Open Access

ARTICLE

Temporal Preferences-Based Utility Control for Smart Homes

by Salman Naseer¹, Raheela Saleem², Muhammad Mudasar Ghafoor³, Shahzada Khurram⁴, Shafiq Ahmad⁵, Abdelaty Edrees Sayed⁵, Muhammad Shafiq^6,*, Jin-Ghoo Choi⁶

1 Department of Information Technology, University of the Punjab, Gujranwala Campus, 52250, Pakistan
2 Department of Computer Science, Gift University, Gujranwala, Punjab, 52250 Pakistan
3 University of the Punjab, Jehlum Campus, Jehlum, 49600, Pakistan
4 Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan
5 Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh, 11421, Saudi Arabia
6 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Korea

* Corresponding Author: Muhammad Shafiq. Email:

Intelligent Automation & Soft Computing 2023, 36(2), 1699-1714. https://doi.org/10.32604/iasc.2023.034032

Received 04 July 2022; Accepted 16 August 2022; Issue published 05 January 2023

Abstract

The residential sector contributes a large part of the energy to the global energy balance. To date, housing demand has mostly been uncontrollable and inelastic to grid conditions. Analyzing the performance of a home energy management system requires the creation of various profiles of real-world residential demand, as residential demand is complex and includes multiple factors such as occupancy, climate, user preferences, and appliance types. Average Peak Ratio (A2P) is one of the most important parameters when managing an efficient and cost-effective energy system. At the household level, the larger relative magnitudes of certain energy devices make managing this ratio critical, albeit difficult. Various Demand Response (DR) and Demand Side Management (DSM) systems have been proposed to reduce this ratio to 1. The main ways to achieve this are economic incentives, user comfort modeling and control, or preference-based. In this study, we propose a unique opportunistic social time approach called the Time Utility Based Control Feature (TUBCF), which uses the concept of a utility function from economics to model and control consumer devices. We propose a DR model for residential customers to reduce Peak-to-Average Ratio (PAR) and improve customer satisfaction by eliminating Appliance Wait Time (WTA) during peak periods. For PAR reduction and WTA, we propose a system architecture and mathematical formulation. Our proposed model automatically schedules devices based on their temporal preferences and considers six households with different device types and operational characteristics. Simulation results show that using this strategy can reduce A2P by 80% and improve user comfort during peak hours.

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Keywords

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