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In this work, a serial-parallel hybrid (SPH) power system formed by a Fuel Cell (FC), an Auxiliary Storage Device (ASD) and the current-controlled dc-dc converters responsible for the power management are realized by using the Digital Signal Controller (DSC) TMS32F28335. The main energy management goal is to transfer energy from the sources (FC or ASD) to the load while ensuring dc bus voltage regulation and high power conversion efficiency. In addition, a safe and reliable operation of the system has to be achieved. The selected converter and its controller features are: non-inverting voltage step up and step down, high efficiency, input and output currents regulation an low ripple values, and the ability to change from input to output current regulation loop, suddenly and smoothly, and vice versa. All these features allow it to be positioned in different FC system localizations and simplifies the design of the master control. Simulation and experimental results have been validated on a 48-V, 1200-W dc bus.

Robust control techniques for power converters are becoming more attractive because they can meet with most demanding control goals like uncertainties. In this sense, the Takagi-Sugeno (T-S) fuzzy controller based on linear matrix inequalities (LMI) is a linear control by intervals that has been relatively unexplored for the output-voltage regulation problem in switching converters. Through this technique it is possible to minimize the disturbance rejection level, satisfying constraints over the decay rate of state variables as well as the control effort. Therefore, it is possible to guarantee, a priori, the stability of the large-signal converters in a broad operation domain. This work presents the design of a fuzzy control synthesis based on a T-S fuzzy model for non-minimum phase dc-dc converters, such as boost and buck-boost. First, starting from the canonical bilinear converters expression, a Takagi-Sugeno (T-S) fuzzy model is obtained, allowing to define the fuzzy controller structure through the parallel distributed compensation technique (PDC). Finally, the fuzzy controller design based on LMIs is solved for the defined specification in close loop through MATLAB toolbox LMI. Simulations and experimental results of a 60 W prototype are presented to verify theoretical predictions.

The versatile buck-boost c interesting features, such as continuous i currents and ease of control in both step-u models. This paper addresses its use in low v applications where the nonlinear current sou characteristic of the PV module requires the in capacitor in the original power stage structure regulation of this additional input capacitor v considering a linear combination of the capa voltage error, and the integral of the volt switching function. The performance of the d that has been tested by simulation indicates th combined with a conventional maximum pow (MPPT) algorithm of perturb and observe type 978-1-4799-7800-7/15/$31.00 ©2015 IEEE

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This research study proposes a methodology based on data science to estimate the technical feasibility of implementing hybrid solar-wind power systems by calculating the plant factor, also known as capacity factor (CF). Data is gathered from the NOVALYNX 110-WS-18 weather station, between the years 2018 and 2020, to determine the energetic potential available for the Candelaria campus at the La Salle University (Colombia). A k-means data clustering algorithm, developed in Matlab, is applied over the following descriptors: time, solar radiation, wind speed, and temperature. The results show that the photovoltaic and wind power systems have a CF of 36.69% and 2.15%, respectively. It is concluded that it is technically feasible to implement a photovoltaic system at the La Salle University, but not a wind power system as it does not meet the minimum CF required.