Abstract: Nonlinear and unbalance loads in three phase
networks create harmonics and losses. Active and passive filters are
used for elimination or reduction of these effects. Passive filters have
some limitations. For example, they are designed only for a specific
frequency and they may cause to resonance in the network at the
point of common coupling. The other drawback of a passive filter is
that the sizes of required elements are normally large. The active
filter can improve some of limitations of passive filter for example;
they can eliminate more than one harmonic and don't cause resonance
in the network. In this paper inverter analysis have been done
simultaneously in three phase and the RL impedance of the line have
been considered. A sliding mode control based on energy feedback of
capacitors is employed in the design with this method, the dynamic
speed of the filter is improved effectively and harmonics and load
unbalance is compensating quickly.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: Self-compacting concrete (SCC), a new kind of high
performance concrete (HPC) have been first developed in Japan in
1986. The development of SCC has made casting of dense
reinforcement and mass concrete convenient, has minimized noise.
Fresh self-compacting concrete (SCC) flows into formwork and
around obstructions under its own weight to fill it completely and
self-compact (without any need for vibration), without any
segregation and blocking. The elimination of the need for
compaction leads to better quality concrete and substantial
improvement of working conditions. SCC mixes generally have a
much higher content of fine fillers, including cement, and produce
excessively high compressive strength concrete, which restricts its
field of application to special concrete only. To use SCC mixes in
general concrete construction practice, requires low cost materials to
make inexpensive concrete.
Rice husk ash (RHA) has been used as a highly reactive
pozzolanic material to improve the microstructure of the interfacial
transition zone (ITZ) between the cement paste and the aggregate in
self compacting concrete. Mechanical experiments of RHA blended
Portland cement concretes revealed that in addition to the pozzolanic
reactivity of RHA (chemical aspect), the particle grading (physical
aspect) of cement and RHA mixtures also exerted significant
influences on the blending efficiency.
The scope of this research was to determine the usefulness of Rice
husk ash (RHA) in the development of economical self compacting
concrete (SCC). The cost of materials will be decreased by reducing
the cement content by using waste material like rice husk ash instead
of.
This paper presents a study on the development of Mechanical
properties up to 180 days of self compacting and ordinary concretes
with rice-husk ash (RHA), from a rice paddy milling industry in
Rasht (Iran). Two different replacement percentages of cement by
RHA, 10%, and 20%, and two different water/cementicious material
ratios (0.40 and 0.35), were used for both of self compacting and
normal concrete specimens. The results are compared with those of
the self compacting concrete without RHA, with compressive,
flexural strength and modulus of elasticity. It is concluded that RHA
provides a positive effect on the Mechanical properties at age after
60 days.
Base of the result self compacting concrete specimens have higher
value than normal concrete specimens in all test except modulus of
elasticity. Also specimens with 20% replacement of cement by RHA
have the best performance.
Abstract: Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. Fueling the attention have been the possibilities of international agreements to reduce greenhouse gas emissions, electricity sector restructuring, high power reliability requirements for certain activities, and concern about easing transmission and distribution capacity bottlenecks and congestion. So it is necessary that impact of these kinds of generators on distribution feeder reconfiguration would be investigated. This paper presents an approach for distribution reconfiguration considering Distributed Generators (DGs). The objective function is summation of electrical power losses A Tabu search optimization is used to solve the optimal operation problem. The approach is tested on a real distribution feeder.
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: This paper presents an approach for daily optimal operation of distribution networks considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. A genetic algorithm is used to solve the optimal operation problem. The approach is tested on an IEEE34 buses distribution feeder.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.