Moth flame optimisation for optimal power flow in a power system with static var compensator

P. Meenakshi; G. V. Nagesh Kumar; Vempalle Rafi; S. Hussain Vali; T. Obulesu; K. Ravisankar

Author(s)

P. Meenakshi Department of Electrical and Electronics Engineering JNTUA College of Engineering Pulivendula,Kadapa,India

G. V. Nagesh Kumar Department of Electrical and Electronics Engineering JNTUA College of Engineering Pulivendula,Kadapa,India

Vempalle Rafi Department of Electrical and Electronics Engineering JNTUA College of Engineering Pulivendula,Kadapa,India

S. Hussain Vali Department of Electrical and Electronics Engineering JNTUA College of Engineering Pulivendula,Kadapa,India

T. Obulesu Department of Electrical and Electronics Engineering JNTUA College of Engineering Pulivendula,Kadapa,India

K. Ravisankar Department of Electrical and Electronics Engineering JNTUA College of Engineering Pulivendula,Kadapa,India

Abstract

It consequently becomes imperative in the current transmission networks to make full use of existing resources and to rapidly transition to renewable energy alternatives. Electrical energy end users also benefit from effective resource utilisation since it lowers the price they pay for electricity. In this work, we offer a multi-objective optimum power flow (OPF) for an integrated gearbox network where FACTS devices are present. The paper's originality lies in the use of a multi-objective function. Minimising voltage variation, power loss, and negative social welfare (NSW) are all part of the objective function. The abatement of loss and NSW guarantees the lowering of per-unit pricing of power at the consumer end resulting in improved customer satisfaction. The problem was fixed using a FACTS Static var compensator. The theory was tested using an IEEE 30 bus network. The objective function has been optimised using the Mouth Flame Optimisation Algorithm. Detailed presentations, comparisons, and analyses of the collected findings have been made.

Publication Details

Page(s) 189-195

DOI DOI not available

Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 19, Issue: 3, Year: 2024

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Keywords

Optimal Power Flow (OPF), moth flame optimization (MFO), static var, negative social welfare (NSW)

References

Ayan K.,Kiliç U. .2012 .Artificial bee colony algorithm solution for optimal reactive power flow. Appl Soft Comput J, 12(5) : 1477-1482.

Shaw B.,Mukherjee V.,Ghoshal S. P. .2014 .Solution of reactive power dispatch of power networks by an opposition-based gravitational search algorithm. Int J Electr Power Energy Syst, 55 : 29-40.

Sulaiman M. H.,Mohamed Z.,Aliman M. R.,O. M. R. .2015 .Using the gray wolf optimizer for solving optimal reactive power dispatch problems. Appl. Soft Comput J, 32 : 286-292.

Khazali A. H.,Kalantar M. .2011 .Optimal reactive power dispatch based on the harmony search algorithm. Int. J Electr Power Energy Syst, 33(3) : 684-692.

Sulaiman M. H.,Ing W. L.,Mustaffa Z.,Mohamed M. R. .2015 .Grey wolf optimizer for solving economic dispatch problem with valve-loading effects. ARPN J Eng Appl Sci, 10(21) : 9796-9801.

Sulaiman M. H.,Rashid Z.,Daniyal M. I. M.,H. M. I. M. .2018 .Economic dispatch solution using moth-flame optimization algorithm. In: MATEC web of conferences, 214 : .

Park J-B,Jeong Y-W,Lee W-N,Shin J-R. .2008 .An improved particle swarm optimization for economic dispatch problems with non-smooth cost functions. , 20(1) : 7.

Chen P-H,Chang H-C. .2002 .Large-scale economic dispatch by genetic algorithm. IEEE Trans Power Syst, 10(4) : 1919-1926.

Taha I. B. M.,Elattar E. E. .2018 .Optimal reactive power resources sizing for power network operations enhancement based on improved grey wolf optimiser. IET Gener Transm Distrib, 12(14) : 3421-3434.

Attia A. F.,El Sehiemy R. A.,Hasanien H. M. .2018 .Optimal power flow solution in power networks using a novel Sine-Cosine algorithm. Int. J Electr Power Energy Syst, 99 : 331-343.

Duman S.,Güvenç U.,Sönmez Y.,Yörükeren N. .2012 .Optimal power flow using a gravitational search algorithm. Energy Convers Manag, 59 : 86-95.

Abido M. A. .2002 .Optimal power flow using particle swarm optimization. Int J Electr Power Energy Syst, 24(7) : 563-571.

Abdel-Fatah S.,Ebeed M.,Kamel S. .2019 .Optimal reactive power dispatch using modified sine cosine algorithm. ITCE, : 510-514.

Mirjalili S. .2015 .Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-based networks. 89, : 228-249.

Yang W.,Zhu W.,Du B.,Wang H.,Xu L.,Xie C.,Shi Y. .2023 .In the present work the microwave assisted oxidative desulfurization (ODS) of model light fuel oil in a helical coil reactor was investigated experimentally and numerically. Automotive waste heat recovery. Energy, 128400 : .

Zand M.,Nasab M. A.,Padmanaban S.,Maroti P. K.,Muyeen S. M. .2023 .To improve the power generation efficiency of the ATEG in automobiles, a scheme is proposed to use a silicone polymer-based thermal conductive oil to transfer heat from the exhaust. Based on this concept, a new type of concentric tube heat exchanger is designed. Energy Reports, 10 : 431-438.

Chen S.,Hu M.,Lei Y.,Kong L. .2023 .This paper expresses economic flexible-securable operation (EFSO) in smart distribution networks (SDNs), including distributed generation and storage networks to produce green energy. Applied Energy, 121557 : .

Dehghan M.,Zadeh Bagheri M.,Kiani M. J.,Negation S. .2023 .The traditional fuel locomotive is the primary type of locomotive currently in operation on non-electrified railways; however, it presents certain disadvantages including a low efficiency and high fuel consumption. Virtual power plants planning in the distribution network constrained to network resiliency under extreme weather events. Energy Reports. 9, : 4243-4256.

Vempalle Rafi Vempalle,Dhal P. K.,Rajesh M.,Srinivasan D. R.,M. Chandrashekhar N. D. R. .2023 .Madhava Reddy, Optimal placement of time-varying distributed generators by using crow search and black widow - Hybrid optimization. Measurement: Sensors, 30 : .

Vempalle Rafi,Dhal P. K. .2020 .Loss Minimization by Reconfiguration along with Distributed Generator Placement at Radial Distribution System with Hybrid Optimization Techniques, Technology and Economics of Smart Grids and Sustainable Energy. , 5 : .