An evolutionary based selective harmonic elimination method suitable for high power constant frequency converters used in renewable energy sources

Ever increasing power crisis,rapid depletion of fossil fuels and the pollution (due to power generation) forces engineering community to look for a green power by exploiting the renewable energy sources such as solar or wind power generation. Harnessing electrical energy from renewable sources is feasible if suitable high power converters/inverters are designed. However the high power converters/inverters introduce harmonics in the power grid as well as in the source. This proposed work addressed the problem of solving selective harmonic elimination pulse width modulation (SHE-PWM) for high power multilevel inverters in constant frequency utility grid. The big issues in solving the nonlinear transcdental equations are,it has multiple optimal solutions,the convergence and the initial guess of the exact solution is an up-hill task. This paper devised two evolutionary algorithms,the Real coded Genetic Algorithm (RGA) and differential evolution algorithm (DE) which results in reducing computational difficulties while the convergence is too fast. An objective function was formulated in such a way that it eliminates the selective harmonics effectively while controlling the fundamental component and it reduces the total harmonic distortion (THD) for different operating points. The theoretical calculations were verified using the simulation results and it was observed that DE results are far more superior to GA. © School of Engineering,Taylor’s University.