Signal Processing and Renewable Energy
Volume:1 Issue: 1, Winter 2017

Theory of compressive sensing  (CS) is an alternative to Shannon/Nyquist sampling theorem which explained the number of samples requirement in order to have the perfect reconstruction. Perfect reconstruction of undersampled data in CS framework is highly dependent to incoherence of measurement and sparsifying basis matrices which the posterior is usually fulfilled by selecting a random matrix. While Noiselets, as a measurement matrix, have very low coherence with wavelets which are the interest of CS, they have never been studied well and compared with other well known Gaussian and Bernoulli measurement matrices, which have been widely used in CS framework, from randomness view point. Therefore, the main contribution of this paper is introducing Noiselets and comparing them with other measurement matrices in two point of view; randomness and quality of recovered images. In case of randomness, the entropy is used as a criterion for computing the randomness. In case of recovered images, the OMP and PDIP algorithms are applied under sampling rates 30, 40, 60%.

This paper presents a new approach to unit commitment (UC) problems using a particle swarm optimization (PSO) technique. The mid term UC problem has a cost function with equality and inequality constraints that make the problem of finding the global optimum difficult by using any mathematical approach. In this paper, a modified PSO (MPSO) mechanism is suggested to deal with the equality and inequality constraints in the UC problems. The proposed MPSO is applied to a 10-unit test system and the results of the MPSO are compared with the results of conventional numerical methods such as mixed integer nonlinear programming (MINLP).

The long-term planning of distribution network expansion planning has different complexities, because this problem has a lot of decision-making variable. The optimal placement problem of HV/MV substations with distributed generations simultaneously for supplying the capacity required for power system are analyzed in this paper. In the mathematical model, objective function together with constant, varied variables and constraints related to limitations for the operation of substations and distributed generation resources as well as network limitations are formulated. Despite of distributed generation resources, the simultaneous placement must be so that firstly load points to be supplied and secondly loss costs of the network to be reduced. In addition, the voltage profile improvement and reduction of network reconfiguration costs are considered. At the end, we will observe the power quality improvement in load points. To solve this problem, optimization of one of new algorithms named cuckoo optimization algorithm has been applied. The study period for performing this test by means of dynamic-pseudo method for a long-term study will be within the design period. Finally, tests will be provided for proving the efficiency of this offered optimization algorithm.

This paper presents an efficient adaptive filter, to remove impulse noise from X-ray images. This filter has two stages. At the first stage, based on the intensity value, the pixels are classified into  two classes, which are noisy pixels and noise- free pixels, the noisy pixels are only processed and the noise-free pixels remain unchanged. In this method the size of window is adaptively changed and the edges and details are preserves, hence for the replacing noisy pixels, two issues are considered the noise-free pixels and the level of noise in an image. The result from 50 test X-ray images showed that this method is promising to remove the impulse noise from X-ray images.

In the high voltage (HV) electrical power systems, different materials are used as the role of insulation to protect the incipient failure inside the HV power equipments. One of the common phenomenas in insulations is Partial Discharge (PD). Because of the high voltage stress, the weak section inside the insulator causes the partial discharge (PD), which is known as a local electrical breakdown. The maximum amplitude of PD could accelerate the destruction process of insulation material. Also, during practical applications in the power systems, voltages with different levels are used or created suddenly. Therefore, it is necessary to analyze the effect of voltage characteristics on the PD. In this paper, the effect of DC, AC and impulse voltage on the maximum amplitude of PD are studied within the MATLAB Simulink platform. Finally, to show the effect of each voltage level on the PD, results are compared with each other in the single and multi cavity situations. The test materials for this research are epoxy resin and oil-impregnated paper. Also, this paper provides a comparison between two different insulation materials.

In the high voltage (HV) electrical power systems, different materials are used as the role of insulation to protect the incipient failure inside the HV power equipments. One of the common phenomenas in insulations is Partial Discharge (PD). Because of the high voltage stress, the weak section inside the insulator causes the partial discharge (PD), which is known as a local electrical breakdown. The maximum amplitude of PD could accelerate the destruction process of insulation material. Also, during practical applications in the power systems, voltages with different levels are used or created suddenly. Therefore, it is necessary to analyze the effect of voltage characteristics on the PD. In this paper, the effect of DC, AC and impulse voltage on the maximum amplitude of PD are studied within the MATLAB Simulink platform. Finally, to show the effect of each voltage level on the PD, results are compared with each other in the single and multi cavity situations. The test materials for this research are epoxy resin and oil-impregnated paper. Also, this paper provides a comparison between two different insulation materials.