System Constrained Active Power Loss Minimization in Practical Multi-terminal HVDC Systems through GA

Year 2018, Volume: 22 Issue: 4, 1163 - 1173, 01.08.2018

Faruk Yalçın , Uğur Arifoğlu

https://doi.org/10.16984/saufenbilder.421351

Cited By: 3

Abstract

In this paper, a novel optimal reactive power flow solution approach in
multi-terminal HVDC (High Voltage Direct Current) systems is studied. ULTCs’
(under load tap changer transformers) full equivalent model for the DC
converters’ are taken into account in the proposed AC-DC power unlike the
similar studies in the literature. Thus, the proposed study provides real
accurate results for practical AC-DC applications. Optimal reactive power flow
for minimum active power loss is provided by Genetic Algorithm (GA). For the
test of the proposed study, the IEEE 14-bus test system modified to AC-DC
system is used in the study. The obtained test results prove that the proposed GA
based optimization method is effective to reach the global optimum point of
minimum active power loss without dropping to local minimum point through
satisfying system constraints.

Keywords

active power loss minimization, HVDC, multi-terminal, ULTC, genetic algorithm

References

• [1] H. Wei, C. Lin and Y. Wang, “The optimal reactive power flow model in mixed polar form based on transformer dummy nodes”, IEEJ Transactions on Electrical and Electronic Engineering, vol. 13, no. 3, pp. 411–416, 2018.
• [2] Y.A. Mobarak, “Modified load flow analysis for integrated ac/dc power systems”, 12th Int. Middle East Power Syst. Conf. MEPCON, pp. 481–484, 2008.
• [3] J.R. De Silva and C.P. Arnold, “A simple improvement to sequential ac/dc power flow algorithms”, International Journal of Electrical Power & Energy Systems, vol. 12, no. 3, pp. 219–221, 1990.
• [4] U. Arifoglu, “Load flow based on newton's method using norton equivalent circuit for ac-dc multiterminal systems”, European Transactions on Electrical Power, vol. 9, no. 3, pp. 167–174, 1999.
• [5] D. Thukaram and G. Yesuratnam, “Optimal reactive power dispatch in a large power system with ac-dc and FACTs controllers”, IET Generation Transmission & Distribution, vol. 2, no. 1, pp. 71–81, 2008.
• [6] D. Thukaram, G. Yesuratnam, and C. Vyjayanthi, “Optimal reactive power dispatch based on voltage stability criteria in a large power system with ac/dc and FACTs devices”, IEEE Int. Conf. Power Electro. Drives Energy Syst. PEDES, 2006.
• [7] J. Yu, W. Yan, W. Li and L. Wen, “Quadratic models of ac-dc power flow and optimal reactive power flow with HVDC and UPFC controls”, Electric Power Systems Research, vol. 78, no. 3, pp. 302–310, 2008.
• [8] J. Yu, W. Yan, W. Li, C.Y. Chung and K.P. Wong, “An unfixed piecewise-optimal reactive power-flow model and its algorithm for ac-dc systems”, IEEE Transactions on Power Systems, vol. 23, no. 1, pp. 170–176, 2008.
• [9] U. De Martinis, F. Gagliardi, A. Losi, V. Mangoni and F. Rossi, “Optimal load flow for electrical power systems with multiterminal HVDC links”, IEE Proceedings Generation Transmission and Distribution, vol. 137, no. 2, pp. 139–145, 1990.
• [10] C.N. Lu, S.S. Chen and C.M. Ong, “The incorporation of HVDC equations in optimal power flow methods using sequential quadratic programming techniques”, IEEE Transactions on Power Systems, vol. 3, no. 3, pp. 1005–1011, 1988.
• [11] H. Ambriz-Perez, E. Acha and C.R. Fuerte-Esquivel, “High voltage direct current modelling in optimal power flows”, International Journal of Electrical Power & Energy Systems, vol. 30, no. 3, pp. 157–168, 2008.
• [12] U. Arifoglu and N. Tarkan, “New sequential ac-dc load-flow approach utilizing optimization techniques”, European Transactions on Electrical Power, vol. 9, no. 2, pp. 93–100, 1999.
• [13] K. Ayan and U. Kilic, “Artificial bee colony algorithm solution for optimal reactive power flow”, Applied Soft Computing, vol. 12, no. 5, pp. 1477–1482, 2012.
• [14] Y. Kabalci, “An improved approximation for the Nakagami-m inverse CDF using artificial bee colony optimization”, Wireless Networks, vol. 24, no. 2, pp. 663–669, 2018.
• [15] L. Wang and L. Li, “A coevolutionary differential evolution with harmony search for reliability-redundancy optimization”, Expert Systems with Applications, vol. 39, no. 5, pp. 5271–5278, 2012.
• [16] M. Gomez-Gonzalez, A. Lopez and F. Jurado, “Optimization of distributed generation systems using a new discrete PSO and OPF”, Electric Power Systems Research, vol. 84, no. 1, pp. 174–180, 2012.
• [17] O.P. Verma, P. Kumar, M. Hanmandlu and S. Chhabra, “High dynamic range optimal fuzzy color image enhancement using artificial ant colony system”, Applied Soft Computing, vol. 12, no. 1, pp. 394–404, 2012.
• [18] U. Guvenc, B.E. Altun and S. Duman, “Optimal power flow using genetic algorithm based on similarity”, Energy Education Science and Technology Part A: Energy Science and Research, vol. 29, no. 1, pp. 1–10, 2012.
• [19] M.S. Kumari and S. Maheswarapu, “Enhanced genetic algorithm based computation technique for multi-objective optimal power flow solution”, International Journal of Electrical Power & Energy Systems, vol. 32, no. 6, pp. 736–742, 2010.
• [20] F. Yalcin and U. Arifoglu, “Inserting the tap values of the tap changer transformers into the Jacobian matrix as control variables”, Sakarya University Journal of Science, vol. 17, no. 3, pp. 337–348, 2013.
• [21] J.H. Holland, Adaptation in Natural and Artificial Systems, Michigan: University of Michigan Press, 1975.
• [22] MATLAB Optimization Toolbox 5 User’s Guide (2012) The Math Works, Inc.
• [23] Ugur Arifoglu, “Optimal power flow using sequential power flow approach for an ac-dc power system”, Ph. D. thesis, Istanbul Technical University, Istanbul, 1993.