Advanced SOM & K Mean Method for Load Curve Clustering

From the load curve classification for one customer, the main features such as the seasonal factors, the weekday factors influencing on the electricity consumption may be extracted. By this way some utilities can make decision on the tariff by seasons or by day in week. The popular clustering techniques are the SOM & K-mean or Fuzzy K-mean. SOM &Kmean is a prominent approach for clustering with a two-level approach: first, the data set will be clustered using the SOM and in the second level, the SOM will be clustered by K-mean. In the first level, two training algorithms were examined: sequential and batch training. For the second level, the K-mean has the results that are strongly depended on the initial values of the centers. To overcome this, this paper used the subtractive clustering approach proposed by Chiu in 1994 to determine the centers. Because the effective radius in Chiu’s method has some influence on the number of centers, the paper applied the PSO technique to find the optimum radius. To valid the proposed approach, the test on well-known data samples is carried out. The applications for daily load curves of one Southern utility are presented

Modified Method for prefabricated vertical drain consolidation analysis

Ground improvement with the prefabricated vertical drain (PVD) has become widely employed for soft ground treatment because of its economical and efficient method. While numerous numerical and analytical methods have been derived for PVD however, it is still an extensively high demand for a simpler and more accurate method for design steps. This paper proposes a method for solving the problem of one-dimensional (1D) consolidation with prefabricated vertical drains. The current approach introduces a 1D equivalent permeability, increasing linearly with depth to perform the consolidation of soft ground improved with PVD. The analytical solutions have been carried out and verified by analyses for two cases of one-way drainage and two-way drainage for uniform soil layer. The results show that the error of excess pore pressure determined by the proposed method is less than that obtained by the simpler method of Chai and smaller than 10% compared to the theoretical solution. The paper also compares the analytical solution with the FEM by ABAQUS software. It is found that the excess pore pressures and consolidation degrees obtained by these methods are similar and close to the theory. These confirm that the introduced 1D equivalent permeability can be employed to perform the consolidation of PVD improvement by analytical and FEM methods

Modified Method for prefabricated vertical drain consolidation analysis

Ground improvement with the prefabricated vertical drain (PVD) has become widely employed for soft ground treatment because of its economical and efficient method. While numerous numerical and analytical methods have been derived for PVD however, it is still an extensively high demand for a simpler and more accurate method for design steps. This paper proposes a method for solving the problem of one-dimensional (1D) consolidation with prefabricated vertical drains. The current approach introduces a 1D equivalent permeability, increasing linearly with depth to perform the consolidation of soft ground improved with PVD. The analytical solutions have been carried out and verified by analyses for two cases of one-way drainage and two-way drainage for uniform soil layer. The results show that the error of excess pore pressure determined by the proposed method is less than that obtained by the simpler method of Chai and smaller than 10% compared to the theoretical solution. The paper also compares the analytical solution with the FEM by ABAQUS software. It is found that the excess pore pressures and consolidation degrees obtained by these methods are similar and close to the theory. These confirm that the introduced 1D equivalent permeability can be employed to perform the consolidation of PVD improvement by analytical and FEM methods

A hybrid artificial neural network - genetic algorithm for load shedding

This paper proposes the method of applying Artificial Neural Network (ANN) with Back Propagation (BP) algorithm in combination or hybrid with Genetic Algorithm (GA) to propose load shedding strategies in the power system. The Genetic Algorithm is used to support the training of Back Propagation Neural Networks (BPNN) to improve regression ability, minimize errors and reduce the training time. Besides, the Relief algorithm is used to reduce the number of input variables of the neural network. The minimum load shedding with consideration of the primary and secondary control is calculated to restore the frequency of the electrical system. The distribution of power load shedding at each load bus of the system based on the phase electrical distance between the outage generator and the load buses. The simulation results have been verified through using MATLAB and PowerWorld software systems. The results show that the Hybrid Gen-Bayesian algorithm (GA-Trainbr) has a remarkable superiority in accuracy as well as training time. The effectiveness of the proposed method is tested on the IEEE 37 bus 9 generators standard system diagram showing the effectiveness of the proposed method

Advanced Metering Infrastructure Based on Smart Meters in Smart Grid

Due to lack of situational awareness, automated analysis, poor visibility, and mechanical switches, today\u27s electric power grid has been aging and ill‐suited to the demand for electricity, which has gradually increased, in the twenty‐first century. Besides, the global climate change and the greenhouse gas emissions on the Earth caused by the electricity industries, the growing population, one‐way communication, equipment failures, energy storage problems, the capacity limitations of electricity generation, decrease in fossil fuels, and resilience problems put more stress on the existing power grid. Consequently, the smart grid (SG) has emerged to address these challenges. To realize the SG, an advanced metering infrastructure (AMI) based on smart meters is the most important key

Minimize the load reduction considering the activities control of the generators and phase distance

This study shows how to calculate the minimum load that needs to be reduced to restore the frequency to the specified threshold. To implement this problem, the actual operation of the electricity system in the event of a generator outage is considered. The main idea of this method is to use the power balance equation between the generation and the load with different frequency levels. In all cases of operating the electrical system before and after the generator outage, the reserve capacity of other generators is considered in each generator outage situation. The reduced load capacity is calculated based on the reciprocal phase angle sensitivity or phase distance. This makes the voltage phase angle and voltage value quality of recovery nodes better. The standard IEEE 9-generator 37-bus test scheme was simulated to show the result of the proposed technique

A Solution of Plane Stress Problem Subjected to Horizontal Shear Force by Using Polynomial Airy Stress Function

Many structural analysis problems in civil engineering and mechanical engineering can be treated as plane stress and plane strain problems introduced in the theory of elasticity. One of the popular analytical methods to tackle plane analysis is to determine Airy stress function. In general, the Airy stress function depends on the analyzed domain and the applied loads; however, the number of problems that can be solved by employing this method is limited because of the formidable challenges of guessing trial function. In many cases, the trial Airy stress functions are selected based on the results of a simple beam model or experimental results. This paper introduces a solution of the plane stress subjected to horizontal shear forces by using a polynomial Airy stress function, in which the trail function is predicted from the results of the elementary beam theory of an equivalent model. The numerical investigation on stress distributions was presented, and it showed that although the internal shear force acting on cross-sections have not appeared, shear stress still appeared, and the shear stress diagram had both negative and positive areas

A Solution of Plane Stress Problem Subjected to Horizontal Shear Force by Using Polynomial Airy Stress Function

Many structural analysis problems in civil engineering and mechanical engineering can be treated as plane stress and plane strain problems introduced in the theory of elasticity. One of the popular analytical methods to tackle plane analysis is to determine Airy stress function. In general, the Airy stress function depends on the analyzed domain and the applied loads; however, the number of problems that can be solved by employing this method is limited because of the formidable challenges of guessing trial function. In many cases, the trial Airy stress functions are selected based on the results of a simple beam model or experimental results. This paper introduces a solution of the plane stress subjected to horizontal shear forces by using a polynomial Airy stress function, in which the trail function is predicted from the results of the elementary beam theory of an equivalent model. The numerical investigation on stress distributions was presented, and it showed that although the internal shear force acting on cross-sections have not appeared, shear stress still appeared, and the shear stress diagram had both negative and positive areas

Isolation and identification of some . Strain from traditional fermented foods

Recent publications showed that Lactic acid bacteria (LAB) are used extensively to inhibit growth of spoilage and pathogenic bacterial strains. That is being applied in food processing such as tradition fermented food or dairy, beverage and meat products. Lactic acid bacteria can produce a variety of antibacterial agents including bacteriocin, diacetyl, etc. Thus, the isolation, identification and taxonomical characterization of each new Lactobacillus sp. strain is being more and more required. However, the large number of species in the genus Lactobacillus almost have their high phenotypic and physiological similarity which easily leads to misidentification. The present study was aimed for isolation and reliable identification of Lactobacillus sp. strains from some traditional fermented foods by on the basis of phenotypic analysis and combination of PCR and sequencing of target sequences base on 16S-23S rRNA gene. Eight strains of LAB were isolated and characterized through morpholigical, physiological, biochemical and carbohydrate fermentation tests. All of them were determined as Lactobacillus sp. Moreover, the nucleotides sequences of 16S-23S rDNA of them was compared and phylogenetic analysis to those of Lactosbacillus species in GenBank and the results confirm that four strains: L1, L3, L4 and L7 belong to Lactobacillus platarum and four strains: L2, L5, L6 and L8 belong to species L. rhamnosu

Finding optimal reactive power dispatch solutions by using a novel improved stochastic fractal search optimization algorithm

In this paper, a novel improved Stochastic Fractal Search optimization algorithm (ISFSOA) is proposed for finding effective solutions of a complex optimal reactive power dispatch (ORPD) problem with consideration of all constraints in transmission power network. Three different objectives consisting of total power loss (TPL), total voltage deviation (TVD) and voltage stabilization enhancement index are independently optimized by running the proposed ISFSOA and standard Stochastic Fractal Search optimization algorithm (SFSOA). The potential search of the proposed ISFSOA can be highly improved since diffusion process of SFSOA is modified. Compared to SFSOA, the proposed method can explore large search zones and exploit local search zones effectively based on the comparison of solution quality. One standard IEEE 30-bus system with three study cases is employed for testing the proposed method and compared to other so far applied methods. For each study case, the proposed method together with SFSOA are run fifty run and three main results consisting of the best, mean and standard deviation fitness function are compared. The indication is that the proposed method can find more promising solutions for the three cases and its search ability is always more stable than those of SFSOA. The comparison with other methods also give the same evaluation that the proposed method can be superior to almost all compared methods. As a result, it can conclude that the proposed modification is really appropriate for SFSOA in dealing with ORPD problem and the method can be used for other engineering optimization problems