An efficient Capacitor Bank Operating System for Single Phase Power Factor Correction using Neural Network Estimations

Wastage of electricity occurs in all places starting from a small house electrical loading to a heavy industrial electrical loading. KiloVolt-Ampere Reactive (KVAR) power metering devices are employed in industrial applications for measuring the energy utilization which measure the energy wastage along with it. This urges a consumer to pay for the unutilized or wasted energy as well. To avoid this, certain capacitor bank units are connected to the industrial application motor units. The right choice of capacitor rating are helpful in minimizing the wasted power observation in the KVAR meters. The selection of capacitor rating is analysed with respect to the power factor calculation. The power factor is a derivation of working power to the apparent power in an electrical system. An optimum power factor to be maintained in an electrical system is 1. The motive of the proposed work is to maintain the power factor by selecting an optimum capacitor bank on the operation of an electrical system at various load conditions. The requirement of capacitor bank values get changed with respect to the load given to an electrical system. A neural network based prediction model is employed in the work for estimating the right choice of capacitor bank. The efficiency of the proposed work is verified and found satisfied with a traditional capacitor bank operating system.

Atomic-resolution Probing of Anion Migration in Perovskites with In-situ (S)TEM

ABSTRACTPerovskites are promising functional materials for their optoelectronic properties and anion migration plays a key role in their functional performance [1-3]. By using in-situ (S)TEM mechanical and electrical testing in conjunction with 4D-STEM [4,5], we directly observed/probed anion migration in perovskites at atomic resolution (see Figure 1). Here, we studied the mechanism for the anion migration in perovskites such as (PbZr)TiO3 and BaTiO3, which is induced under the mechnaicl/electrical loading. To avoid the influence of the electron beam, we carried out the in-situ (S)TEM study at 60kv with low dose. And to avoid the possible strong size effect and the substrate (interface) influence, we prepared free-standing sub-micrometer single-crystalline structures to perform the experiments. Corresponding EDS and EELS examinations were performed to measure the local chemical change with applied stress and electrical currents. Our observations revealed the coexistence of multiple phase structures and hierarchical domain structures, as well as the greatly enhanced anion drifting and diffusion at the charged domain walls (Figure 2) and phase boundaries. The complex interaction between the local domain evolution and phase transition has been discussed. Based on above investigations, a model for anion migration in perovskire under mechanical/electrical loading has been presented.

Cost Benefit Analysis for Electrical Loading System for Transformers of a Barangay

The study assessed the cost and benefit of electrical loading management of transformers. There is a serious occurrence of over and under loaded transformer which deeply affects the power quality or system loss and reliability of the distribution lines. Initially, the percent loading of the 27 transformers of Feeder 21 were identified using Microsoft Excel 2016. Then, the identified transformers were classified into three categories; overload (greater than 70%), under loaded (less than 40%) and normal loaded (40-70%). Through this process, three (3) solutions were identified: Solution I - change the transformer rating, Solution II – merge and transfer transformer loadsand Solution III - combine solution I and II. The three-solution used to identify the new percent loading to meet the normal percent loading (40-69%). Subsequently, the reduced Core and Copper Losses, Annual Energy Save, Savings and Benefit/Cost Ratio were computed and analyzed to determine the impact of loadingmanagement. The results show that there was an accumulated savings of Php 332,060.08 for Solution I, Php 92,043.09 for Solution II and Php 252,045.78 for Solution III. In the case of Benefit/Cost ratio it should be greater than 1 (>1) for a project to be economically feasible and justifiable; Solution I was 1.22, Solution II was 687.3 and 1.93 for Solution III. Based on the results of the study, SolutionIII was best among the three, for it has met the criteria of all transformers were all in normal loaded (40-70%) condition, and greater than 1 benefit/cost ratio.