Building a new integrated system to predict and control electricity consumption
Sarah Atef, a researcher at the School of Innovative Design Engineering, successfully defends her thesis titled “Rationalizing Energy Consumption Using Artificial Intelligence”
Prof. Amr Eltawil, Dean of the School of Innovative Design engineering assured that a researcher’s Ph.D. thesis titled “Rationalizing Energy Consumption Using Artificial Intelligence” was successfully defended. The thesis suggests building an effective integrated system to control and predict the daily electricity consumption in residential blocks, and he added the suggested system contains a predictive model to respond to the demand for electricity.
Moreover, Prof. Eltawil stated the thesis proposed by Ms. Sarah Atef, a researcher at the Industrial Engineering Department, suggested two methodologies to build an effective predictive model. The first methodology utilizes a feedforward neural network with long-term memory, which predicts electricity consumption. The second methodology utilizes a bidirectional neural network to predict the consumption data; then transferring these data to the proposed system. He added the proposed system can be used to perfectly schedule the usage of several electrical home appliances using a fuzzy-based model. Furthermore, he pointed out that the proposed model can dramatically reduce the maximum loads, rationalize electricity consumption, and save the consumption cost bearing in mind the constant and dynamic pricing paradigms.
The judgment committee included Prof. Amr Ahmed Abd-Elmoneim, Prof. Amr Bahgat Eltawil, and Prof. Tamer Farouk Abd-Elmongy