Abstract: Transmission network expansion planning (TNEP) is
a basic part of power system planning that determines where, when
and how many new transmission lines should be added to the
network. Up till now, various methods have been presented to solve
the static transmission network expansion planning (STNEP)
problem. But in all of these methods, transmission expansion
planning considering network adequacy restriction has not been
investigated. Thus, in this paper, STNEP problem is being studied
considering network adequacy restriction using discrete particle
swarm optimization (DPSO) algorithm. The goal of this paper is
obtaining a configuration for network expansion with lowest
expansion cost and a specific adequacy. The proposed idea has been
tested on the Garvers network and compared with the decimal
codification genetic algorithm (DCGA). The results show that the
network will possess maximum efficiency economically. Also, it is
shown that precision and convergence speed of the proposed DPSO
based method for the solution of the STNEP problem is more than
DCGA approach.
Abstract: The reluctance motor is an electric motor in which
torque is produced by the tendency of its moveable part to move to a
position where the inductance of the excited winding is maximized.
In this paper switched reluctance motors (SRMs) with two different
configurations(3-phase SRM with 4rotor poles and 6 stator poles, 4-
phase SRM with 6rotor poles and 8 stator poles) is designed by
RMxprt, and performance of them is analyzed. Efficiency and torque
of SRM for different configurations in full-load condition have been
presented. The results indicate that with correct choosing of motor
applications, maximum efficiency can be found.
Abstract: High Speed PM Generators driven by micro-turbines
are widely used in Smart Grid System. So, this paper proposes
comparative study among six classical, optimized and genetic
analytical design cases for 400 kW output power at tip speed 200
m/s. These six design trials of High Speed Permanent Magnet
Synchronous Generators (HSPMSGs) are: Classical Sizing;
Unconstrained optimization for total losses and its minimization;
Constrained optimized total mass with bounded constraints are
introduced in the problem formulation. Then a genetic algorithm is
formulated for obtaining maximum efficiency and minimizing
machine size. In the second genetic problem formulation, we attempt
to obtain minimum mass, the machine sizing that is constrained by
the non-linear constraint function of machine losses. Finally, an
optimum torque per ampere genetic sizing is predicted. All results are
simulated with MATLAB, Optimization Toolbox and its Genetic
Algorithm. Finally, six analytical design examples comparisons are
introduced with study of machines waveforms, THD and rotor losses.
Abstract: In the supply chain management customer is the most
significant component and mass customization is mostly related to
customers because it is the capability of any industry or organization
to deliver highly customized products and its services to the
respective customers with flexibility and integration, providing such
a variety of products that nearly everyone can find what they want.
Today all over the world many companies and markets are facing
varied situations that at one side customers are demanding that their
orders should be completed as quickly as possible while on other
hand it requires highly customized products and services. By
applying mass customization some companies face unwanted cost
and complexity. Now they are realizing that they should completely
examine what kind of customization would be best suited for their
companies. In this paper authors review some approaches and
principles which show effect in supply chain management that can be
adopted and used by companies for quickly meeting the customer
orders at reduced cost, with minimum amount of inventory and
maximum efficiency.
Abstract: TiO2/MgO composite films were prepared by coating
the magnesium acetate solution in the pores of mesoporous TiO2
films using a dip coating method. Concentrations of magnesium
acetate solution were varied in a range of 1x10-4 – 1x10-1 M. The
TiO2/MgO composite films were characterized by scanning electron
microscopy (SEM), transmission electron microscropy (TEM),
electrochemical impedance spectroscopy(EIS) , transient voltage
decay and I-V test. The TiO2 films and TiO2/MgO composite films
were immersed in a 0.3 mM N719 dye solution. The Dye-sensitized
solar cells with the TiO2/MgO/N719 structure showed an optimal
concentration of magnesium acetate solution of 1x10-3 M resulting in
the MgO film estimated thickness of 0.0963 nm and giving the
maximum efficiency of 4.85%. The improved efficiency of dyesensitized
solar cell was due to the magnesium oxide film as the wide
band gap coating decays the electron back transfer to the triiodide
electrolyte and reduce charge recombination.
Abstract: The excellent suitability of the externally excited synchronous
machine (EESM) in automotive traction drive applications
is justified by its high efficiency over the whole operation range and
the high availability of materials. Usually, maximum efficiency is
obtained by modelling each single loss and minimizing the sum of all
losses. As a result, the quality of the optimization highly depends on
the precision of the model. Moreover, it requires accurate knowledge
of the saturation dependent machine inductances. Therefore, the
present contribution proposes a method to minimize the overall losses
of a salient pole EESM and its inverter in steady state operation based
on measurement data only. Since this method does not require any
manufacturer data, it is well suited for an automated measurement
data evaluation and inverter parametrization. The field oriented control
(FOC) of an EESM provides three current components resp. three
degrees of freedom (DOF). An analytic minimization of the copper
losses in the stator and the rotor (assuming constant inductances) is
performed and serves as a first approximation of how to choose the
optimal current reference values. After a numeric offline minimization
of the overall losses based on measurement data the results are
compared to a control strategy that satisfies cos (ϕ) = 1.
Abstract: Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.