A semi-empirical multipurpose steady-state model of a fuel cell for household appliances

2013 International Conference on Renewable Energy Research and Applications (ICRERA)

et al. 2013

Self Cite

Today, energy harvesting is drawing a great deal of attention due to modern trends in energy saving and sustainable development purposes. Among renewable energy sources fuel cells and photovoltaic arrays are the most promising for a wide variety of applications, ranging from few mWatts of wireless sensor networks to kWatts for household appliances. Coupling several harvesters and renewable sources is the winning strategy to ensure a proper supply overcoming the uncertainty and limited availability of common harvesters and renewable sources. Multisource energy harvesting is actually an open research topic involving several pressing and often conflicting requirements. System cost, complexity, size and efficiency are only a few performance indicators. In this paper, a multi-input, singleinductor architecture is proposed. A practical implementation is proposed as an example. Benefits brought by the proposed architecture over existing solutions are widely investigated. Design guidelines are given and simulation results are presented to test the efficiency of the proposed architecture.

Section: Introductionmentioning

confidence: 99%

A multi-input, single-inductor power system for multisource energy harvesting

Boscaino

Ferraro

2013 International Conference on Renewable Energy Research and Applications (ICRERA)

et al. 2013

Self Cite

“…Because of the continuous proliferation of high power nonlinear loads and distributed generation systems [1][2][3][4][5][6][7], the characteristics of the supplied voltages and currents are more and more altered respect to the rated ones.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty evaluation in the measurements for the electric power quality analysis

Cipriani

2013 International Conference on Renewable Energy Research and Applications (ICRERA)

Spataro

2013

The paper deals with the uncertainty estimation in the measurements performed to assess the electric power quality. In a first steps, according to the 'ISO - Guide to Expression of the Uncertainty in Measurements' all the error sources, which give a significant contribution to the combined uncertainty associated to the measurement results, are identified. Successively, in order to analyze how the errors propagate through the measurement chain, a Monte Carlo based approach is proposed. The method exploits an ad-hoc developed simulator of the measurement process, which takes into account the particular way of propagation of all the identified error sources. Eventually, with the aim of validate the proposed approach, the results of a series of experimental tests are presented. © 2013 IEEE

“…Manufacturers' data do not usually include such parameters that are not readily measured in an electronic laboratory. To overcome the drawbacks of analytical approaches, tunable parameters and related identification procedures based on experimental data are introduced by analytical, semi-empirical approaches [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. The complexity and computational cost of analytical models is usually high, and the best-suited environment to simulate is MATLAB/ Simulink.…”

Section: Introductionmentioning

confidence: 99%

Comparison of models of fuel cells based on experimental data for the design of power electronics systems

Boscaino

Capponi

IET Renewable Power Generation

et al. 2015

Fuel cells have a key role in the potential provision of combined generation of heat and power. Sophisticated power management algorithms have been developed to reduce hydrogen consumption. An accurate analysis of the interaction between the fuel cell system and the front-end power converter is fundamental to achieving high performances. Accurate modelling of the entire system is required, especially the primary energy source, including the auxiliary components. Fuel cell modelling techniques have been presented extensively in the literature. Models are usually oriented to give technical insight concerning the fuel cell systems. The importance of fuel cell modelling in the design and control of front-end power converters seldom has been addressed, and this has led to highly complex model structures and the need to assume the values of several parameters that cannot be measured easily in a power electronics laboratory. Such models are not well suited for designing renewable energy systems. Hence, semiempirical models oriented to the design of power systems are presented and compared. Both white-box and black-box modelling approaches are presented, and both models were tested on a 5-kW commercial fuel cell system provided by Nuvera. Both modelling approaches were validated comparing the simulation and experimental results.