Data Mining Applications in Understanding Electricity Consumers’ Behavior: A Case Study of Tulkarm District, Palestine

Maher Abubaker

doi:10.3390/en12224287

Abstract

This paper presents a comprehensive data analysis and visualization of electricity consumers’ prepaid bills of Tulkarm district. We analyzed 250,000 electricity consumers’ prepaid bills covering the time period from June to December 2018. The application of data mining techniques for understanding electricity consumers’ behavior in electricity consumption and their behavior in charging their electricity meter’s smart cards in terms of quantities charged and charging frequencies in different time periods, areas and tariffs are used. Understanding consumers’ behavior will support planning and decision making at strategic, tactical and operational levels. This analysis is useful for predicting and forecasting future demand with a certain degree of accuracy. Monthly, weekly, daily and hourly time periods are covered in the analysis. Outliers detection using visualization tools such as box plot is applied. K-means unsupervised machine learning clustering algorithm is implemented. The support vector machine classification method is applied. As a result of this study, electricity consumers’ behavior in different areas, tariffs and timing periods is understood and presented by numbers and graphs and new electricity consumer segmentation is proposed.

Highlights

One of the primary research areas in power systems’ management and planning is the analysis of energy consumption [1]
The main aim of this study is to analyze the data of electricity consumers prepaid bills (ECPB) of Tulkarm district using data mining techniques
The analysis shows that August, July and September having more electricity consumption than other months

Summary

Introduction

One of the primary research areas in power systems’ management and planning is the analysis of energy consumption [1]. Data analysis and mining play a vital role in providing information about electricity consumption. Information about consumers’ behavior of electricity consumption in different areas (North, West, etc.) and tariffs (household, agricultural, industrial, etc.), detection and early warning of energy theft or fraud, and fast detection of disturbances in energy demand and supply. Tulkarm Municipality (TM) is the main and only electricity distributor in Tulkarm district. TM is the main electricity distributor of the Tulkarm district. Tulkarm district, which includes the city and its suburbs and villages is part of the West Bank. TM electricity management system is in an urgent need for improvement. For this reason, it is taken as the sample of this study.

Objectives

Results

Conclusion