Coordinated Framework for Reconfiguration and Direct Load Control to Meet the Challenges of Distribution Systems Operation
Subject Areas : electrical and computer engineeringE. Hosseini 1 , Mohammad Sadegh Sepasian 2 , H. Arasteh 3 , V. Vahidinasab 4
1 -
2 -
3 -
4 -
Abstract :
The basic approach of this paper is to improve the operational condition of distribution systems by the simultaneous utilization of system reconfiguration and direct load control programs. A Genetic Algorithm (GA) based algorithm is employed to find the optimal states of switches as well as the optimal incentives of the demand response programs. The concept of price elasticity of demand is utilized to illustrate the changes of electricity consumption pattern as a result of customers’ participation in Demand Response (DR). The objective function of the proposed model is network operation costs. In addition, voltage constraints, lines capacity limits and the related constraints of DR programs are considered in the optimization problem. Finally, the effectiveness of the proposed method in reducing operation costs is shown using the 33-bus distribution network. The simulation results show that the coordination of reconfiguration and DR can reduce the operation costs and load shedding requirements in addition to solving lines’ over loading problems.
[1] د. منظور و ح. رضایی، "محاسبه قيمت سايه‌اي انرژي الكتريكي در بازار برق ايران،" فصل‌نامه تحقيقات مدل‌سازي اقتصادي، جلد 2، شماره 6، صص. 172-155، زمستان 1390.
[2] S. S. F. Souza, R. Romero, and J. F. Franco, "Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems," Electr. Power Syst. Res., vol. 119, pp. 304-312, Feb. 2015.
[3] A. Zidan, M. F. Shaaban, and E. F. El-Saadany, "Long-term multi-objective distribution network planning by DG allocation and feeders' reconfiguration," Electr. Power Syst. Res., vol. 95, pp. 95-104, Dec. 2013.
[4] ر. هوشمند و ا. قلی‌پور، "بازآرایی سیستم توزیع در محيط بازار برق با حضور منابع توليد پراكنده،" نشريه مهندسي برق و مهندسي كامپيوتر ايران، الف- مهندسي برق، سال 12، شماره 1، صص. 45-37، بهار 1393.
[5] L. S. M. Guedes, A. C. Lisboa, D. A. G. Vieira, and R. R. Saldanha, "A multiobjective heuristic for reconfiguration of the electrical radial network," IEEE Trans. Power Del., vol. 28, no. 1, pp. 311-319, Oct. 2013.
[6] U. S. Department of Energy, "Benefits of demand response in electricity markets and recommendations for achieving them," Section 1252 of the Report, Energy Policy Act of 2005, 2006.
[7] A. Merlin and H. Back, "Search for a minimal loss operating spanning tree configuration in urban power distribution system," in Proc. Power Syst. Comput. Conf., pp. 1-18, Sep. 1975.
[8] S. Civanlar, J. J. Grainger, H. Yin, and S. S. H. Lee, "Distribution feeder reconfiguration for loss reduction," IEEE Trans. Power Del., vol. 3, no. 3, pp. 1217-1223, Jul. 1988.
[9] M. H. Haque, "Improvement of power delivery efficiency of distribution system through loss reduction," in Proc. IEEE Conf. Power Eng. Soc., Winter Meeting, vol. 4, pp. 2739-2744, Jan. 2000.
[10] Q. Zhou, D. Shirmohammadi, and W. H. E. Liu, "Distribution feeder reconfiguration for operation cost reductio," IEEE Trans. Power Syst., vol. 112, no. 2, pp. 730-735, May 1997
[11] H. C. Chin and K. Y. Huage, "A simple distribution reconfiguration algorithm for loss minimization," in Proc. IEEE Conf. Power Syst. Technology, vol. 2, pp. 607-611, Dec. 2000.
[12] G. J. Whei-Min Lin and H. C. Chin, "An effective algorithm for distribution feeder loss reduction by switching operation," in Proc. IEEE Conf. Transm. Distrib., vol. 2, pp. 597-602, Apr. 1999.
[13] V. Glamocanin, "Optimal loss reduction of distribution networks," IEEE Trans. Power Syst., vol. 5, no. 5, 774-782, Sep. 1990.
[14] T. E. McDermott, I. Drezgo, and R. P. Broadwater, "A hueristic nonlinear constructive method for distribution system reconfiguration," IEEE Trans. Power Del., vol. 14, no. 2, pp. 478-483, May 1999.
[15] R. T. F. Ah King, B. Radha, and H. C. S. Rughooputh, "A real-parameter genetic algorithm for optimal network reconfiguration," in IEEE Conf. Ind. Technol., vol. 1, pp. 54-59, Dec. 2003.
[16] N. Gupta, A. Swarnkar, and K. R. Niazi, "Distribution network reconfiguration for power quality and reliability improvement using genetic algorithms," Electr. Power Energy Syst., vol. 54, pp. 664-671, Jan. 2014.
[17] A. Mazza, G. Chicco, and A. Russo, "Optimal multi-objective distribution system reconfiguration with multi criteria decision making-based solution ranking and enhanced genetic operators," Electr. Power Energy Syst., vol. 54, pp. 255-267, Jan. 2014.
[18] D. Shirmohammadi and H. W. Hong, "Reconfiguration of electric distribution networks for resistive line losses reduction," IEEE Trans. Power Deli., vol. 4, no. 2, pp. 1492-1498, Apr. 1989.
[19] D. Das, "A fuzzy multi-objective approach for network reconfiguration of distribution systems," IEEE Trans. Power Del., vol. 21, no. 1, pp. 202-209, Jan. 2006.
[20] K. Nara, A. Shiose, M. Kitagawoa, and T. Ishihara, "Implementation of genetic algorithm for distribution systems loss minimum reconfiguration," IEEE Trans. Power Syst., vol. 7, no. 3, pp. 1044-1051, Aug. 1992.
[21] J. Z. Zhu, "Optimal reconfiguration of electrical distribution network using the refined genetic algorithm," Elect. Power Syst. Res., vol. 62, no. 1, pp. 37-42, May 2002.
[22] R. Srinivasa Rao, S. V. L. Narasimham, M. R. Raju, and A. Srinivasa Rao, "Optimal network reconfiguration of large-scale distribution system using harmony search algorithm," IEEE Trans. Power Syst., vol. 26, no. 3, pp. 1080-1088, Sep. 2011.
[23] T. DcDermott, "Distribution system reliability and reconfiguration software tools," in Proc. EEE/PES. Transmission and Distribution Conference and Exposition, vol. 2, pp. 993-993, Nov. 2001.
[24] H. Salazar, R. Gallego, and R. Romero, "Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems," IEEE Trans. Power Del., vol. 21, no. 3, pp. 1735-1742, Jul. 2006.
[25] R. J. Sarfi, M. M. A. Salma, and A. Y. Chikani, "Loss reduction in distribution system: a new approach using partitioning techniques," in Proc. IEEE IAS Annual Meeting, vol. 2, pp. 1439-1444, Oct. 1993.
[26] R. J. Sarfi, M. M. A. Salma, and A. Y. Chikani, "Distribution system reconfiguration for loss reduction: an algorithm based on network partitioning theory," IEEE Trans. Power Syst., vol. 11, no. 1, pp. 504-510, Feb. 1996.
[27] C. Chang, "Reconfiguration and capacitor placement for loss reduction of distribution systems by ant colony search algorithm," IEEE Trans. Power Syst., vol. 23, no. 4, 1747-1755, Nov. 2008.
[28] S. Valero, M. Ortiz, C. Senabre, C. Alvarez, F. J. G. Franco, and A. Gabaldon, "Methods for customer and demand response policies selection in new electricity markets," IET Gener. Transm. Distrib., vol. 1, no. 1, pp. 104-110, Jan. 2007.
[29] E. Bompard, Y. Ma, R. Napoli, and G. Abrate, "The demand elasticity impacts on the strategic bidding behavior of the electricity producers," IEEE Trans. Power Syst., vol. 22, no. 1, pp. 188-197, Feb. 2007.
[30] C. L. Su and D. Kirschen, "Quantifying the effect of demand response on electricity markets," IEEE Trans. Power Syst., vol. 24, no. 3, pp. 1199-1207, Aug. 2009.
[31] A. Khodaei, M. Shahidehpour, and S. Bahramirad, "SCUC with hourly demand response considering intertemporal load characteristics," IEEE Trans. Smart Grid, vol. 2, no. 3, pp. 564-571, Sep. 2011.
[32] A. Abdollahi, M. Parsa Moghaddam, M. Rashidinejad, and M. K. Sheikh-El-Eslami, "Investigation of economic & environmental-driven demand response measures incorporating UC," IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 12-25, Mar. 2012.
[33] H. A. Aalami, M. Parsa Moghaddam, and G. R. Yousefi, "Modeling and prioritizing demand response programs in power markets," Electr. Power Syst. Res., vol. 80, no. 4, pp. 426-435, Apr. 2010.
[34] M. P. Moghaddam, A. Abdollahi, and M. Rashidinejad, "Flexible demand response programs modeling in competitive electricity markets," Appl. Energy, vol. 88, no. 9, pp. 3257-3269, Sep. 2011.
[35] D. T. Nguyen, M. Negnevitsky, and M. de Groot, "Pool-based demand response exchange-concept and modeling," IEEE Trans. Power Syst., vol. 26, no. 3, pp. 1677-1685, Jul. 2011.
[36] S. Chandramohan, N. Atturulu, R. P. Kumudini Devi, and B. Venkatesh, "Operating cost minimization of a radial distribution system in a deregulated electricity market through reconfiguration using NSGA method," Electr. Power Energy Syst., vol. 32, no. 2, pp. 126-132, Feb. 2010.
[37] R. S. Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham, "Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation," IEEE Trans. Power Syst., vol. 28, no. 1, pp. 317-325, Feb. 2013.
[38] S. H. Mirhoseini, S. M. Hosseini, M. Ghanbari, and M. Ahmadi, "A new improved adaptive imperialist competitive algorithm to solve the reconfiguration problem of distribution systems for loss reduction and voltage profile improvement," Electr. Power Energy Syst., vol. 55, pp. 128-143, Feb. 2014.
[39] G. Gutierrez-Alcaraz and C. N. Lu, "Demand response and network reconfiguration on distribution system investment deferment," in Cired, Conf. Electr. Distrib., 4 pp., Jun. 2011.
[40] H. Bagheri Tolabi, M. H. Ali, S. B. M. Ayob, and M. Rizwan, "Novel hybrid fuzzy-bees algorithm for optimal feeder multi-objective reconfiguration by considering multiple-distributed generation," Energy, vol. 71, pp. 507-515, Jul. 2014.
[41] A. M. Cossi, R. Romero, and J. R. Mantovani, "Planning and projects of secondary electric power distribution systems," IEEE Trans. Power Syst., vol. 24, no. 3, pp. 1599-608, Aug. 2009.
[42] H. G. Kwag and J. O. Kim, "Optimal combined scheduling of generation and demand response with demand resource constraints," Appl. Energy, vol. 96, pp. 161-170, Aug. 2012.
[43] ح. ا. اعلمي، مدل‌سازي پاسخ‌گويي بار مبتني بر ضرايب حساسيت قيمتي تقاضا، رساله دکتري مهندسي برق- قدرت، دانشگاه تربيت مدرس، تهران، 1389.
[44] IEA, Strategic Plan for the IEA Demand-Side Management Program 2008-2012. IEA Press, 2008, Available at, http://www.iea.org, accessed Mar. 2012.
[45] M. Klobasa, "Analysis of demand response and wind integration in Germany's electricity market," IET Renew. Power Gener., vol. 4, no. 1, pp. 55-63, Feb. 2010.
[46] ح. ا. اعلمي، غ. ر. يوسفي و م. پارسامقدم، "تأثير برنامه‌هاي پاسخ‌گويي بار بر منحني مصرف برق روزانه كشور،" نشريه مهندسي برق و مهندسي كامپيوتر ايران، سال 6، شماره 4، صص. 316-308، زمستان 1387.
[47] م. کیا، م. ستایش‌نظر و م. ص. سپاسیان، "اجرای هم‌زمان برنامه پاسخ‌گویی بار زمان استفاده (TOU) و برنامه مشارکت واحدها با قید امنیت (SCUC)،" نشريه مهندسي برق و مهندسي كامپيوتر ايران، الف- مهندسي برق، سال 13، شماره 1، صص. 24-13، بهار 1394.
[48] M. H. Amini, B. Nabi, and M. R. Haghifam, "Load management using multi-agent systems in smart distribution network," in Proc. IEEE PES General Meeting, Vancouver, 5 pp., British Columbia, Canada, Jul. 2013.
[49] H. R. Arasteh, M. Parsa Moghaddam, M. K. Sheikh-El-Eslami, and A. Abdollahi, "Integrating commercial demand response resources with unit commitment," Electr. Power Energy Syst., vol. 51, pp. 153-161, Oct. 2013.
[50] D. S. Kirschen and G. Strbac, Fundamentals of Power System Economics, John Wiley & Sons, 2004.
[51] H. Aalami, M. Parsa Moghaddam, and G. R. Yousefi, "Demand response modeling considering interruptible/curtailable loads and capacity market programs," Appl. Energy, vol. 87, no. 1, pp. 243-250, Jan. 2010.
[52] H. Aalami, G. R. Yousefi, and M. ParsaMoghaddam, "Demand response model considering EDRP and TOU programs," in Proc. IEEE PES T & D Conf., 6 pp., Chicago, USA, Apr. 2008.
[53] M. E. Baran and F. Wu, "Network reconfiguration in distribution systems for loss reduction and load balancing," IEEE Trans. Power Del., vol. 4, no. 2, pp. 1401-1407, Apr. 1989.
