A Smart Management Approach Investigation for Hybrid Autonomous Power System

A novel design of system management based on multi-agents approach applied to an autonomous hybrid power system is proposed and investigated. The system under study integrates few elements, some serve to provide power requirements, while the others used to store energy. Among these items, we can mention a Solar Power Source namely (SPS) which works as primary source to feed a DC electric load. The system integrates also a secondary power source namely Power Recovery Source (PRS) based on a fuel cell technology used to compensate the power deficit if required. More than two kinds of energy storage, the first called Hydrogen Generation Element (HGE) including a water electrolyzer to store the energy in hydrogen form, while the second uses an Ultracapacitor Element (UE) to store the energy in its electrical form. To reach the well functioning of the system in order to satisfy the load requirements whatever the facts, an intelligent energy management approach based on multi-agent modeling is implemented and verified. Hence, the reliability and the effectiveness of the applied management strategy, which allows the coordination between the different energy sources and protects the system against any fluctuation, are proved by the obtained results from Matlab/Simulink

Synthetic biology and microdevices : a powerful combination

Recent developments demonstrate that the combination of microbiology with micro-and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other technologies. In the last decade, there has been a shift from the optimization of the abiotic components, for example, the chip, to the improvement of the processing capabilities of cells through genetic engineering. The synthetic biology approach will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. To this end, the development of new genetic circuits has to be guided by computational design methods that enable to tune and optimize the circuit response. As the successful design of genetic circuits is highly dependent on the quality and reliability of its composing elements, intense characterization of standard biological parts will be crucial for an efficient rational design process in the development of new genetic circuits. Microengineered devices can thereby offer a new analytical approach for the study of complex biological parts and systems. By summarizing the recent techniques in creating new synthetic circuits and in integrating biology with microdevices, this review aims at emphasizing the power of combining synthetic biology with microfluidics and microelectronics

Adaptive online parameter estimation algorithm of PEM fuel cells

Since most of fuel cell models are generally nonlinearly parameterized functions, existing modeling techniques rely on the optimization approaches and impose heavy computational costs. In this paper, an adaptive online parameter estimation approach for PEM fuel cells is developed in order to directly estimate unknown parameters. The general framework of this approach is that the electrochemical model is first reformulated using Taylor series expansion. Then, one recently proposed adaptive parameter estimation method is further tailored to estimate the unknown parameters. In this method, the adaptive law is directly driven by the parameter estimation errors without using any predictors or observers. Moreover, parameter estimation errors can be guaranteed to achieve exponential convergence. Besides, the online validation of regressor matrix invertibility are avoided such that computation costs can be effectively reduced. Finally, comparative simulation results demonstrate that the proposed approach can achieve better performance than least square algorithm for estimating unknown parameters of fuel cells.Postprint (published version

Model-based analysis for the thermal management of open-cathode proton exchange membrane fuel cell systems concerning efficiency and stability

In this work we present a dynamic, control-oriented, concentrated parameter model of an open-cathode proton exchange membrane fuel cell system for the study of stability and efficiency improvement with respect to thermal management. The system model consists of two dynamic states which are the fuel cell temperature and the liquid water saturation in the cathode catalyst layer. The control action of the system is the inlet air velocity of the cathode air flow manifold, set by the cooling fan, and the system output is the stack voltage. From the model we derive the equilibrium points and eigenvalues within a set of operating conditions and subsequently discuss stability and the possibility of efficiency improvement. The model confirms the existence of a temperature-dependent maximum power in the moderate temperature region. The stability analysis shows that the maximum power line decomposes the phase plane in two parts, namely stable and unstable equilibrium points. The model is capable of predicting the temperature of a stable steady-state voltage maximum and the simulation results serve for the design of optimal thermal management strategies.Postprint (author's final draft

Modeling and Control for Smart Grid Integration of Solar/Wind Energy Conversion System

Performance optimization, system reliability and operational efficiency are key characteristics of smart grid systems. In this paper a novel model of smart grid-connected PV/WT hybrid system is developed. It comprises photovoltaic array, wind turbine, asynchronous (induction) generator, controller and converters. The model is implemented using MATLAB/SIMULINK software package. Perturb and observe (P&O) algorithm is used for maximizing the generated power based on maximum power point tracker (MPPT) implementation. The dynamic behavior of the proposed model is examined under different operating conditions. Solar irradiance, temperature and wind speed data is gathered from a grid connected, 28.8kW solar power system located in central Manchester. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for smart grid performance optimization

Nonlinear observation in fuel cell systems: a comparison between disturbance estimation and High-Order Sliding-Mode techniques

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper compares two Nonlinear Distributed Parameter Observers (NDPO) for the observation of a Proton Exchange Membrane Fuel Cell (PEMFC). Both NDPOs are based on the discretisation of distributed parameters models and they are used to estimate the state profile of gas concentrations in the anode and cathode gas channels of the PEMFC, giving detailed information about the internal conditions of the system. The reaction and water transport flow rates from the membrane to the channels are uncertainties of the observation problem and they are estimated throughout all the length of the PEMFC without the use of additional sensors. The first observation approach is a Nonlinear Disturbance Observer (NDOB) for the estimation of the disturbances in the NDPO. In the second approach, a novel implementation of a High-Order Sliding-Mode (HOSM) observer is developed to estimate the true value of the states as well as the reaction terms. The proposed observers are tested and compared through a simulation example at different operating points and their performance and robustness is analysed over a given case study, the New European Driving Cycle.Peer ReviewedPostprint (author's final draft

Biomimetic flow fields for proton exchange membrane fuel cells: A review of design trends

Bipolar Plate design is one of the most active research fields in Polymer Electrolyte Membrane Fuel Cells (PEMFCs) development. Bipolar Plates are key components for ensuring an appropriate water management within the cell, preventing flooding and enhancing the cell operation at high current densities. This work presents a literature review covering bipolar plate designs based on nature or biological structures such as fractals, leaves or lungs. Biological inspiration comes from the fact that fluid distribution systems found in plants and animals such as leaves, blood vessels, or lungs perform their functions (mostly the same functions that are required for bipolar plates) with a remarkable efficiency, after millions of years of natural evolution. Such biomimetic designs have been explored to date with success, but it is generally acknowledged that biomimetic designs have not yet achieved their full potential. Many biomimetic designs have been derived using computer simulation tools, in particular Computational Fluid Dynamics (CFD) so that the use of CFD is included in the review. A detailed review including performance benchmarking, time line evolution, challenges and proposals, as well as manufacturing issues is discussed.Ministerio de Ciencia, Innovación y Universidades ENE2017-91159-EXPMinisterio de Economía y Competitividad UNSE15-CE296

Energy Management Strategies in hydrogen Smart-Grids: A laboratory experience

As microgrids gain reputation, nations are making decisions towards a new energetic paradigm where the centralized model is being abandoned in favor of a more sophisticated, reliable, environmentally friendly and decentralized one. The implementation of such sophisticated systems drive to find out new control techniques that make the system “smart”, bringing the Smart-Grid concept. This paper studies the role of Energy Management Strategies (EMSs) in hydrogen microgrids, covering both theoretical and experimental sides. It first describes the commissioning of a new labscale microgrid system to analyze a set of different EMS performance in real-life. This is followed by a summary of the approach used towards obtaining dynamic models to study and refine the different controllers implemented within this work. Then the implementation and validation of the developed EMSs using the new labscale microgrid are discussed. Experimental results are shown comparing the response of simple strategies (hysteresis band) against complex on-line optimization techniques, such as the Model Predictive Control. The difference between both approaches is extensively discussed. Results evidence how different control techniques can greatly influence the plant performance and finally we provide a set of guidelines for designing and operating Smart Grids.Ministerio de Economía y Competitividad DPI2013-46912-C2-1-