COMPARATIVE STUDY OF HEURISTIC OPTIMIZATION TECHNIQUES (HOTS) FOR ENERGY EFFICIENT INDUCTION MOTOR DESIGN

Three-phase induction motors are widely used in domestic, commercial and industrial applications. On an average, the energy consumed by an induction motor during its life cycle is 60–100 times the initial cost of the motor. Even a small percentage of efficiency increase will result in a significant energy conservation and economic impact. A comparative study of heuristic optimization techniques (HOTs) has been carried out for energy efficient induction motor design (EEIMD) problem considering the active power loss effect to ensure the minimum manufacturing and annual power loss costs. The objective of this paper is to minimize the total manufacturing and annual power loss costs. In this paper, various HOTs such as genetic algorithm (GA), particle swarm optimization (PSO), and exchange market algorithm (EMA) have been applied to obtain EEIMD solutions. The proposed algorithms have been applied on designing the two sample motors. In comparison with the solution quality and execution time obtained by the HOTs, the EMA seems to be a promising technique to solve EEIMD problems. Index Terms Energy efficient motor, evolutionary algorithm, genetic algorithm, heuristic optimization techniques. NOMENCLATURE Misc, Mist core and tooth iron masses in stator (Kg) Mirc, Mirtb, Mirtt core, tooth bodies and tooth tips iron masses in rotor (Kg) Mb, Mer, Msc bars, end rings and stator conductor copper masses (Kg) pisc, pist specific iron loss of stator core and tooth (W/Kg) Pisc, Pist core and teeth iron power loss in stator (W) Pb, Per, Psc bars, end rings and stator conductors copper power losses (W) Pf, Ps friction and stray power losses (W) Ksr, Kss rotor and stator slot copper insulating factors δr rotor current densities (A/mm) p number of poles T motor running time per year (hr) α annual rate of interest and depreciation η full-load efficiency W rated power (W) Ker end ring non-uniformity current distribution factor Wc, Wi copper and iron specific masses (Kg/m) ρs, ρr stator and rotor copper resistivities (Ω.m) Ki iron insulation factor Kj end ring to bar current density ratio f supply frequency (Hz) Nr, Ns rotor and stator number of slots cc, ci specific copper and iron material costs (Rs/Kg) ce specific energy loss cost (Rs/Wh) cp specific power loss cost (Rs/W) drc rotor core depth (m) drs rotor slot opening depth (m) wrs rotor slot opening width (m) Di rotor inner diameter (m) Do stator outer diameter (m) Dr rotor diameter (m) L gross iron length (m) Li active iron length (m) m number of particles in the swarm N number of dimensions in a particle K pointer of iterations (generations) Vi, n k velocity of particle i at iteration k W weighting factor C 1, C2 acceleration factor rand j random number between 0 and 1 © 2017 IJRAR July 2017, Volume 4, Issue 3 www.ijrar. org (E-ISSN 2348-1269, PISSN 2349-5138) IJRAR19D1017 International Journal of Research and Analytical Reviews (IJRAR) www.ijrar. org 148 X i, n k current position of particle i at iteration k pbest i personal best of particle i gbest global best of the group W max final weight factor W min initial weight factor Iter current iteration number Iter max maximum iteration number ni n person of the first group nj n person of the second group r random number within [0, 1] j member of the second group members of the first group members of the second group r1 and r2 random numbers nk n member of the third group k member of the third group and Sk share variation of the kth member of the third group share value added randomly to some shares total shares of member t shares of the t member information of exchange market risk level for each member of the second group number of the t member in exchange market number of the last member in exchange market, l is a constant coefficient for each member g1 common market risk amount , maximum and minimum values of risk in market respectively share value added randomly to some shares random number between -0.5 and 0.5 market variable risk in third group