Abstract: This paper unifies power optimization approaches in
various energy converters, such as: thermal, solar, chemical, and
electrochemical engines, in particular fuel cells. Thermodynamics
leads to converter-s efficiency and limiting power. Efficiency
equations serve to solve problems of upgrading and downgrading of
resources. While optimization of steady systems applies the
differential calculus and Lagrange multipliers, dynamic optimization
involves variational calculus and dynamic programming. In reacting
systems chemical affinity constitutes a prevailing component of an
overall efficiency, thus the power is analyzed in terms of an active
part of chemical affinity. The main novelty of the present paper in the
energy yield context consists in showing that the generalized heat
flux Q (involving the traditional heat flux q plus the product of
temperature and the sum products of partial entropies and fluxes of
species) plays in complex cases (solar, chemical and electrochemical)
the same role as the traditional heat q in pure heat engines.
The presented methodology is also applied to power limits in fuel
cells as to systems which are electrochemical flow engines propelled
by chemical reactions. The performance of fuel cells is determined by
magnitudes and directions of participating streams and mechanism of
electric current generation. Voltage lowering below the reversible
voltage is a proper measure of cells imperfection. The voltage losses,
called polarization, include the contributions of three main sources:
activation, ohmic and concentration. Examples show power maxima
in fuel cells and prove the relevance of the extension of the thermal
machine theory to chemical and electrochemical systems. The main
novelty of the present paper in the FC context consists in introducing
an effective or reduced Gibbs free energy change between products p
and reactants s which take into account the decrease of voltage and
power caused by the incomplete conversion of the overall reaction.
Abstract: With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.
Abstract: An aqueous methanol sensor for use in direct
methanol fuel cells (DMFCs) applications is demonstrated; the
methanol sensor is built using dispersed single-walled carbon
nanotubes (SWCNTs) with Nafion117 solution to detect the methanol
concentration in water. The study is aimed at the potential use of the
carbon nanotubes array as a methanol sensor for direct methanol fuel
cells (DMFCs). The concentration of methanol in the fuel circulation
loop of a DMFC system is an important operating parameter, because
it determines the electrical performance and efficiency of the fuel cell
system. The sensor is also operative even at ambient temperatures
and responds quickly to changes in the concentration levels of the
methanol. Such a sensor can be easily incorporated into the methanol
fuel solution flow loop in the DMFC system.
Abstract: In this paper, the application of GRNN in
modeling of SOFC fuel cells were studied. The parameters
are of interested as voltage and power value and the current
changes are investigated. In addition, the comparison between
GRNN neural network application and conventional method
was made. The error value showed the superlative results.