Energy consumption prediction using Petri Nets-ANFIS development technique

Abstract

Energy consumption has always been considered one of the major issues in the six Gulf Cooperation Council (GCC) countries. Therefore, the predicted energy consumption can respond based on several factors and conditions, where which will help in response to plan saving energy for the future. The significant contribution of the present study is the development of software merging the Petri-Nets and ANFIS to become a comprehensive model to find the maximum annual load demand estimation of the GCC countries based on the historical data of the countries. The ANFIS-Petri Nets have expected modeling to represent knowledge and help in rule-based expert systems. The data has several parameters/conditions (factors), where these factors are temperature, humidity, GDP, pressure, and energy consumption. The results lead to a fast and accurate figure have developed an energy estimated system that works by tracking, analyzing, and controlling conditions of the energy system. The Petri-Nets ANFIS developed technique targeting the estimated maximum annual energy consumption believes that obtaining the values is satisfactory for the future of GCC states. In addition, the developed and obtained models have great application for the GCC countries. This might help to develop the models of other countries.