Forecasting and Simulation for Electrical Power System and Load Distribution in Taif – Saudi Arabia

Abstract

Monitoring electrical power system and clarifying the way of electricity flow is a difficult task, that might cause electricity cuts because of the increasing loads of grids. In recent years, the observations showed that electric loads in Taif city have increased significantly due to the population growth and large urbanization. These causes require a good monitoring and analyzing system intensively to maintain continuity and reliability of electrical service. Machine learning and dynamic programming approaches will be employed for forecasting the distribution of power load and optimization of Electrical Power System in Taif City to avoid the unexpected problems in electrical network before they have occurred. The other goal is to facilitate monitoring of the electrical power system in Taif city and clarify the electricity flow from Makkah to Taif and then to other neighboring districts. The results and findings of the study will be evaluated using the methods of error calculation and ranking and presented in detail.