Alejandro J. del Real

Real-Time Implementation of a Constrained MPC for Efficient Airflow Control in a PEM Fuel Cell

Fuel cells represent an area of great industrial interest due to the possibility to generate clean energy for stationary and automotive applications. It is clear that the proper performance of these devices is closely related to the kind of control that is used; therefore, a study of improved control alternatives is fully justified. The air-supply control is widely used to guarantee safety and to achieve a high performance. This paper deals with this control loop, proposing and comparing two control objectives aimed at satisfying the oxygen starvation avoidance criterion and the maximum efficiency criterion, respectively. The control architecture is based on a constrained explicit model predictive control (MPC) law suitable for real-time implementation due to its low computational demands. The proposed controller is implemented and evaluated on a 1.2-kW polymer electrolyte membrane or proton exchange membrane fuel-cell test bench, thus obtaining real data which show that the maximum efficiency criterion does not conflict with the starvation avoidance criterion and allows system performance improvements of up to 3.46%. Moreover, experimental results utilizing the explicit MPC approach also show improved transient responses compared to those of the manufacturers control law.

An Integrated Framework for Distributed Model Predictive Control of Large-Scale Power Networks

This work proposes a novel integrated framework in order to model, simulate, and optimize potentially large-scale and complex networks, fusing an extended network modeling methodology and distributed model predictive control structures based on Lagrange multipliers. In concrete, a revised network modeling formulation is utilized, allowing extended networking capabilities with a novel, generic, and compact way of organizing network topology information. This optimization framework offers a number of very convenient features: distribution of the overall network control effort among the local agents; no overall network knowledge required; the introduction/elimination of a node only affects to its neighbors. Thus, this integrated framework offers a powerful and easy-to-use mathematical tool in order to analyze and manage a wide variety of todays large-scale network. Specifically, this methodology is applied here to a power network to show the benefit of the work developed.

Water Management in PEM Fuel Cells: Controllability Analysis and Steady-state Optimization for Temperature Control

Abstract This paper presents a controllability study of the water management inside anode channel by regulating the stack temperature for PEM fuel cell systems with dead-ended anode. Moreover, this work includes the design of a steady-state target optimizer which calculates the temperature set-point profiles that minimize the stack degradation and the hydrogen leaks. The control architecture is successfully simulated and the results show promising performance.

A risk-based strategy for power system optimization

This paper introduces a risk-based method to optimize the planning of power systems. This works uses the formulation of Energy Hub previously presented in the literature, as an interface among energy producers, consumers and the transportation infrastructure. Risk factors such as demands, operating and maintenance cost or power cost are considered in the optimization of the system. Mitigation actions reduce the risk impacts that may affect the system. A model predictive control approach is used to optimize the demand satisfaction and to determine the set of mitigation actions to be executed. An example of a hybrid storage system is considered. In particular, the architecture incorporates a wind generator, a Combined Heat and Power Plant (CHPP) and an intermediate hydrogen storage. A set of possible risks has been identified in the system in order to select the mitigation actions that reduce the impacts of these risks. Different simulations are executed to illustrated the benefits of the proposal.