A New Metaheuristic Inflation Data for Real & Reactive Power Generator Restraints

Authors

  • S. Parthiban Department of Electrical and Electronics Engineering, Nandha College of Technology, Erode Author
  • P. Karthikeyan Department of Electrical and Electronics Engineering, Nandha College of Technology, Erode. Author
  • P. Poongodi Department of Electrical and Electronics Engineering, Nandha College of Technology, Erode Author
  • P. Balamurugan Department of Electrical and Electronics Engineering, Nandha College of Technology, Erode Author

DOI:

https://doi.org/10.61841/pq7aze18

Keywords:

Economic Dispatch, Metaheuristic Methods, Chaotic PSO Algorithm, Power Generation Dispatch, Chaotic Sequences

Abstract

 To enhance the real and reactive power of the generator vary with in the certain limit and fulfills the load demand with less fuel cost, such as power balance. A divergent of the basic PSO method, is determined by incorporating chaotic sequences to enhance its consummanation. Two different example problems comprising 6 and 15 generating units are solved to demonstrate the effectiveness of the specific task. The results of CPSO are compared with GA and PSO techniques. The generation costs is lower, New method can result in great economic effect. For ELD problems, the CPSO method is more feasible and effective alternative approaches than the traditional particle swarm optimization algorithm 

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References

[1] Jabr Rabih A, Coonick Alun H, Cory Brian J. A homogeneous linear programming algorithm for the

security constrained economic dispatch problem. IEEE Transactions on Power Systems 2000;15(3):930–7.

[2] Fan JiYuan, Zhang Lan. Real-time economic dispatch with line flow and emission constraints using

quadratic programming. IEEE Transactions on Power Systems 1998;13(2):320–6.

[3] Nanda J, Hari Lakshman, Kothari ML. Economic emission load dispatch with line flow constraints using a

classical technique. IEE Proc Generat Transm Distrib 1994;141(1):1–10.

[4] Liang Zi Xiong, Glover Duncan. A zoom feature for a dynamic programming solution to economic

dispatch including transmission losses. IEEE Transactions on Power Systems 1992;7(2):544–7.

[5] Barcelo Wayne R, Rastgoufard Parviz. Dynamic economic dispatch using the extended security

constrained economic dispatch algorithm. IEEE Transactions on Power Systems 1997;12(2):961–7.

[6] Lee FN, Breipohl AM. Reserve constrained economic dispatch with prohibited operating zones. IEEE

Transactions on Power Systems 1993;8(1):246–9.

[7] El-Keib AA, Ma H, Hart JL. Environmentally constrained economic dispatch using the Lagrangian

relaxation method. IEEE Transactions on Power Systems 1994;9(4):1723–7.

[8] Walters David C, Sheble Gerald B. Genetic algorithm solution of economic dispatch with valve point

loading. IEEE Transactions on Power Systems 1993;8(3):1325–8.

[9] Bakirtzis A, Petridis V, Kazarlis S. Genetic algorithm solution to the economic dispatch problem. IEE

Proceedings on Generation, Transmission and Distribution 1994;141(4):377–82.

[10] [Chen Po Hung, Chang Hong Chan. Large-scale economic dispatch by genetic algorithm. IEEE

Transactions on Power Systems 1995;10(4):1919–26.

[11] Sheble Gerald B, Brittig Kristin. Refined genetic algorithm-economic dispatch example. IEEE

Transactions on Power Systems 1995;10(1):117–8.

[12] Su Ching Tzong, Chiou Gwo Jen. A fast-computation Hopfield method to economic dispatch of power

systems. IEEE Transactions on Power Systems 1997;12(4):1759–64.

[13] Yalcinoz T, Short MJ. Neural networks approach for solving economic dispatch problem with transmission

capacity constraints. IEEE Transactions on Power Systems 1998;13(2):307–13.

[14] Lin Whei Min, Cheng Fu Sheng, Tsay Ming Tong. Nonconvex economic dispatch by integrated artificial

intelligence. IEEE Transactions on Power Systems 2001;16(2):307–11.

[15] Eberhart Russell C, Kennedy James. Particle swarm optimization. IEEE International Conference on

Neural Networks 1995; vol. IV:1942–7.

[16] Nandagopal S., Arunachalam V.P., Karthik S."A novel approach for inter-transaction association rule

mining, Journal of Applied Sciences Research VOL, 8, Issue 7, 2012.

[17] Kannan R., Selvambikai M., Jeena Rajathy I., Ananthi S. Rasayan, A study on structural analysis of

electroplated Nano crystalline nickel based thin films, Journal of Chemistry, Vol 10, issue 4, 2017.

[18] Arunvivek G.K., Maheswaran G., Senthil Kumar S., Senthilkumar M., Bragadeeswaran T. Experimental

study on influence of recycled fresh concrete waste coarse aggregate on properties of concrete.

International Journal of Applied Engineering Research, Vol 10, issue 11, 2015

[19] Krishna S.K., Sathya M. Usage of nanoparticle as adsorbent in adsorption process. A review International

Journal of Applied Chemistry, vol 11, Issue 2, 2015.

[20] Sudha S., Manimegalai B., Thirumoorthy P. A study on routing approach for in-network aggregation in

wireless sensor networks, International Conference on Computer Communication and Informatics:

Ushering in Technologies of Tomorrow, Today, ICCCI 2014.

[21] Satheesh A., Jeyageetha V. Improving power system stability with facts controller using certain intelligent

techniques, International Journal of Applied Engineering Research, Vol 9, no 23, 2014.

[22] Ashok V., Kumar N, Determination of blood glucose concentration by using wavelet transform and neural

networks, Iranian Journal of Medical Sciences, Vol 38, Issue 1, 2013.

[23] Somasundaram K., Saritha S., Ramesh K, Enhancement of network lifetime by improving the leach

protocol for large scale WSN, Indian Journal of Science and Technology, Vol 9, Issue 16, 2016.

[24] Jayavel S., Arumugam S., Singh B., Pandey P., Giri A., Sharma A. Use of Artificial Intelligence in

automation of sequential steps of software development / production, Journal of Theoretical and Applied

Information Technology, Vol 57, Issue 3, 2013.

[25] Ramesh Kumar K.A., Balamurugan K., Gnanaraj D., Ilangovan S, Investigations on the effect of flyash on

the SiC reinforced aluminium metal matrix composites, Advanced Composites Letters, Vol 23, Issue 3,

2014.

[26] Suresh V.M., Karthikeswaran D., Sudha V.M., Murali Chandraseker D, Web server load balancing using

SSL back-end forwarding method. IEEE-International Conference on Advances in Engineering, Science

and Management, ICAESM-2012, 2012.

[27] Karthikeswaran D., Sudha V.M., Suresh V.M., Javed Sultan A, A pattern based framework for privacy

preservation through association rule mining, IEEE-International Conference on Advances in Engineering,

Science and Management, ICAESM-2012, 2012.

[28] Senthil J., Arumugam S., Shah P, Real time automatic code generation using generative programming

paradigm, European Journal of Scientific Research, vol. 78, issue 4, 2012.

[29] Vijayakumar J., Arumugam S, Certain investigations on foot rot disease for betelvine plants using digital

imaging technique, Proceedings - 2013 International Conference on Emerging Trends in Communication,

Control, Signal Processing and Computing Applications, IEEE-C2SPCA", 2013.

[30] Vijayakumar J., Arumugam S. Odium piperis fungus identification for piper betel plants using digital

image processing, Journal of Theoretical and Applied Information Technology, vol 60, issue 2, 2014.

[31] Manchula A., Arumugam S, Face and fingerprint biometric fusion: Multimodal feature template matching

algorithm, International Journal of Applied Engineering Research, vol 9, issue 22, 2014.

[32] Ramesh Kumar K.A., Balamurugan K., Arungalai Vendan S., Bensam Raj J, Investigations on thermal

properties, stress and deformation of Al/SiC metal matrix composite based on finite element method.

Carbon - Science and Technology, Vol 6, Issue 3, 2014.

[33] Kanchana A., Arumugam S, Palm print texture recognition using connected-section morphological

segmentation, Asian Journal of Information Technology Vol 6, Issue 3, 2014.

[34] Padmapriya R., Thangavelu P, Characterization of nearly open sets using fuzzy sets, Global Journal of

Pure and Applied Mathematics, vol 11, issue 1, 2015.

[35] P.B. Narandiran, T. Bragadeeswaran, M. Kamalakannan, V. Aravind, Manufacture of Flyash Brick Using

Steel Slag and Tapioca Powder. Jour of Adv Research in Dynamical & Control Systems, Vol. 10, No. 12,

2018, 527-532

[36] R. Girimurugan*, N. Senniangiri, K. Adithya, B. Velliyangiri, Mechanical Behaviour of Coconut Shell

Powder Granule Reinforced Epoxy Resin Matrix Bio Composites, Jour of Adv Research in Dynamical &

Control Systems, Vol. 10, No. 12, 2018, 533-541.

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Published

31.10.2019

How to Cite

Parthiban, S., Karthikeyan, P., Poongodi, P., & Balamurugan, P. (2019). A New Metaheuristic Inflation Data for Real & Reactive Power Generator Restraints. International Journal of Psychosocial Rehabilitation, 23(4), 1180-1186. https://doi.org/10.61841/pq7aze18