An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory

Aqib Jamil, Turki Ali Alghamdi, Zahoor Ali Khan, Sakeena Javaid, Abdul Haseeb, Zahid Wadud and Nadeem Javaid
Additional contact information
Aqib Jamil: Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
Turki Ali Alghamdi: Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah 11692, Saudi Arabia
Zahoor Ali Khan: Computer Information Science, Higher Colleges of Technology, Fujairah 4114, UAE
Sakeena Javaid: Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
Abdul Haseeb: Department of Electrical Engineering, Institute of Space Technology (IST), Islamabad 44000, Pakistan
Zahid Wadud: Department of Computer System Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan
Nadeem Javaid: Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan

Sustainability, 2019, vol. 11, issue 22, 1-23

Abstract: The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.

Keywords: cuckoo search algorithm; demand side management; game theory; smart grid; earthworm algorithm; heuristic techniques (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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