Diagnostic Framework for Electricity Losses in Pakistan Using Data Visualization Techniques

Fatima Tariq, Dr Atif Alvi
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Abstract

To obtain the best results and leads to accuracy, data visualization techniques allows the big data and unprocessed data in a structured format. There are a lot of techniques that provides the best results for both high and low dimensional data preprocessing. Electricity crisis are becoming the part of day to day life and increasing rapidly. There are a lot of factors that affects the distribution and transmission losses of electricity. PEPCO, GENCO and other distribution companies are responsible for electricity distribution .There are 10-12% electricity losses during the distribution from main to other. At different sectors electricity production and installation from different resources of energy needs a proper monitoring system .Except of system losses a lot of electricity lost due to non-technical factors which leads to the shortage of electricity in a Country. .Grid stations should be planted according to the population of the province .Diagnostic framework includes the previous and present data comparison which predicts and forecasts the future consumption that helps to overcome losses by time series analysis algorithm (ARIMA)
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使用数据可视化技术的巴基斯坦电力损失诊断框架
为了获得最佳结果并导致准确性,数据可视化技术允许大数据和未处理数据以结构化格式呈现。有许多技术可以为高维和低维数据预处理提供最佳结果。电力危机正在成为日常生活的一部分,并迅速增加。影响电力分配和传输损耗的因素很多。由PEPCO, GENCO等配电公司负责配电,从主配电到其他配电的过程中有10-12%的损耗。在不同的部门,电力生产和安装来自不同的能源资源需要一个适当的监测系统。除了系统损失,大量的电力损失是由于非技术因素,导致电力短缺在一个国家。电网站应该根据省的人口种植。诊断框架包括过去和现在的数据比较,预测和预测未来的消费,有助于克服损失时间序列分析算法
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