiobjective transmission expansion planning problem based on ACOPF considering load and wind power generation uncertainties." International Transactions on Electrical Energy Systems 27, no. 6 (2017): e2312.
  5.  Y. Shu, and Y. Tang. "Analysis and recommendations for the adaptability of China's power system security and stability relevant standards." CSEE Journal of Power and Energy Systems 3, no. 4 (2017): 334-339.
  6.  S.D. Ahmed, F.S. Al-Ismail, M. Shafiullah, F.A. Al-Sulaiman, and I.M. El-Amin. "Grid integration challenges of wind energy: A review." IEEE Access 8 (2020): 10857-10878.
  7.  A. Habiburrahman, and L.D. Arya. "Comparison of transmission losses and voltage regulation of overhead and gas insulated transmission line." In 2020 IEEE International Conference on Advances and Developments in Electrical and Electronics Engineering (ICADEE), pp. 1-3. IEEE, 2020.
  8.  I. Pavičić, I. Ivanković, A. Župan, R. Rubeša, and M. Rekić. "Advanced prediction of technical losses on transmission lines in real time." In 2019 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET), pp. 1-7. IEEE, 2019.
  9.  L. Rudolf. "Software solution of technical losses of the transmission network system line." Transactions on Electrical Engineering 2, no. 4 (2013): 97-101.
  10.  A. Ombua, and H. Abba Labane. "High voltage lines: energy losses in insulators." The International Journal of Engineering and Science 6, no. 10 (2017): 10.
  11.  T. Barforoushi, and R. Heydari. "Risk-constrained transmission network expansion planning in competitive electricity markets considering expected energy not supplied and wind curtailment." Journal of Modeling Engineering 20, no. 70 (2022): 209-223.
  12.  R. Fathi, B. Tousi, and S. Galvani. "Optimal Allocation of Renewable Resources in Distribution Networks Considering Uncertainty Based on Info-Gap Decision Theory Using Improved Salp Swarn Algorithm." Journal of Modeling Engineering 20, no. 67 (2022): 207-223.
  13.  M. Tripathy, S. Mishra, L. Lei Lai, and Q.P. Zhang. "Transmission loss reduction based on FACTS and bacteria foraging algorithm." In International Conference on Parallel Problem Solving from Nature, pp. 222-231. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006.
  14.  S. Jangjit, P. Kumkratug, and P. Laohachai. "Reduction of transmission line loss by using Interline Power Flow Controllers." In ECTI-CON2010: The 2010 ECTI International Confernce on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, pp. 450-453. IEEE, 2010.
  15.  J.H. Gurney, R.J. Koessler, J.S. Mumick, F.S. Prabhakara, and G. Shen. "Loss reduction opportunities in EHV transmission systems." In 2009 IEEE Power & Energy Society General Meeting, pp. 1-7. IEEE, 2009.
  16.  A.Y. Abdelaziz, S.F. Mekhamer, M.A.L. Badr, F.M. Mohamed, and E.F. El-Saadany. "A modified particle swarm algorithm for distribution systems reconfiguration." In 2009 IEEE Power & Energy Society General Meeting, pp. 1-8. IEEE, 2009.
  17.  A.A. Esmin, G. Lambert-Torres, and A.Z. De Souza. "A hybrid particle swarm optimization applied to loss power minimization." IEEE Transactions on Power Systems 20, no. 2 (2005): 859-866.
  18.  K. Vaisakh, M. Sridhar, and K.S. Linga Murthy. "Adaptive PSO-DV algorithm for minimization of power loss and voltage instability." In 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, pp. 140-144. IEEE, 2009.
  19.  H. Tehzeeb-Ul-Hassan, R. Zafar, S.A. Mohsin, and O. Lateef. "Reduction in power transmission loss using fully informed particle swarm optimization." International Journal of Electrical Power & Energy Systems 43, no. 1 (2012): 364-368.
  20.  R. Bacher, and H. Glavitsch. "Loss reduction by network switching." IEEE Transactions on Power Systems 3, no. 2 (1988): 447-454.
  21.  https://icseg.iti.illinois.edu/ieee-39-bus-system/
  22.  R. Liu, A.K. Srivastava, D.E. Bakken, A. Askerman, and P. Panciatici. "Decentralized state estimation and remedial control action for minimum wind curtailment using distributed computing platform." IEEE Transactions on Industry Applications 53, no. 6 (2017): 5915-5926.
  23.  P. Kundu, and A. Kumar Pradhan. "Enhanced protection security using the system integrity protection scheme (SIPS)." IEEE Transactions on Power Delivery 31, no. 1 (2015): 228-235.
  24.  T. Weckesser, H. Jóhannsson, and J. Østergaard. "Real-time remedial action against aperiodic small signal rotor angle instability." IEEE Transactions on Power Systems 31, no. 1 (2015): 387-396.
  25.  M. Derafshian Maram, and N. Amjady. "Event‐based remedial action scheme against super‐component contingencies to avert frequency and voltage instabilities." IET Generation, Transmission & Distribution 8, no. 9 (2014): 1591-1603.
  26.  U. Rudez, and R. Mihalic. "WAMS-based underfrequency load shedding with short-term frequency prediction." IEEE Transactions on Power Delivery 31, no. 4 (2015): 1912-1920.
  27.  T. Shekari, A. Gholami, F. Aminifar, and M. Sanaye-Pasand. "An adaptive wide-area load shedding scheme incorporating power system real-time limitations." IEEE Systems Journal 12, no. 1 (2016): 759-767.
  28.  Y. Zhou, H. Huang, Z. Xu, W. Hua, F. Yang, and S. Liu. "Wide‐area measurement system‐based transient excitation boosting control to improve power system transient stability." IET Generation, Transmission & Distribution 9, no. 9 (2015): 845-854.
  29.  J. Gou, Y. Liu, J. Liu, G.A. Taylor, and M.M. Alamuti. "Novel pair‐wise relative energy function for transient stability analysis and real‐time emergency control." IET Generation, Transmission & Distribution 11, no. 18 (2017): 4565-4575.
  30.  Z. Liu, Z. Chen, H. Sun, and Y. Hu. "Multiagent system-based wide-area protection and control scheme against cascading events." IEEE Transactions on Power Delivery 30, no. 4 (2014): 1651-1662.
  31.  N. Liu, and P. Crossley. "Assessing the risk of implementing system integrity protection schemes in a power system with significant wind integration." IEEE Transactions on Power Delivery 33, no. 2 (2017): 810-820.
  32.  P.M. Joshi, and H.K. Verma. "Synchrophasor measurement applications and optimal PMU placement: A review." Electric Power Systems Research 199 (2021): 107428.
  33.  D. Zolin, and E. Ryzhkova. "Synchronized Phasor Measurements for Power System Digital Control Applications." In 2021 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), pp. 42-47. IEEE, 2021..
  34.  S. Kumar, B. Tyagi, V. Kumar, and S. Chohan. "Optimization of phasor measurement units placement under contingency using reliability of network components." IEEE Transactions on Instrumentation and Measurement 69, no. 12 (2020): 9893-9906.
  35.  A.K. Sinha, R. Kumar, C. Saikia, S. Rudrapaul, and B. Saikia. "An optimal PMU placement technique for the topological observability of a part of the NER grid of India." In 2013 International Conference on Circuits, Power and Computing Technologies (ICCPCT), pp. 142-146. IEEE, 2013.
  36.  G.C. Patil, and A.G. Thosar. "Optimal placement of PMU for power system observability using integer programming." In 2017 International Conference on Innovative Research In Electrical Sciences (IICIRES), pp. 1-6. IEEE, 2017.
  37.  Z. Lu, Z. Xu, and Z. Shi. "State estimation of voltage phasors based on part of voltage and current phasors measurement." Autom Electr Power Syst 24 (2000): 42-44.
  38.  North American Electric Reliability Cooperation (NERC), “PRC-012-2 – Remedial Action Schemes (Final Draft),” North American Electric Reliability Cooperation (NERC) PRC-012- 2, Tech. Rep., Apr. 2016.
  39.  W.S. Meyer, and V.D. Albertson. "Improved loss formula computation by optimally ordered elimination techniques." IEEE Transactions on Power Apparatus and Systems 1 (1971): 62-69.
  40.  R.D. Zimmerman, C.E. Murillo-Sánchez, and R.J. Thomas. "MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education." IEEE Transactions on Power Systems 26, no. 1 (2010): 12-19.
  41.  MATLAB version 9.6.0.1072779 (R2019a), The Mathworks, Inc., Natick, Massachusetts, 2019.
  42.  "Matlab optimization toolbox." The Mathworks, Inc., Natick, Massachusetts, 2019.
  43.  S.A. Mirjalili. "Genetic algorithm." In Evolutionary Algorithms and Neural Networks. Springer, (2019): 43–55.
  44.  S. Katoch, S.S. Chauhan, and V. Kumar. "A review on genetic algorithm: past, present, and future." Multimedia Tools and Applications 80 (2021): 8091-8126.
آمار
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