An Intelligent Load Management System With Renewable Energy Integration for Smart Homes | Zendy

Nadeem Javaid | Zendy; Ihsan Ullah | Zendy; Mariam Akbar | Zendy; Zafar Iqbal | Zendy; Farman Ali Khan | Zendy; Nabil Alrajeh | Zendy; Mohamad Souheil Alabed | Zendy

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An Intelligent Load Management System With Renewable Energy Integration for Smart Homes

Author(s) -

Nadeem Javaid,

Ihsan Ullah,

Mariam Akbar,

Zafar Iqbal,

Farman Ali Khan,

Nabil Alrajeh,

Mohamad Souheil Alabed

Publication year - 2017

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2715225

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Demand side management (DSM) will play a significant role in the future smart grid by managing loads in a smart way. DSM programs, realized via home energy management systems for smart cities, provide many benefits; consumers enjoy electricity price savings and utility operates at reduced peak demand. In this paper, evolutionary algorithms-based (binary particle swarm optimization, genetic algorithm, and cuckoo search) DSM model for scheduling the appliances of residential users is presented. The model is simulated in time of use pricing environment for three cases: 1) traditional homes; 2) smart homes; and 3) smart homes with renewable energy sources. Simulation results show that the proposed model optimally schedules the appliances resulting in electricity bill and peaks reductions.

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