Multi-objective optimal reactive power dispatch to maximize power system social welfare in the presence of generalized unified power flow controller

• Autorzy: Suresh C. V. , Sivanguraju S.

Identyfikatory

DOI

10.2478/aee-2015-0032

• Języki publikacji: EN

Abstrakty

EN

In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC). This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.

Słowa kluczowe

EN

generalized unified power flow controller; optimal reactive power dispatch; social welfare; multi-objective optimization

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2015
• Tom: Vol. 64, nr 3
• Strony: 405--426
• Opis fizyczny: Bibliogr. 35 poz., rys., tab., wz.

Twórcy

autor

Suresh C. V.

• Department of Electrical and Electronics Engineering Jawaharlal Nehru Technological University Kakinada, Kakinada Andhra Pradesh, 533 003, India

autor

Sivanguraju S.

• Department of Electrical and Electronics Engineering Jawaharlal Nehru Technological University Kakinada, Kakinada Andhra Pradesh, 533 003, India

Bibliografia

• [1] Hasanpour S., Ghazi R., Javidi MH., A new approach for cost allocation and reactive power pricing in a deregulated environment. Electrical Engineering 91: 27-34 (2009).
• [2] Almeida K. C., Senna F.S., Optimal active-reactive power dispatch under competition via bilevel programming. IEEE Transactions on Power Systems 26(4): 2345-2354 (2011).
• [3] Gomesa M. H., Saraivab J. T., A market based active/reactive dispatch including transformer taps and reactor and capacitor banks using simulated annealing. Electric Power Systems Research 79: 959-972 (2009).
• [4] Kundur P., Power System Stability and Control. McGraw-Hill, Inc., New York (1994).
• [5] Rabiee A., Shayanfar H., Amjady N., Multi-objective clearing of reactive power market in deregulated power systems. Applied Energy 86(9): 1555-1564 (2009).
• [6] Operating Policy-10 on Interconnected Operation Services. North American Electric Reliability Corporation (2000).
• [7] Xie K., Song Y. H., Stonham J., Yu E., Liu G., Decomposition Model and Interior Point Methods for Optimal Spot Pricing of Electricity in Deregulated Environments. IEEE Transactions on Power Systems 15(1): 39-50 (2000).
• [8] Verma K. S., Gupta H. O., Impact on real and reactive power pricing in open power market using unified power flow controller. IEEE Transactions on Power Systems 21(1): 365-371 (2006).
• [9] Verma K. S., Singh S. N., Gupta H. O., Optimal location of UPFC for congestion management. Electrical Power Systems Research 58(2): 89-96 (2001).
• [10] Verma K. S., Singh S. N., Gupta H. O., FACTS device location for enhancement of total transfer capability. Proceedings of IEEE Power Engineering Society. Winter Meeting, Columbus 2: 522-527 (2001).
• [11] Choi J. Y., Rim S. H., Park J. K., Optimal real time pricing of real and reactive powers. IEEE Transactions on Power Systems 13(4): 1226-1231 (1998).
• [12] Lamont J. W., Fu J., Cost analysis of reactive power support. IEEE Transactions Power Systems, 14(3): 890-896 (1999).
• [13] Dai Y., Ni Y. X., Wen F. S., Han Z. X., Analysis of reactive power pricing under deregulation. Proceedings of IEEE Power Engineering Society, Summer Meeting, Seattle, pp. 2162-2167 (2000).
• [14] Ranatunga R. A. S. K., Annakkage U. D., Kumble C. S., Algorithms for incorporating reactive power into market dispatch. Electrical Power Systems Research 65: 179-186 (2003).
• [15] Ranatunga R. A. S. K., Annakkage U. D., Kumble C. S., Implications of reactive power on nodal pricing and dispatch. Proceedings of IEEE Power Engineering, Winter Meeting, pp. 885-890 (2000).
• [16] Devaraj D., Improved genetic algorithm for multi-objective reactive power dispatch problem. European Transactions on Electrical Power 17(6): 569-581 (2007).
• [17] Li Hongxin., Li Yinhong., Chen Jinfu., Adaptive multiple evolutionary algorithms search for multi-objective optimal reactive power dispatch. International Transactions on Electrical Energy Systems 24(6): 780-795 (2013).
• [18] Taher Niknam., Mohammad Rasoul Narimani., Masoud Jabbari., Dynamic optimal power flow using hybrid particle swarm optimization and simulated annealing. International Transactions on Electrical Energy Systems 23(7): 975-1001 (2013).
• [19] Hazra J, Sinha A. K, A multi-objective optimal power flow using particle swarm optimization. European Transactions on Electrical Power 21(1): 1028-1045 (2011).
• [20] Saravanan M., Mary Raja Slochanal S., Venkatesh P., Prince Stephen Abraham J., Application of particle swarm optimization technique for optimal FACTS devices considering cost of installation and system loadability. Electrical Power Systems Research 77: 276-283 (2007).
• [21] Seyed M.H. Nabavi., Kamran Khafafi., Aidin Sakhavati., Saeid Nahi., Optimal Location and Sizing of SSSC using Genetic Algorithm in Deregulated Power Market. International Journal of Computer Applications 22(4): 37-41 (2011).
• [22] Husam I. Shaheen., Ghamgeen I., Rashed S.J. Cheng., Optimal location and parameter setting of UPFC for enhancing power system security based on differential evolution algorithm. Electrical power and energy systems 33: 94-105 (2011).
• [23] Y. Dai., X .D. Liu., Y. X. Ni., F. S. Wen., Z. H. Han., C. M. Shen., F. F. Wu., A cost allocation method for reactive power service based in power flow tracing. Electrical Power System Research 64: 59-65 (2003).
• [24] C. Y. Chung., T. S. Chung., C. W. Yu., X. J. Lin., Cost-based reactive power pricing with voltage security consideration in restructured power systems. Electrical Power Systems Research 70: 85-91 (2004).
• [25] Hao S., A reactive power management proposal for transmission operators. IEEE Transactions on Power Systems 18: 1374-1381 (2003).
• [26] Naresh Babu, A. V., Ramana T., Sivanagaraju S., Analysis of optimal power flow problem based on two stage initialization algorithm. International Journal of Electrical Power and Energy Systems 55: 91-99 (2014).
• [27] Niknam T., Narimani M. R., Aghaei J., Azizipanah-Abarghooee R., Improved particle swarm optimization for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index. IET Generation, Transmission & Distribution 6(6): 515-527 (2012).
• [28] Kennedy J., Eberhart R., Particle Swarm Optimization. IEEE International conference on Neural Networks 4: 1942-1948 (1995).
• [29] Dhillon J. S., Parti S. C, Kothari D. P., Stochastic economic emission load dispatch. Electric Power Systems Research 26: 179-186 (1993)
• [30] Vaisakh K., Praveena P., Rama Mohana Rao S., Kala Meah., Solving dynamic economic dispatch problem with security constraints using bacterial foraging PSO-DE algorithm. Electrical Power and Energy Systems 39: 56-67 (2012).
• [31] Kalyanmoy Deb., Samir Agarwal., Amrit Pratap., Meyarivan T., A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. Kanpur Genetic Algorithms Laboratory, IIT Kanpur.
• [32] Abido M. A., Optimal power flow using Tabu search algorithm. Electric Power Components and Systems 30: 469-483 (2002).
• [33] Alsac O., Stott B., Optimal Load Flow with steady state security. IEEE PES summer meeting and EHV/UHV conference, pp.745-751 (1973).
• [34] Arul R., Ravi G., Velsami S., Non-convex economic dispatch with heuristic load patterns, valve point loading effect, prohibited operating zones, ramp-rate limits, and spinning reserve constraints using harmony search algorithm. Electrical Engineering 95: 53-61 (2013).
• [35] Chanda Sandip., Abhinandan De., A multi-objective solution algorithm for optimum utilization of smart Grid infrastructure towards social welfare. Electrical Power and Energy Systems 58: 307-318 (2014).