Multi-objective optimal scheduling of household appliances for demand side management using a hybrid heuristic algorithm

Youquan Liu, Huazhen Li, Jiawei Zhu, Yishuai Lin and Weidong Lei

Energy, 2023, vol. 262, issue PA

Abstract: In the era of smart grids and the Internet of Things, demand side management, which aims to reduce electricity bills while increasing user satisfaction by scheduling appliances properly, becomes imperative for residential consumers. As a result of the conflict between the two objectives, it is impossible to optimize them simultaneously. Nevertheless, using multi-objective optimization approaches, trade-off solutions can be obtained. In this paper, a novel demand-side management method is presented to manage the operation of residential appliances. In the beginning, appliances are divided into interruptible, non-interruptible, and power-shiftable types according to their operating characteristics and the user’s preferences. And the mathematical models are built accordingly. Then, a multi-objective optimization problem is formulated to minimize the electricity cost and user dissatisfaction, in which residents’ tolerance to discomfort is considered. Since it is a multi-objective mixed integer nonlinear programming problem, a hybrid meta-heuristic algorithm is proposed to solve it efficiently. The experiment results have confirmed the effectiveness of the optimization model and the higher efficiency of the hybrid algorithm. Furthermore, a case study has been performed to demonstrate the effectiveness of the scheduling method.

Keywords: Smart grid; Demand side management; Residential appliance scheduling; Mixed integer nonlinear programming problem; Multi-objective optimization; Meta-heuristic algorithm (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:262:y:2023:i:pa:s0360544222023428

DOI: 10.1016/j.energy.2022.125460

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