Numerical Optimization of Switching Ripples in the Double Dual Boost Converter through the Evolutionary Algorithm L-SHADE

Abstract

Power-electronics based converters are essential circuits in renewable energy applications such as electricity generated with photovoltaic panels. The research on the field is getting increasing attention due to climate change problems and their possible attenuation with the use of renewable energy. Mathematical models of the converters are being used to optimize several aspects of their operation. This article is dedicated to optimizing (through the mathematical model and an evolutionary algorithm) the operation of a state-of-the-art converter. The converter, which is composed of two parts or phases, is controlled by pulse width modulation with two switching signals (one for each phase). The converter provides by itself low switching ripple in both the output voltage and the input current, which is beneficial for renewable energy applications. In the traditional operation, one of the switching signals has an algebraic dependence on the other one. This article proposes a new way to select the duty cycle for both signals. In the proposed method, duty cycles of both phases are considered independent of each other; this provides an extra degree of freedom; on the other hand, this produce that the possible combinations of duty cycles which produce a certain voltage gain is infinite, it becomes a problem with infinite possible solutions. The proposed method utilizes the a linear success-history based adaptive differential evolution with linear population reduction, also called L-SHADE algorithm for simplicity, to find the two duty cycles that achieve the desired voltage gain and to minimize the converters switching ripple. The obtained results are compared with the former operation of the converter; the proposed operation achieves a lower output voltage ripple while achieving the desired operation (voltage gain).