بهبود پایداری ولتاژ در ریزشبکه با استفاده از بهینه‌سازی کنترل محلی
محورهای موضوعی : مهندسی برق و کامپیوتروحید بهرامی فروتن 1 , محمدحسن مرادی 2 , محمد عابدینی 3
1 - دانشگاه بوعلی سینا
2 - دانشگاه بوعلی سینا
3 - دانشگاه آیت‌الله بروجردی
کلید واژه: اندازه‌گیری‌های ناحیه گسترده تدابیر ویژه حفاظتی تخمین پایداری گذرا روش تک‌ماشین معادل معیار سطوح برابر,
چکیده مقاله :
پایداری گذرا یکی از مسایل پراهمیت در بهره‌برداری از سیستم‌های قدرت است و لذا ارزیابی وضعیت پایداری گذرای شبکه امری ضروری است. روش‌های معمول ارزیابی وضعیت پایداری گذرا به صورت آفلاین می‌باشد که بر اساس آن مجموعه‌ای از اقدامات پیش‌گیرانه اتخاذ می‌شود و یا مجموعه‌ای از اقدامات اصلاحی تحت عنوان تدابیر ویژه حفاظتی برای عملکرد در شرایط زمان واقعی طراحی می‌شود. به منظور کاهش ریسک تدابیر اتخاذشده در شرایط زمان واقعی، در این مقاله روشی جدید برای تخمین برخط پایداری گذرا ارائه شده است که بر اساس ترکیب اندازه‌گیری‌های محلی و ناحیه گسترده عمل می‌کند. بر اساس این روش ابتدا سیستم قدرت دوناحیه‌ای با دسته‌بندی ژنراتورهای هم‌نوا و بر اساس روش تک‌ماشین معادل ساده‌سازی شده و سپس از معیار سطوح برابر برای پیش‌بینی پایداری گذرای آن استفاده می‌شود. بر اساس نوآوری روش پیشنهادی، سطح شتاب‌دهنده منحنی توان الکتریکی بر حسب زاویه رتور شبکه تک‌ماشینه معادل در لحظات وقوع خطا از روی سطوح شتاب‌دهنده محاسبه‌شده در هر یک از شین‌های ژنراتوری به صورت محلی محاسبه می‌شود که دقت محاسبات را افزایش می‌دهد. نتایج شبیه‌سازی انجام‌شده بر روی شبکه‌های نمونه 11شینه با چهار ژنراتور سنکرون و 39شینه با 10 ژنراتور سنکرون، کارآمدی روش پیشنهادی را نشان می‌دهد.
Stability challenges in Microgrids (MGs) usually arise from low inertia of Distributed Generation (DG). In this paper, a voltage stability improvement method is proposed in order to improve MG operation. Voltage Stability Index (VSI) is applied to evaluate and improve voltage stability of MGs including different types of DGs. A new hybrid optimization is introduced to find the optimal operation of autonomous MG and to improve VSI. Operational optimization is performed by finding optimal droop parameters of DGs and sitting wind DGs to reduce energy generation cost. Optimization is defined as a multi-objective function and a hybrid HS-GA algorithm is applied to solve the optimization problem. A new power flow formulation is also proposed in which the steady state frequency, reference frequency, droop coefficients and, reference voltage of droop based DGs are considered as optimization variables. Results of proposed approach are compared with other methods for 33 and 69-bus IEEE systems using MATLAB software. Results prove the efficiency of proposed approach for operational improvement of MGs.
[1] F. Katiraei, R. Iravani, N. Hatziaragyriou, and A. Dimeas, "Microgrids management," IEEE Power and Energy Magazine, vol. 6, no. 3, pp. 54-65, May/Jun. 2008.
[2] G. M. Masters, Renewable and Electric Power Systems, John Wiley & Sons, 2004.
[3] N. Khalesi, N. Rezaei, and M. Haghifam, "DG allocation with application of dynamic programming for loss reduction and reliability improvement," Int. J. Elect. Power Energy Syst., vol. 33, no. 1, pp. 288-295, Jan. 2011.
[4] K. Nekooei, M. M. Farsangi, H. Nezamabai, and K. Y. Lee, "An improved multi-objective harmony search for optimal placement of DGs in distribution systems," IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 557-567, Mar. 2013.
[5] A. Soroudi and M. Afrasiab, "Binary PSO-based dynamic multi-objective model for distributed generation planning under uncertainty," IET Gen., Transm. Distrib., vol. 6, no. 2, pp. 67-78, Jun. 2012.
[6] S. H. Abdi and K. Afshar, "Application of IPSO-Monte Carlo for optimal distributed generation allocation and sizing," Int. J. Elect. Power Energy Syst., vol. 44, no. 1, pp. 786-797, Feb. 2013.
[7] M. H. Moradi and M. Abedini, "A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems," Int. J. Elect. Power Energy Syst., vol. 34, no. 1, pp. 66-74, Jan. 2012.
[8] W. S. Tan, M. Y. Hassan, H. A. Rahman, and M. P. Abdullah, "Multi-distributed generation planning using hybrid particle swarm optimization-gravitational search algorithm including voltage rise issue," IET Gener., Transm., Distrib., vol. 7, no. 9, pp. 929-942, Jan. 2013.
[9] X. Guan, Z. Xu, and Q. Jia, "Energy-efficient buildings facilited by microgrid," IEEE Trans. on Smart Grid, vol. 1, no. 3, pp. 243-252, Dec. 2010.
[10] C. A. Hernandez-Aramburo, T. C. Green, and N. Mugniot, "Fuel consumption minimization of a microgrid," IEEE Trans. on Ind. Appl., vol. 41, no. 3, pp. 673-681, May 2005.
[11] E. Barklund, N. Pogaku, M. Prodanovic, C. Hernandez-Aramburo, and T. C. Green, "Energy management in autonomous microgrid using stability-constrained droop control of inverters," IEEE Trans. Power Electron., vol. 23, no. 5, pp. 2346-2352, Sep. 2008.
[12] A. K. Basu, A. Bhattacharya, S. Chowdhury, and S. P. Chowdhury, "Planned scheduling for economic power sharing in a CHP-based micro grid," Power Systems, IEEE Trans. on, vol. 27, no. 1, pp. 30-38, Feb. 2012.
[13] S. Conti, R. Nicolosi, S. A. Rizzo, and H. H. Zeineldin, "Optimal dispatching of distributed generators and storage systems for MV islanded microgrids," IEEE Trans. Power Del., vol. 27, no. 3, pp. 1243-1251, Jul. 2012.
[14] A. Basu, A. Bhattacharya, S. Chowdhury, and S. P. Chowdhury, "Planned scheduling for economic power sharing in a CHP-based microgrid," IEEE Trans. Power Syst., vol. 27, no. 1, pp. 30-38, Feb. 2012.
[15] B. Khorramdel and M. Raoofat, "Optimal stochastic reactive power scheduling in a microgrid considering voltage droop scheme of DGs and uncertainty of wind farms," Energy, vol. 45, no. 1, pp. 994-1006, Sept. 2012.
[16] E. Dilettoso, S. A. Rizzo, and N. Salerno, "SALHE-EA: a new evolutionary algorithm for multi-objective optimization of electromagnetic devices," in Intelligent Computer Techniques in Applied Electromagnetics, vol. 119, pp. 37-45, 2008.
[17] J. Mitra, M. R. Vallem, and S. B. Patra, "A probabilistic search method for optimal resource deployment in a microgrid," in Proc. 9th Int. Conf. Probabilistic Methods Applied to Power Systems, 6 pp., Stockholm, Sweden, Jun. 2006.
[18] M. Pipattanasomporn, M. Willingham, and S. Rahman, "Implications of on-site distributed generation for commercial/industrial facilities," IEEE Trans. Power Systems, vol. 20, no. 1, pp. 206-212, Feb. 2005.
[19] J. Oyarzabal, J. Jimeno, J. Ruela, A. Engler, and C. Hardt, "Agent based micro grid management system," in Proc. Int. Conf. on Future Power Systems, 6 pp., 18-18 Nov. 2005.
[20] H. E. Farag, M. M. A. Abdelaziz, and E. F. El-Saadany, "Voltage and reactive power impacts on successful operation of islanded microgrids," IEEE Trans. Power Syst., vol. 28, no. 2, pp. 1716-1727, May 2013.
[21] G. Diaz and C. Gonzalez-Moran, "Fischer-burmeister-based method for calculating equilibrium points of droop-regulated microgrids," IEEE Trans. Power Syst., vol. 27, no. 2, pp. 959-967, May 2012.
[22] N. R. Ullah, K. Bhattacharya, and T. Thiringer, "Wind farms as reactive power ancillary service providers-technical and economic issues," IEEE Trans. Energy Convers, vol. 24, no. 3, pp. 661-672, Sept. 2009.
[23] R. H. Lasseter and P. Piagi, "Microgrid: a conceptual solution," in Proc. of 35th Annual IEEE Power Electronics Specialists Conf., vol. 6, pp. 4285-4290, Aachen, Germany, 20-25 Jun. 2004.
[24] G. Antonis and D. Hatziargyriou, "Centralized control for optimizing microgrids operation," IEEE Trans. Energy Conversation, vol. 23, no. 1, pp. 241-248, Mar. 2008.
[25] C. A. Hernandez-Aramburo, T. C. Green, and N. Mugniot, "Fuel consumption minimization of a microgrid," IEEE Trans. on Industry Applications, vol. 41, no. 3, pp. 673-681, May-Jun. 2005.
[26] Z. W. Geem, J. H. Kim, and G. V. Loganathan, "A new heuristic optimization algorithm: harmony search," Simulation, vol. 76, no. 2, pp. 60-68, Feb. 2001.
[27] B. Khorramdel and M. Raoofat, "Optimal stochastic reactive power scheduling in a microgrid considering voltage droop scheme of DGs and uncertainty of wind farms," Energy, vol. 45, no. 1, pp. 994-1006, Sept. 2012.
[28] K. S. Lee and Z. W. Geem, "A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice," Comput. Methods Appl. Mech. Eng., vol. 194, no. 36-38, pp. 3902-3933, Sept. 2005.
[29] B. Venkatesh and R. Ranjan, "Data structure for radial distribution power flow analysis," IEE Proceedings Generation, Transmission and Distribution, vol. 150, no. 1, pp. 101-106, Jan. 2003.
[30] M. M. A. Abdelaziz and E. F. El-Saadany, "Maximum loadability consideration in droop-controlled islanded microgrids optimal power flow," Electric Power Sys. Res., vol. 106, pp. 168-179, Jan. 2014.
[31] C. A. Hernandez-Aramburo, T. C. Green, and N. Mugniot, "Fuel consumption minimization of a microgrid," IEEE Trans. on Industry Applications, vol. 41, no. 3, pp. 673-681, May 2005.
[32] M. H. Moradi, S. M. R. Tousi, and M. Abedini, "Multi-objective PFDE algorithm for solving the optimal siting and sizing problem of multiple DG sources," International J. of Electrical Power & Energy Systems, vol. 56, pp. 117-126, Mar. 2014.
