استعمال بعض الاساليب الاحصائية للتنبؤ بالطاقة الكهربائية الضائعة (دراسة تطبيقية

Using some statistical methods to predict the lost electrical energy (applied study)

Abstract

Time series is an important method that deals with the behavior of phenomena and interpreting them over certain time periods. The importance of time series analysis is to obtain an accurate description of these series for building an appropriate model to predicting and using the results for future planning.
The purpose of choosing an appropriate model is to making predictions to find out the lost electricity of the holy city of Karbala for the future, so that the ministry of electricity can identify the losses in electrical energy in order to take the necessary precautions to face this phenomenon, and to find the ways to deal with it.
We had used the (Box Jenkins) method for determining the best and efficient statistical model that can used in the prediction and analysis of the time series of lost electricity in the province of holy Karbala for the period (2012-2016). Based on this model we predicted the lost electricity for the next two years (2017-2018). The predictive values were consistent with the real values; this is proving this model efficiency.
The study recommend to use the proposed model in order to predicting the lost electrical energy in future, and obtaining the information and data related to the lost energy in order to benefit from scientific research, that will help in making other studies using different statistical methods for time series. This is to trying to minimize the losses occurring in electrical energy, which aim in end to serving the public interest.