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International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.8, No.11, Nov. 2016

Multi-Objective Optimal Dispatch Solution of Solar-Wind-Thermal System Using Improved Stochastic Fractal Search Algorithm

Full Text (PDF, 781KB), PP.61-73


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Author(s)

Tushar Tyagi, Hari Mohan Dubey, Manjaree Pandit

Index Terms

Meta-heuristic;MOOD;TOPSIS;Fractals;Renewable energy

Abstract

This paper presents solution of multi-objective optimal dispatch (MOOD) problem of solar-wind-thermal system by improved stochastic fractal search (ISFSA) algorithm. Stochastic fractal search (SFSA) is inspired by the phenomenon of natural growth called fractal. It utilizes the concept of creating fractals for conducting a search through the problem domain with the help of two main operations diffusion and updating. To improve the exploration and exploitation capability of SFSA, scale factor is used in place of random operator. The SFSA and proposed ISFSA is implemented and tested on six different multi objective complex test systems of power system. TOPSIS is used here as a decision making tool to find the best compromise solution between the two conflicting objectives. The outcomes of simulation results are also compared with recent reported methods to confirm the superiority and validation of proposed approach.

Cite This Paper

Tushar Tyagi, Hari Mohan Dubey, Manjaree Pandit,"Multi-Objective Optimal Dispatch Solution of Solar-Wind-Thermal System Using Improved Stochastic Fractal Search Algorithm", International Journal of Information Technology and Computer Science(IJITCS), Vol.8, No.11, pp.61-73, 2016. DOI: 10.5815/ijitcs.2016.11.08

Reference

[1]J Nanda., D.P. Kothari, K.S Linga Murthy, “Economic emission load dispatch through goal programming techniques”, IEEE Trans. on Energy Conversion 3(1), (1988) 26-32 

[2]C Palanichamy, N.S Babu, “Analytical solution for combined economic and emissions dispatch”, Electric Power System Research 78, (2008) 1129–1137. 

[3]M Basu. “Economic environmental dispatch using multi-objective differential evolution”Applied Soft Computing 11, (2011) 2845–2853 

[4]M S Kaurav, H M Dubey, M Pandit, BK Panigrahi,Simulated annealing algorithm for combined economic and emission dispatch,in proc. IEEE Inter. Conf, ICACCN 2011,pp. 631-636.

[5]B.K Panigrahi, R.V.Pandi, S. Das, S.Das, “Multi-objective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatch problem” Energy 35, (2010) 4761-4770.

[6]N.Pandit, A. Tripathi, S.Tapaswi, M Pandit, “An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch”Applied Soft Computing 12, (2012) 3500–3513.

[7]P K Roy, Sudipta Bhui “Multi-objective quasi –oppositional teaching learning based optimization for economic   emission load dispatch problem”, Electrical Power and Energy systems:53(2013):937-948. 

[8]U. Güvenç, Y.Sönmez, S.Duman, N.Yörükeren, “Combined economic and emission dispatch solution using gravitational search algorithm” Scientia Iranica D vol.19 no.6 pp.1754–1762 (2012)

[9]K.Bhattacharjee, A.Bhattacharya, S.H.Dey “Solution of Economic Emission Load Dispatch   problems of power systems by Real Coded Chemical Reaction algorithm”, Electrical and Energy systems vol.59,pp.176-187,(2014)

[10]K.Bhattacharjee, A.Bhattacharya, S.H.Dey, “Backtracking search optimization based economic environmental power dispatch problems”. Electrical Power and Energy systems 73, 830-842. (2015)

[11]A J Wood, B F. Wallenberg, “Power Generation, Operation and Control”. 1984, New York: Wiley.

[12]J. Hetzer, D. C. Yu, K. Bhattarai, “An Economic Dispatch Model Incorporating Wind Power”, IEEE Trans. On Energy Conversion, vol. 23, no. 2, pp. 603-611, 2008.

[13]X. Liu, “Economic Load Dispatch Constrained by Wind Power Availability: A Wait-and-See Approach,” IEEE Trans. Smart Grid, vol.1, no.3, pp. 347-355, 2010.

[14]H. M Dubey., M.Pandit, B.K Panigrahi, “Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch”,Renewable Energy, 83,188-202 (2015).

[15]S. H. Karaki, R. B. Chedid, R. Ramadan, “Probabilistic Performance Assessment of Autonomous Solar-Wind Energy Conversion Systems”, IEEE Transactions on Energy Conversion, Vol. 14, No. 3, September 1999. pp. 766-772 

[16]H. Bilil, G. Aniba, M. Maaroufi, “Probabilistic Economic Emission Dispatch Optimization of Multi-Sources Power System”, Energy Procedia 50 (2014) 789 – 796. 

[17]M. Fadaee, M.A.M. Radzi, “Multi-objective Optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review”, Renewable and Sustainable Energy Reviews 16 (2012) 3364–3369.

[18]H.Salimi,“Stochastic fractal search: A powerful metaheuristic algorithm”, Knowledge based Systems 75,(2015) 1-18. 

[19]J Kiefer, "Sequential minimax search for a maximum", in Proceedings of the American Mathematical Society 4 (3), 1953, pp. 502–506.

[20]M.K. Deshmukh, S.S. Deshmukh, “ Modelling of hybrid renewable energy systems”, Renewable and Sustainable Energy Reviews 12 (2008) 235–249 

[21]Solar Radiation Hand Book (2008), A joint Project of Solar Energy Centre, MNRE Indian Metrological Department 

[22]K. Deb, “Multi objective optimization using evolutionary algorithms”, Jhon Wiley & Sons, 2001.

[23]C.L Hwang, K. Yoon, “Multiple attribute decision making: Method and applications”, Spinger-Verlag,New York,NY, 1981.

[24]M. Behzadian., S.K.Otaghsara., M.Yazdani, J. Ignatius, “A state of art survey of TOPSIS applications”, Expert system with application.39,13051-69  (2012) 

[25]A. Layeb, S. R. Boussalia, “A Novel Quantum Inspired Cuckoo Search Algorithm for Bin Packing Problem”, I.J. Information Technology and Computer Science,  4(5), 58-67, 2012.

[26]M. Orouskhani,Y. Orouskhani,“A Novel Cat Swarm Optimization Algorithm for Unconstrained Optimization Problems”, I.J. Information Technology and Computer Science, 5(11), 32-41, 2013.

[27]D.N. Le, “A New Ant Colony Optimization Algorithm Applied to Optimizing Centralized Wireless Access Network” I.J. Information Technology and Computer Science,6(4), 30-36,2014.