magazinelogo

Journal of Electrical Power & Energy Systems

ISSN Online: 2576-053X Downloads: 29209 Total View: 341099
Frequency: semi-annually ISSN Print: 2576-0521 CODEN: JEPEEG
Email: jepes@hillpublisher.com

Volumes & Issues

Current Issue

Article Open Access http://dx.doi.org/10.26855/jepes.2021.03.002

Real Power Loss Reduction by Hybridization of Tree-Seed Algorithm with Sine-Cosine Algorithm

Kanagasabai Lenin

Department of EEE, Prasad V. Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, Andhra Pradesh, India.

*Corresponding author: Kanagasabai Lenin

Published: March 15,2021

Abstract

In this work, real power loss has done through hybridized Tree-seed algorithm. Sine-cosine algorithm which has been combined with Tree-seed algorithm (HTS) is projected to solve the problem. Tree-seed algorithm is based on the relationship between trees and seeds. And Sine Cosine Algorithm is based on the functions of Sine and Cosine; it stimulates the leader variable agent solutions towards the most excellent solution. In this work, seed engendering mechanism has been enhanced through adaptive mode and with reference to the iterations a linearly (k) varying mechanism has been implemented to perk up the exploration and exploitation. With considering voltage stability index proposed hybridized Tree-seed algorithm (HTS) is tested in IEEE 30, bus system. Then, the Proposed hybridized Tree-seed algorithm has been tested in standard IEEE 14, 30, 57, 118, 300 bus test systems without considering the voltage stability index. In first analysis with considering voltage stability index real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained. In the second evaluation without considered voltage stability index, also power loss reduction achieved. Percentage of power loss reduction is 15.80%, 20.74%, 26.29%, and 14.55% with respect to the base value. Power Loss comparison has been done with other standard methods.

References

[1] K. Y. Lee. (1984). “Fuel-cost minimisation for both real and reactive-power dispatches,” Proceedings Generation, Transmission and Distribution Conference, 131(3), pp. 85-93. 

[2] N. I. Deeb. (1998). “An efficient technique for reactive power dispatch using a revised linear programming approach,” Electric Power System Research, 15(2), pp. 121-134. 

[3] M. R. Bjelogrlic, M. S. Calovic, B. S. Babic. (1990). “Application of Newton’s optimal power flow in voltage/reactive power control”, IEEE Trans Power System, vol. 5, no. 4, pp. 1447-1454.

[4] S. Granville. (1994). “Optimal reactive dispatch through interior point methods,” IEEE Transactions on Power System, 9(1), pp. 136-146. http://dx.doi.org/10.1109/59.317548.

[5] N. Grudinin. (1998). “Reactive power optimization using successive quadratic programming method,” IEEE Transactions on Power System, 13(4), pp. 1219-1225. http://dx.doi.org/10.1109/59.736232.

[6] Uğurarifoğlu and farukyalçin. (2018). System Constrained Active Power Loss Minimization in Practical Multi-terminal HVDC Systems through GA, Sakarya University Journal of Science, 10.16984/saufenbilder.421351, (1-1), (2018).

[7] Kamel, S., Abdel-Fatah, S., Ebeed, M., Yu, J., Xie, K. G., and Zhao, C. Y. (2019). Solving Optimal Reactive Power Dispatch Problem Considering Load Uncertainty. 10.1109/ISGT-Asia.2019.8881322.

[8] Biplab Bhattacharyya and Nihar Karmakar. (2019). Optimal Reactive Power Management Problem: A Solution Using Evolu-tionary Algorithms, IETE Technical Review. DOI: 10.1080/02564602.2019.1675541.

[9] S. Kamel, S. Abdel-Fatah, M. Ebeed, J. Yu, K. Xie, and C. Zhao. (2019). “Solving Optimal Reactive Power Dispatch Problem Considering Load Uncertainty,” 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), Chengdu, China, 2019, pp. 1335-1340, doi: 10.1109/ISGT-Asia.2019.8881322.

[10] T. M. Aljohani, A. F. Ebrahim, O. Mohammed Single. (2019). “Multiobjective Optimal Reactive Power Dispatch Based on Hybrid Artificial Physics-Particle Swarm Optimization”, Energies, 12(12), 2333; https://doi.org/10.3390/en12122333.

[11] Ram Kishan Mahate and Himmat Singh. (2019). Multi-Objective Optimal Reactive Power Dispatch Using Differential Evolution. International Journal of Engineering Technologies and Management Research, 6(2), 27-38. http://doi.org/10.5281/zenodo.2585477.

[12] Nguyen, ThangTrung, Vo, Dieu Ngoc. (n.d.). “Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives”. Neural Computing and Applications, VL-32, IS-10. https://doi.org/10.1007/s00521-019-04073-4.

[13] Yang, S., Wang, W., Liu, C., et al. Optimal reactive power dispatch of wind power plant cluster considering static voltage stability for low-carbon power system. J. Mod. Power Syst. Clean Energy3, 114–122 (2015). 

https://doi.org/10.1007/s40565-014-0091-x

[14] S. Emiroglu, Y. Uyaroglu, G. Ozdemir. (2017). “Distributed Reactive Power Control based Conservation Voltage Reduction in Active Distribution Systems,” Advances in Electrical and Computer Engineering, vol. 17, no. 4, pp. 99-106. doi:10.4316/AECE.2017.04012.

[15] Mojtaba Ghasemi, Mahdi Taghizadeh, Sahand Ghavidel, Jamshid Aghaei, Abbas Abbasian. (2015). “Solving optimal reactive power dispatch problem using a novel teaching-learning-based optimization algorithm”, Engineering Applications of Artificial Intelligence, Volume 39, pp. 100-108.

[16] Wei, Yan-Ling, Nguyen, Thang Trung, Vo, Dieu Ngoc, Van Tran, Hai, Van Dai, Le. (2019). “Optimal Dispatch of Reactive Power Using Modified Stochastic Fractal Search Algorithm”, Complexity, Hindaw, 1076-2787, 2019.

[17] A. Padilha-Feltrin, D. A. QuijanoRodezno, and J. R. S. Mantovani. (2015). “Volt-VAR Multiobjective Optimization to Peak-Load Relief and Energy Efficiency in Distribution Networks,” IEEE Transactions on Power Delivery, vol. 30, no. 2, pp. 618-626, Apr. 2015.

[18] Ghazavi Dozein, M., Monsef, H., Ansari, J., and Kazemi, A. (2016). An effective decentralized scheme to monitor and control the reactive power flow: a holonic‐based strategy. Int. Trans. Electr. Energ. Syst., 26: 1184-1209.

[19] S. D. Beigvand, H. Abdi, and M. La Scala. (2016). “Combined heat and power economic dispatch problem using gravitational search algorithm,” Electr. Power Syst. Res., 133, 160-172.

[20] N. Narang, E. Sharma, and J. S. Dhillon. (2017). “Combined heat and power economic dispatch using integrated civilized swarm optimization and Powell’s pattern search method,” Appl. Soft Comput., 52, 190-202.

[21] W. Warid, H. Hizam, N. Mariun, and N. I. A. Wahab. (2018). “A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution,” Applied Soft Computing Journal, Vol. 65, pp. 360-373, Apr. 2018. 

[22] O. Herbadji, L. Slimani, and T. Bouktir. (2017). “Multiobjective optimal power flow considering the fuel cost, emission, voltage deviation and power losses using multi-objective dragonfly algorithm”, International Conference on Recent Advances in Electrical Systems, pp. 191-197, 2017.

[23] K. Vaisakh, Member, IEEE, and P. Kanta Rao. (n.d.). “Optimum Reactive Power Dispatch Using Differential Evolution for Improvement of Voltage Stability”, 978-1-4244-1762-9/08/ C 2008 IEEE. 

[24] S. D. Chavan, Nisha P. Adgokar. (2015). “An Overview on Particle Swarm Optimization: Basic Concepts and Modified Vari-ants”. International Journal of Science and Research, Volume 4 Issue 5, May 2015, pp. 255-260.

[25] Nagendra, P., Halder Nee Dey, S., and Paul, S. (2014). “Voltage stability assessment of a power system incorporating FACTS controllers using unique network equivalent”, Ain Shams Eng. J., 5(1), 103-111. 

[26] Nagendra, P., Halder Nee Dey, S., and Paul, S. (2015). “Location of static VAR compensator in a multi-bus power system using unique network equivalent”, Adv. Energy Res., 3(4), 235-249.

[27] H. Zhang, X. Lei, C. Wang, D. Yue, and X. Xie. (2017). “Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty,” PLOS ONE, pp. 1-25, 29 September 2017. 

[28] K. N. Bindu and K. K. Kumar. (2016). “Combined Economic And Emission Dispatch Using Random Drift Particle Swarm Optimization,” International Journal for Modern Trends in Science and Technology, vol. 2, no. 11, pp. 134-139, November 2016.

[29] Rupa, J. M., Ganesh, S. (2014). Power flow analysis for radial distribution system using backward/forward sweep method. Inter J Electr, Comput, Electron Commun Eng., 8: 1540-1544. 

[30] Abdel-Akher, M. (2013). Voltage stability analysis of unbalanced distribution systems using backward/forward sweep load-flow analysis method with secant predictor. IET gener, transmdistrib., 7: 309-317.

[31] Prasad, B., C. D. Prasad, and G. P. Kumar. (2016). “Effect of load parameters variations on AGC of single area thermal power system in presence of integral and PSO-PID controllers,” 2015 Conf. Power, Control. Common. Compute. Technol. Sustain. Growth, PCCCTSG 2015, no. 1, pp. 64-68, 2016. 

[32] Javadmorsal, Kazemzare, Mehrdad Tarafdar Hagh. (2016). “Performance comparison of TCSC with TCPS and SSSC controllers in AGC of realistic interconnected multi-sources power system,” Elsevier, pp. 64-68, 2016.

[33] Uğurarifoğlu and Farukyalçin. (2018). System Constrained Active Power Loss Minimization in Practical Multi-terminal HVDC Systems through GA, Sakarya University Journal of Science, 10.16984/saufenbilder.421351, (1-1), (2018).

[34] Wei, H., Lin, C., and Wang, Y. (2018). The optimal reactive power flow model in mixed polar form based on transformer dummy nodes. IEEJ Trans Elec Electron Eng., 13: 411-416.

[35] Fang, S., Cheng, H., Xu, G., Zhou, Q., He, H., Zeng, P. (2017). Stochastic optimal reactive power reserve dispatch considering voltage control areas. Int. Trans. Electr. Energ. Syst., 2017; 27: e2269.

[36] Ghazavi Dozein, M., Monsef, H., Ansari, J., and Kazemi, A. (2016). An effective decentralized scheme to monitor and control the reactive power flow: a holonic‐based strategy. Int. Trans. Electr. Energ. Syst., 26: 1184-1209.

[37] Du, Z., Nie, Y., and Liao, P. (2014). PCPDIPM‐based optimal reactive power flow model using augmented rectangular coor-dinates. Int. Trans. Electr. Energ. Syst., 24: 597-608.

[38] Liu, B., Liu, F., Zhai, B., and Lan, H. (2019). Investigating continuous power flow solutions of IEEE 14‐bus system. IEEJ Trans Elec Electron Eng., 14: 157-159. 

[39] A. Panda, S. Pani. (2016). A symbiotic organisms search algorithm with adaptive penalty function to solve multi-objective constrained optimization problems, Appl. Soft Comput., 46(2016): 344-360.

[40] C. K. Shiva, V. Mukherjee. (2015). A novel quasi-oppositional harmony search algorithm for automatic generation control of power system, Appl. Soft Comput., 35(2015): 749-765.

[41] H. R. E. H. Bouchekara, M. Zellagui, and M. A. Abido. (2017). “Optimal coordination of directional overcurrent relays using a modified electromagnetic field optimization algorithm,” Applied Soft Computing, vol. 54, pp. 267-283, 2017.

[42] B. Talebi and M. N. Dehkordi. (2018). “Sensitive association rules hiding using electromagnetic field optimization algorithm,” Expert Systems with Applications, vol. 114, pp. 155-172, 2018.

[43] Becerra, V. Cooray. (2006). “A simplified physical model to determine the lightning upward connecting leader inception”, IEEE Trans. Power Deliv., 21, 897-908.

[44] M. Kiran. (2015). “TSA: tree-seed algorithm for continuous optimization”, Expert Syst. Appl., 42(19), 6686-6698.

[45] A. Babalik, A. Cinar, M. Kiran. (2018). A modification of tree-seed algorithm using Deb’s rules for constrained optimization. Appl. Soft Comput., 63(2018), 289-305. 

[46] M. Aslan, M. Beskirli, H. Kodaz, M. Kiran. (2018). An improved tree seed algorithm for optimization problems, Int. J. Mach. Learn. Comput., 8(1): 20-25.

[47] Jiang, J. H., Xu, M. R., Meng, Xian. Q., and Li, K. Q. (2019). STSA: A sine Tree-Seed Algorithm for complex continuous optimization problems. Physica A: Statistical Mechanics and its Applications. 537. 122802. 10.1016/j.physa.2019.122802.

[48] S. Mirjalili. (2016). SCA: a sine cosine algorithm for solving optimization problems. Knowledge-Based System, 96(2016), 120-133.

[49] Illinois Center for a Smarter Electric Grid (ICSEG). Available online: https://icseg.iti.illinois.edu/ieee-30-bussystem/ (accessed on 25 February 2019).

[50] El Ela, A. A., Abido, M. A., Spea, S. R. (2011). Differential evolution algorithm for optimal reactive power dispatch. Electr. Power Syst. Res., 2011, 81, 458-464.

[51] Duman, S., Sönmez, Y., Güvenç, U., Yörükeren, N. (2012). Optimal reactive power dispatch using a gravitational search algo-rithm. IET Gener. Transm. Distrib., 2012, 6, 563-576.

[52] Aljohani, T. M., Ebrahim, A. F., Mohammed, O. (2019). Single and Multiobjective Optimal Reactive Power Dispatch Based on Hybrid Artificial Physics-Particle Swarm Optimization. Energies, 2019, 12, 2333.

[53] Dai, C., W. Chen, Y. Zhu, and X. Zhang. (2009). Seeker optimization algorithm for optimal reactive power dispatch. IEEE T. Power Syst., 24(3): 1218-1231.

[54] Subbaraj, P. and P. N. Rajnarayan. (2009). Optimal reactive power dispatch using self-adaptive real coded Genetic algorithm. Electr. Power Syst. Res., 79(2): 374-38.

[55] Pandya, S. and R. Roy. (2015). Particle swarm optimization based optimal reactive power dispatch. Proceeding of the IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), pp. 1-5.

[56] Ali Nasser Hussain, Ali Abdulabbas Abdullah, and Omar Muhammed Neda. (2018). “Modified Particle Swarm Optimization for Solution of Reactive Power Dispatch”, Research Journal of Applied Sciences, Engineering and Technology 15(8): 316-327, 2018. DOI:10.19026/rjaset.15.5917.

[57] S. Surender Reddy. (2017). “Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm”, International Journal of Electrical and Computer Engineering, Vol. 7, No. 5, pp. 2349-2356. 

[58] S. S. Reddy. (2014). “Faster evolutionary algorithm based optimal power flow using incremental variables”, Electrical Power and Energy Systems, vol. 54, pp. 198-210.

How to cite this paper

Real Power Loss Reduction by Hybridization of Tree-Seed Algorithm with Sine-Cosine Algorithm

How to cite this paper: Kanagasabai Lenin. (2021) Real Power Loss Reduction by Hybridization of Tree-Seed Algorithm with Sine-Cosine Algorithm. Journal of Electrical Power & Energy Systems5(1), 8-23.

DOI: http://dx.doi.org/10.26855/jepes.2021.03.002