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

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 impos...

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Veröffentlicht in:Energy (Oxford) Jg. 262; S. 125460
Hauptverfasser: Liu, Youquan, Li, Huazhen, Zhu, Jiawei, Lin, Yishuai, Lei, Weidong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.01.2023
Schlagworte:
algorithms
case studies
consumer satisfaction
Demand side management
electricity
electricity costs
energy
Internet
Meta-heuristic algorithm
Mixed integer nonlinear programming problem
Multi-objective optimization
Residential appliance scheduling
Smart grid
system optimization
Mixed integer nonlinear programming problem
Residential appliance scheduling
Demand side management
Multi-objective optimization
Meta-heuristic algorithm
Smart grid
ISSN:0360-5442
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Zusammenfassung: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. •Multi-objective problem formulation considering cost and user satisfaction.•User’s tolerance to discomfort is considered.•A hybrid algorithm containing MOPSO and NSGA-II is developed.•Providing users an explicit cost-satisfaction analysis.•TOPSIS approach is used to select the trade-off solution.
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ISSN:0360-5442
DOI:10.1016/j.energy.2022.125460