This paper proposes a new DC-DC converter. The DC-DC multilevel boost converter, based on one inductor, one switch, 2N-1 diodes and 2N-1 capacitor, for N levels plus the reference (total N+1 levels), is a boost converter able to control and maintain the same voltage in all the Nx output levels, and able to control the input current. This converter is based on the multilevel converters principle, and it is proposed to be used as DC-link in applications where several controlled voltage levels are needed with self balancing and unidirectional current flow, such as photovoltaic (PV) or fuel cell generation systems with multilevel inverters. Used to feed a multilevel inverter, the proposed topology achieves a self voltage balancing; experimental results prove the principle of the proposition.

Selective harmonics elimination (SHE) is a widely applied control strategy in multilvel inverters for harmonics reduction. SHE is designed for the elimination of low-order harmonics while keeping the fundamental component equal to any previously specified amplitude. This paper proposes a novel bio-inspired metaheuristic optimization algorithm called Black Widow Optimization Algorithm (BWOA) for solving the SHE set of equations. BWOA mimics the spiders’ different movement strategies for courtship-mating, guaranteeing the exploration and exploitation of the search space. The optimization results show the reliability of BWOA compared to the state-of-the-art metaheuristic algorithms and show competitive results as a microalgorithm, opening its future application for an on-line optimization calculation in low requirement hardware.

We introduce a new dc-dc converter topology with the following features: first, quadratic voltage gain, which allows the converter to work over a wide voltage range with a minimal variation of duty cycle and without the use of extreme duty cycles; second, output voltage ripple mitigation, which can be accomplished with respect to a fixed but otherwise arbitrary duty cycle by proper selection of components and switching signals. Since the proposed converter can be designed to have zero output voltage ripple for the nominal gain (duty cycle), this allows the use of small values of capacitances. The underlying principles and steady-state equations in continuous conduction mode are presented in detail. Experimental tests are presented to validate the analysis.

This study introduces an advanced DC–DC power converter with two main objectives, (i) to achieve a wide range of voltage gain, which means the converter may work over a wide range of input voltage for a fixed desired output voltage and (ii) to achieve a reduced input current ripple. Those features are highly desired in renewable energy applications, for example with photovoltaic panels and fuel cells. The proposed converter was designed in a structure in which the input voltage is composed by the difference of two inductor currents, the currents through inductors are driven with transistors that may have different duty cycle, this allows the current ripple cancellation. In addition, the structure of the converter provides a quadratic type voltage gain, which leads to a wide range of operation voltage. The converter achieves both the wire range of voltage gain and current ripple cancellation, nonetheless, the buck–boost capability is also provided. The input current ripple reduction helps preserve the renewable energy sources since they suffer deterioration when current with considerable ripple is drawn from them. Dynamic and steady‐state analysis are performed along with the components sizing. Simulation and experimental results are provided to demonstrate the principle of the proposition.

This paper presents a modification to the dingo optimization algorithm (mDOA) to solve the non-linear set of equations of the selective harmonic elimination (SHE) control technique widely applied in multilevel inverters. In addition, said modification is conducted to the survival criteria by including a local search to provide a better balance when replacing vectors (dingoes) with a low survival rate. The proposed method is also benchmarked with some unimodal functions to illustrate its better exploitation capabilities. Finally, the SHE optimization results were calculated and compared with three well-known state-of-the-art metaheuristics, where the modified version of the dingo optimization algorithm showed very competitive results. The significant difference between the mDOA results and the rest of the algorithms is determined by the Wilcoxon rank-sum non-parametric statistical test with a 5% degree of significance. The p-values confirm the meaningful advantage of the mDOA compared to other bio-inspired algorithms for many modulation indexes. Experimentally, the proposed algorithm is validated through the implementation of a three-phase 11-level inverter.