A new smart approach of an efficient energy consumption management by using a machine-learning technique

Maha Yousif Hasan, Dheyaa Jasim Kadhim


Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is satisfied. It divides the measured data for actual power (A_p ) of the electrical model into two portions: the training portion is selected for different maximum actual powers, and the validation portion is determined based on the minimum output power consumption and then used for comparison with the actual required input power. Simulation results show the energy expenditure problem can be solved with good accuracy in energy consumption by reducing the maximum rate (A_p ) in a given time (24) hours for a single house, as well as electricity’s bill cost, is reduced.


Actual power; Energy consumption; Energy efficiency; Machine learning; Validation approach;

Full Text:


DOI: http://doi.org/10.11591/ijeecs.v25.i1.pp68-78


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics