HYBRIDIZED PROSCOPIIDAE - MYRMELEONTIDAE AND PAMPAS FOX INSPIRED OPTIMIZATION ALGORITHM

Authors

  • Lenin Kanagasabai Prasad V. Potluri Siddhartha Institute Of Technology

DOI:

https://doi.org/10.55766/sujst-2024-02-e02690

Keywords:

Population, Hybridization, Fitness rate

Abstract

In this paper Hybridization of Proscopiidae Optimization with Myrmeleontidae Algorithm (PM) and Pampas Fox inspired optimization (PFO) algorithm are applied to solve the tangible power Loss reduction problem. Proscopiidae optimization algorithm integrated with Myrmeleontidae optimization algorithm. Proscopiidae certainly move idealistically up until it reach a protected region and projected algorithm owns good exploration ability. Myrmeleontidae optimization algorithm owns better exploitation. In the exploration space Proscopiidae interrelate each other and identical number of Myrmeleontidae will be there in the exploration. In exploitation segment, movement of the Pampas Fox is towards the direction of the prey’s sound. Population engendered randomly, partial iterations are applied in the exploration and exploitation segment. PM and PFO algorithms validated in IEEE 354 bus and 220 KV systems.

References

Venkataramana, A., Carr, J., and Ramshaw, R.S. (1987). Optimal Reactive Power Allocation. IEEE Power Engineering Review, 7(2):40-40. https://doi.org/10.1109/MPER.1987.5527548

El-Ela, A.A., Mouwafi, M., and Al-Zahar, W. (2019). Optimal Transmission System Expansion Planning Via Binary Bat Algorithm. 2019 21st International Middle East Power Systems Conference (MEPCON), 238-243. https://doi.org/10.1109/MEPCON47431.2019.9008022

Xiong, C., Liu, H., Yang, Z., and Wang, J. (2022). Optimal reactive power dispatch of distribution network considering voltage security. 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1,362-1,367. https://doi.org/10.1109/SSCI51031.2022.10022232

Chatellenaz, M.L., Muller, G.C., and Vallejos, G.A. (2018). Pampas foxes as prey of yellow anacondas. Canid Biology & Conservation, 21(1):1-3.

Sidea, D.O., Picioroaga, I.I., Tudose, A.M., Podar, C., Anton, N., and Bulac, C. (2022). Optimal reactive power dispatch considering load variation in distribution networks using an improved sine-cosine algorithm. 2022 International Conference and Exposition on Electrical And Power Engineering (EPE); 499-504, https://doi.org/10.1109/EPE56121.2022.9959076

Kumar, G.S., Chaitanya, S.N.V.S.K., Rao, V., and Bakkiyaraj, R.A. (2022). Optimal Reactive Power Dispatch solution accomplished with incorporation of Solar power using Harris Hawks Optimizer Algorithm. 2022 4th International Conference on Energy, Power and Environment (ICEPE). 1-6, https://doi.org/10.1109/ICEPE55035.2022.9798031

García, V.B. and Kittlein, M.J. (2005). Diet, habitat use, and relative abundance of pampas fox (Pseudalopex gymnocercus) in northern Patagonia, Argentina. Mammalian Biology, 70(4):218-226. https://doi.org/10.1016/j.mambio.2004.11.019

Lenin, K. (2022). Novel Western Jackdaw Search, Antrostomus Swarm and Indian Ethnic Vedic Teaching - Inspired Optimization Algorithms for Real Power Loss Diminishing and Voltage Consistency Growth. International Journal of System Assurance Engineering and Management, 13(6):2,895-2,919. https://doi.org/10.1007/s13198-022-01758-3

Rayudu, K., Yesuratnam, G., and Jayalaxmi, A. (2017). Ant colony optimization algorithm based optimal reactive power dispatch to improve voltage stability. 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT), 1-6. https://doi.org/10.1109/ICCPCT.2017.8074391

Kanagasabai, L. (2022). Jerusalem artichoke Algorithm for Power Loss Reduction and Voltage Stability Enhancement. International Journal of System Assurance Engineering and Management, 13(4):1,788-1,800. https://doi.org/10.1007/s13198-021-01550-9

Lai, L.L., Nieh, T.Y., Vujatovic, D., Ma, Y.N., Lu, Y.P., Yang, Y.W., and Braun, H. (2005). Swarm intelligence for optimal reactive power dispatch. 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific, 1-5. https://doi.org/10.1109/TDC.2005.1547197

Saddique, M.S., Habib, S., Haroon, S.S., Bhatti, A.R., Amin, S., and Ahmed, E.M. (2022). Optimal solution of reactive power dispatch in transmission system to minimize power losses using sine-cosine algorithm. IEEE Access: Practical Innovations, Open Solutions, 10:20,223-20,239. https://doi.org/10.1109/ACCESS.2022.3152153

Mohamed, T. (2022). Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm. Alexandria Engineering Journal, 61(2):1,383-1,401. https://doi.org/10.1016/j.aej.2021.06.021

Nagarajan, K., Parvathy, A.K., and Rajagopalan, A. (2020). Multi-objective optimal reactive power dispatch using Levy Interior Search Algorithm. International Journal on Electrical Engineering and Informatics, 12(3):547-570. https://doi.org/10.15676/ijeei.2020.12.3.8

Sahoo, P.P., Kumar, L., and Kumar, S. (2022). Optimal allocation of FACTS controller for Reactive Power Planning. 2022 4th International Conference on Energy, Power and Environment (ICEPE), 1-6, https://doi.org/10.1109/ICEPE55035.2022.9798167

Preedavichit, P. and Srivastava, S.C. (1997). Optimal reactive power dispatch considering FACTS devices. APSCOM-97. International Conference on Advances in Power System Control, Operation and Management. APSCOM-97. (Conf. Publ. No. 450), Hong Kong, 1997, pp. 620-625. https://doi.org/10.1049/cp:19971906

Raghuwanshi, B.S., and Shukla, S. (2019). Class imbalance learning using UnderBagging based kernelized extreme learning machine. Neurocomputing, 329:172-187. https://doi.org/10.1016/j.neucom.2018.10.056

Duman, S., Sönmez, Y., Güvenç, U., and Yörükeren, N. (2012). Optimal reactive power dispatch using a gravitational search algorithm. IET Generation, Transmission and Distribution, 6(6):563. https://doi.org/10.1049/iet-gtd.2011.0681

Sharif, S.S., Taylor, J.H., and Hill, E.F. (2002). On-line optimal reactive power flow by energy loss minimization. Proceedings of 35th IEEE Conference on Decision and Control. Kobe, Japan, 1996, pp. 3,851-3,856. https://doi.org/10.1109/CDC.1996.577262

Souhil M., and Bouktir, T. (2018). Multi-objective ant lion optimization algorithm to solve large-scale multi- objective optimal reactive power dispatch problem. The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 35:350-372.

Ibrahim, T., Del Rosso, A., Guggilam, S., Dowling, K., and Patel, M. (2022). EPRI-VCA: Optimal Reactive Power Dispatch Tool. 2022 IEEE Power & Energy Society General Meeting (PESGM). Denver, CO, USA, 2022, pp. 1-5. https://doi.org/10.1109/PESGM48719.2022.9917236

Trummal, T., Andreesen, G., and Kilter, J. (2020). Optimal Reactive Power Control in a Multi-Machine Thermal Power Plant. 2020 21st International Scientific Conference on Electric Power Engineering (EPE). Prague, Czech Republic, 2020, pp. 1-6, https://doi.org/10.1109/EPE51172.2020.9269239

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Published

2024-05-14

How to Cite

Kanagasabai , L. (2024). HYBRIDIZED PROSCOPIIDAE - MYRMELEONTIDAE AND PAMPAS FOX INSPIRED OPTIMIZATION ALGORITHM. Suranaree Journal of Science and Technology, 31(2), 010296(1–7). https://doi.org/10.55766/sujst-2024-02-e02690

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