A comprehensive supervisor control for a hybrid system that comprises wind and photovoltaic generation subsystems, a battery bank, and an ac load is developed in this paper. The objectives of the supervisor control are, primarily, to satisfy the load power demand and, second, to maintain the state of charge of the battery bank to prevent blackout and to extend the life of the batteries. For these purposes, the supervisor controller determines online the operation mode of both generation subsystems, switching from power regulation to maximum power conversion. Decision criteria for the supervisor based on measurable system variables are presented. Finally, the performance of the supervisor controller is extensively assessed through computer simulation using a comprehensive nonlinear model of the plant.

Abstract-A second-order sliding mode strategy to control the breathing subsystem of a polymer electrolyte membrane fuel cell stack for transportation applications is presented. The controller is developed from a design model of the plant derived from open literature, and well suited for the design of second-order sliding mode strategies. Stability issues are solved using a super twisting algorithm. The resulting approach exhibits good dynamic characteristics, being robust to uncertainties and disturbances. Simulations results are provided, showing the feasibility of the approach.

This work explores an adaptive second-order sliding mode control strategy to maximize the energy production of a wind energy conversion system (WECS) simultaneously reducing the mechanical stress on the shaft. Such strategy successfully deals with the random nature of wind speed, the intrinsic nonlinear behavior of the WECS, and the presence of model uncertainties and external perturbations acting on the system. The synthesized adaptive controller is designed from a modified version of the super-twisting (ST) algorithm with variable gains. The suitability of the proposed strategy is proved by extensive computer-aided simulations employing a comprehensive model of the system emulating realistic conditions of operation, i.e., considering variations in the parameters and including external disturbances. Additionally, a second controller based on the traditional ST algorithm is also designed and simulated. Results are presented and discussed in order to establish a comparison framework.

The work presented in this article combines experimental analysis and theoretical studies of temperature effects on the performance of an open-cathode, self-humidified PEM fuel cell system for the design of optimization strategies. The experimental analysis shows the great potential of improving the system performance by proper temperature management. The most significant temperature dependent parameters of the system under study are the activation polarization and the water content of the ionomer of the catalyst layer. An Extremum seeking control algorithm is proposed to regulate the temperature to a voltage maximum. However, the slow dynamics of the temperature related catalyst-drying effect on performance complicate the optimal thermal management via model-free control strategies.

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