A multi-objective home energy management system based on internet of things and optimization algorithms. (January 2021)

• Record Type: Journal Article
• Authors: Wang, Xiuwang; Mao, Xinna; Khodaei, Hossein
• Is Part Of: Journal of building engineering. Volume 33(2021)
• Publication Date: 2021-01
• Subjects: Home energy management system -- Multi-objective optimization -- Demand response -- Energy consumption cost -- User satisfaction; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2020.101603
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: This study presents a new optimal method for home energy management system based on the internet of things. The method is a multi-objective optimization method that considers two main purposes including energy consumption cost and user satisfaction. The method is designed under the environment of the smart grid. Generally, the impact of the users in the system efficiency in terms of energy cost saving is significant. This reason makes residential users participate in household appliances management. The optimization algorithm is based on a new improved version of the butterfly algorithm for increasing the convergence speed. IoT system is based on ZigBee which is known as the lowest consumption among different wireless technologies. The household employs based on a sample user scenario with different appliances. Using Multi-objective optimization gives fragmented energy consumption. The results of Multi-objective optimization are also compared with PSO-based and BOA-based algorithms to show the proposed method's effectiveness. Simulation results are compared by the normal home energy management system to declare the system efficiency. Highlights: A general HEMS model based on loT is established. The system is used to schedule washing machine, water heater, EV, dishwasher, and air conditioner. The system is in a residential energy structure including renewable energy sources and storage battery. An improved model of butterfly optimization algorithm is proposed for the HEMS. Multi-objective optimization is used for better HEMS monitoring.