پایان نامه پخش بار سری زمانی

فهرست پایان نامه پخش بار سری زمانی

فهرست:

فصل اول: مقدمه

1-1- اهمیت مسئله. 2

1-2- پخش بار احتمالی.. 3

1-3- مروری بر کارهای انجام شده 12

1-4- اهداف پایان نامه. 24

1-5- ساختار پایان نامه. 25

فصل دوم: سری های زمانی

2-1- مقدمه. 27

2-2- مدلهای ARMA.. 27

2-2-1- فرآیندهای ایستا و ناایستا 27

2-2-2- فرآیندهای میانگین متحرک  (MA) 29

2-2-3- فرآیندهای خودبازگشتی (AR) 29

2-2-4- فرآیندهایARMA.. 30

2-2-5- فرآیندهای ARIMA.. 30

2-2-6- فرآیندهای SARIMA.. 31

2-2-7- فرآیندهای Multivariate ARMA.. 31

2-3- ویژگی مدل سریهای زمانی.. 32

2-3-1- توابع خود همبستگی و خود همبستگی جزیی.. 32

2-3-2- تعیین ایستایی وناایستایی سری های زمانی با استفاده از تابع ACF.. 35

2-3-3- شناسایی الگو با استفاده از توابع ACF و PACF.. 36

2-3-4- شرط ایستایی و وارون پذیری با توجه به ضرایب مدل.. 37

2-3-5- آ‍زمونهای تشخیص الگو. 38

فصل سوم: پخش بار سری زمانی

3-1- مقدمه. 40

3-2- پخش بار احتمالی.. 41

3-3- معرفی روش پخش بار فرمولاسیون4. 43

3-4- فرمول بندی روش پیشنهادی.. 47

3-5- شبیه سازی شبکه مورد مطالعه. 51

3-5-1- مدلسازی سری زمانی توان خروجی توربین بادی.. 52

3-5-2- مدلسازی توان اکتیو و راکتیو تزریقی.. 55

3-5-3- نتایج شبیه سازی.. 56

فصل چهارم: استفاده از پخش بار سری زمانی برای تغییر ساختار شبکه با هدف مینیمم کردن تلفات

4-1- مقدمه. 67

4-2- مسئله بازآرایی شبکه در سیستم های قدرت... 68

4-3- معرفی الگوریتم BPSO.. 70

4-4- استفاده از مدل های سری زمانی در بازآرایی شبکه. 71

4-5- نتایج شبیه سازی.. 73

4-5-1- شبکه مورد مطالعه. 73

4-5-2- نتایج.. 74

4-5-3- بررسی درستی روش پیشنهادی.. 77

فصل پنجم: استفاده از سری زمانی DAR برای مدلسازی پارامترهای گسسته در سیستم قدرت

5-1- مقدمه. 83

5-2- متغیرهای گسسته در سیستم قدرت... 84

5-2-1- مدلسازی تپ ترانس.... 84

5-2-2- مدلسازی واحدهای تولید پراکنده CHP.. 85

5-3- فرآیندهای خودبازگشتی گسسته (DAR) 87

5-3-1- معرفی مدل.. 87

5-3-2- انتخاب درجه مدل.. 88

5-3-3- بررسی درستنمائی مدل انتخاب شده 90

5-3-4- تخمین پارامترهای مجهول در مدل.. 92

5-4- نتایج شبیه سازی.. 93

فصل ششم: نتیجه گیری و پیشنهادات

6-1- نتیجه گیری.. 99

6-2- پیشنهادات... 100

ضمیمه

7-1- اطلاعات شبکه 14 باسه IEEE.. 102

7-2- اطلاعات شبکه 69 باسه. 104

منابع و مآخذ  108

منبع:

 

 

[1] T. Boehme, A. R. Wallace, and G. P. Harrison, “Applying Time Series to Power Flow Analysis in Networks With High Wind Penetration,” IEEE Transactions on Power Systems, vol. 22, no. 3, pp. 951–957, 2007.

 

[2] P. Chen, Z. Chen, and B. Bak-Jensen, “Probabilistic load flow: A review,” in Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008, 2008, pp. 1586–1591.

 

[3] G. J. Anders, “Probability Concepts in Electric Power Systems”, New York: Wiley, 1990.

 

[4] P. Chen, Stochastic Modeling and Analysis of Power System with Renewable Generation. Department of Energy Technology, Aalborg University, 2010.

 

[5] E. Rosenblueth, “Point estimates for probability moments”, Proc. Nat. Acad. Sci., Vol. 72, pp. 3812–3814, Oct. 1975.

 

[6] E. Rosenblueth, “Two-point estimates in probability”, Appl. Math. Model. Vol. 5, pp. 329-335, Oct. 1981.

 

[7] K. S. Li, “Point-estimate method for calculating statistical moments”, J. Eng. Mech.-ASCE, Vol. 118, No. 7, pp. 1506-1511, Jul. 1992.

 

[8] M. E. Harr, “Probabilistic estimates for multivariate analysis”, Appl. Math. Model., Vol. 13, No. 5, pp. 313-318, May. 1989.

 

[9] H. P. Hong, “An efficient point estimate method for probabilistic analysis”, Reliab. Eng. Syst. Saf., Vol. 59, No. 3, pp. 261-267, Mar. 1998.

 

[10] B. Borkowska, “Probabilistic load flow”, IEEE Trans. Power Apparatusnand Systems, Vol. PAS-93, No. 3, pp. 752-755, May-Jun. 1974.

 

[11] R. N. Allan and M. R. G. Al-Shakarchi, “Probabilistic a.c. load flow”, Proceedings of the Institution of Electrical Engineers, Vol. 123, No. 6, pp. 531-536, Jun. 1976.

 

[12] R. N. Allan and M. R. G. Al-Shakarchi, “Probabilistic techniques in AC load flow analysis”, Proc. IEEE PAS-124, pp. 154–160, Feb. 1976.

 

[13] R. N. Allan and A. M. Leite da Silva, “Probabilistic load flow using multilinearisations”, IEE Proc., Part C: Generation, Transmission and Distribution, Vol. 128, No. 5, pp. 280-287, Sep. 1981.

 

[14] A. P. S. Meliopoulos, G. J. Cokkinides and X. Y. Chao, “A new probabilistic power flow analysis method”, IEEE Trans. Power Systems, Vol. 5, No. 1, pp. 182-190, Feb. 1990.

 

[15] A. M. Leite da Silva and V.L. Arienti, “Probabilistic load flow by a multilinear simulation algorithm”, IEE Proc. Part C: Generation, Transmission and Distribution, Vol. 137, No. 4, pp. 276-282, Jul. 1990.

 

[16] M. Brucoli, F. Torelli and R. Napoli, “Quadratic probabilistic load flow with linearly modelled dispatch”, Electrical Power & Energy Systems, Vol. 7, No. 3, pp. 138-146, Jul. 1985.

 

[17] A. M. Leite da Silva, R. N. Allan, S. M. Soares, “Probabilistic load flow considering network outages”, IEE Proc., Part C: Generation, Transmission and Distribution, Vol. 132, No. 3, pp. 139-145, May. 1985.

 

[18] L. A. Sanabria and T. S. Dillon, “Stochastic power flow using cumulants and Von Mises functions,” International Journal of Electrical Power & Energy Systems, vol. 8, no. 1, pp. 47–60, Jan. 1986.

 

[19] N. S. Rau and C. Necsulescu, “Solution of probabilistic load flow equations using combinatorics,” International Journal of Electrical Power & Energy Systems, vol. 12, no. 3, pp. 156–164, Jul. 1990.

 

[20] P. Zhang and S.T. Lee, “Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion”, IEEE Trans. Power Systems, Vol. 19, No. 1, pp. 676-682, Feb. 2004.

 

[21] C.-L. Su, “Distribution probabilistic load flow solution considering network reconfiguration and voltage control devices,” in 15th Power Systems Computation Conference, Liege, 2005.

 

[22] N. D. Hatziargyriou, T. S. Karakatsanis, and M. I. Lorentzou, “Voltage control settings to increase wind power based on probabilistic load flow,” International Journal of Electrical Power & Energy Systems, vol. 27, no. 9–10, pp. 656–661, Nov. 2005.

 

[23] C. L. Su, “Probabilistic load-flow computation using point estimate method”, IEEE Trans. Power Systems, Vol. 20, No. 4, pp. 1843-1851,Nov. 2005.

 

[24] Z. Hu and X. Wang, “A probabilistic load flow method considering branch outages”, IEEE Trans. Power Systems, Vol. 21, No. 2, pp. 507-514, May. 2006.

 

[25] J.M. Morales, J. Perez-Ruiz, “Point estimate schemes to solve the probabilistic power flow”, IEEE Transaction on Power Systems, Vol. 22, No. 4, pp. 1594-1601, Nov. 2007.

 

[26] H. Liao, “Fast Deterministic Sampling for Mean and Covariance Estimation in Stochastic Load Flow”, IEEE Conference Power Engineering Society General Meeting, Tampa, FL, pp. 1-6, 24-28 June 2007.

 

[27] J. Schwippe, O. Krause, C. Rehtanz, “Extension of a Probabilistic Load Flow Calculation Based on an Enhanced Convolution Technique”, IEEE Conference on Sustainable Alternative Energy, Valencia, pp. 1-6, 28-30 Sept 2009.

 

[28] J. Usaola, “Probabilistic load flow with wind production uncertainty using cumulants and Cornish–Fisher expansion”, Journal of  Electrical Power and Energy Systems, Vol. 31, No. 9, pp. 474-481, Oct. 2009.

 

[29] P. Caramia, G. Carpinelli, P. Varilone, “Point estimate schemes for probabilistic three-phase load flow”, Journal of Electric Power Systems Research, Vol. 80, No. 2, pp. 168-175,  Feb. 2010.

 

[30] J. Usaola, “Probabilistic load flow with correlated wind power injections”, Journal of Electric Power Systems Research, Vol. 80, No. 5, pp. 528-536, May. 2010.

 

[31] F.J. Ruiz-Rodriguez, J.C. Hernández, F. Jurado, “Probabilistic load flow for photovoltaic distributed generation using the Cornish-Fisher expansion”, Journal of Electric Power Systems Research, Vol. 89, pp. 129-138, Aug. 2012.

 

[32] D. Shirmohammadi, H.W. Hong, A. Semlyen, “A compensation-based power flow method for weakly Meshed distribution and transmission network”, IEEE Transactions on Power Systems, Vol. 3, No. 2, pp. 753-762, May. 1988.

 

[33] R. N. Allan, C. H. Grigg, D. A. Newey, “Probabilistic power-flow techniques extended and applied to operational decision making”, Proceedings of the Institution of Electrical Engineers, Vol. 123, No. 12, pp. 1317-1324, Dec. 1976.

 

[34] A. M. Leite da Silva, V. L. Arienti and R. N. Allan, “Probabilistic load flow considering dependence between input nodal powers”, IEEE Trans. Power Apparatus and Systems, Vol. PAS-103, No. 6, pp. 1524-1530, Jun. 1984.

 

[35] G. Papaefthymiou, P. H. Schavemaker, L. van der Sluis, “Integration of stochastic generation in power systems”, 15th Power Systems Computation Conference, Liege, Aug. 2005.

 

[36] P.F. Correia, J.M. Ferreira de Jesus, “Simulation of correlated wind speed and power variates in wind parks”, Journal of Electric Power Systems Research, Vol. 80, No. 5, pp. 592-598, May. 2010.

 

[37] D. Villanueva, A. Feijóo, J. Luis Pazos, “Probabilistic Load Flow Considering Correlation between Generation, Loads and Wind Power”, Journal of Smart Grid and Renewable Energy, Vol. 2, pp. 12-20, Feb. 2011.

 

[38] N. Amjady, “Short-Term Hourly Load Forecasting Using Time-Series Modeling With Peak Load Estimation Capability”, IEEE Trans. Power Systems, Vol. 16, No. 4, pp. 798-805, Nov. 2001.

 

[39] N. Amjady, “Generation Adequacy Assessment of Power Systems by Time Series and Fuzzy Neural Network”, IEEE Trans. Power Systems, Vol. 21, No. 3, pp. 1340-1349, Aug. 2006.

 

[40] C. Y. Evrenosog˜lu, and A. Abur, “Time Series Modeling of Voltage Profiles Along Transmission Lines”, IEEE Trans. Power Systems, Vol. 22, No. 1, pp. 172-178, Feb. 2007.

 

[41] P. Chen, T. Pedersen, B. Bak-Jensen, and Z. Chen, “ARIMA-Based Time Series Model of Stochastic Wind Power Generation,” IEEE Transactions on Power Systems, vol. 25, no. 2, pp. 667–676, May 2010.

 

]42[ صامت. ح.، مدلسازی دینامیکی و پیشبینی توان راکتیو کوره های قوس الکتریکی با هدف استفاده در الگوریتم کنترل SVC. دانشکده مهندسی برق و کامپیوتر، دانشگاه صنعتی اصفهان، 1387.

 

[43] G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting and Control. John Wiley & Sons, 2008.

 

[44] Z. I. Botev, J. F. Grotowski, and D. P. Kroese, “Kernel density estimation via diffusion,” Ann. Statist., vol. 38, no. 5, pp. 2916–2957, Oct. 2010.

 

[45] S.-A. Yin and C.-N. Lu, “Distribution Feeder Scheduling Considering Variable Load Profile and Outage Costs,” IEEE Transactions on Power Systems, vol. 24, no. 2, pp. 652–660, May 2009.

 

[46] A. Merlin and H. Back, “Search for a minimal-loss operating spanning tree configuration in an urban power distribution system,” in Proc. of the Fifth Power System Conference (PSCC), Cambridge, 1975, pp. 1–18.

 

[47] S. Civanlar, J. J. Grainger, H. Yin, and S. S. H. Lee, “Distribution feeder reconfiguration for loss reduction,” IEEE Transactions on Power Delivery, vol. 3, no. 3, pp. 1217–1223, Jul. 1988.

 

[48] D. Shirmohammadi and H. W. Hong, “Reconfiguration of electric distribution networks for resistive line losses reduction,” IEEE Transactions on Power Delivery, vol. 4, no. 2, pp. 1492–1498, Apr. 1989.

 

[49] K. Nara, A. Shiose, M. Kitagawa, and T. Ishihara, “Implementation of genetic algorithm for distribution systems loss minimum re-configuration,” IEEE Transactions on Power Systems, vol. 7, no. 3, pp. 1044–1051, Aug. 1992.

 

[50] R. J. Sarfi, M. M. A. Salama, and A. Y. Chikhani, “Distribution system reconfiguration for loss reduction: an algorithm based on network partitioning theory,” in, 1995 IEEE Power Industry Computer Application Conference, 1995. Conference Proceedings, 1995, pp. 503–509.

 

[51] Y. H. Song, G. S. Wang, A. T. Johns, and P. Y. Wang, “Distribution network reconfiguration for loss reduction using fuzzy controlled evolutionary programming,” Generation, Transmission and Distribution, IEE Proceedings-, vol. 144, no. 4, pp. 345–350, Jul. 1997.

 

[52] D. Das, “A fuzzy multiobjective approach for network reconfiguration of distribution systems,” IEEE Transactions on Power Delivery, vol. 21, no. 1, pp. 202–209, Jan. 2006.

 

[53] A. Biswas and P. X.-K. Song, “Discrete-valued ARMA processes,” Statistics & Probability Letters, vol. 79, no. 17, pp. 1884–1889, Sep. 2009.

 

[54] P. X.-K. Song, R. K. Freeland, A. Biswas, and S. Zhang, “Statistical analysis of discrete-valued time series using categorical ARMA models,” Computational Statistics & Data Analysis, vol. 57, no. 1, pp. 112–124, Jan. 2013.

 

[55] P. Chen, Z. Chen, B. Bak-Jensen, R. Waagepetersen, and S. Sörensen, “Verification of a Probabilistic Model for A Distribution System with Integration of Dispersed Generation,” in Proceedings of the 16th Power Systems Computation Conference, 2008, p. 7.

 

[56] P. Chen, Z. Chen, B. Bak-Jensen, R. Villafafila, and S. Sorensen, “Study of power fluctuation from dispersed generations and loads and its impact on a distribution network through a probabilistic approach,” in 9th International Conference on Electrical Power Quality and Utilisation, 2007. EPQU 2007, 2007, pp. 1–5.

 

[57] A. Shamshad, M. A. Bawadi, W. M. A. Wan Hussin, T. A. Majid, and S. A. M. Sanusi, “First and second order Markov chain models for synthetic generation of wind speed time series,” Energy, vol. 30, no. 5, pp. 693–708, Apr. 2005.

 

[58] N. B. Negra, O. Holmstrøm, B. Bak-Jensen, and P. Sørensen, “Model of a synthetic wind speed time series generator,” Wind Energy, vol. 11, no. 2, pp. 193–209, 2008.

 

[59] G. Papaefthymiou and B. Klockl, “MCMC for Wind Power Simulation,” IEEE Transactions on Energy Conversion, vol. 23, no. 1, pp. 234–240, Mar. 2008.