Work

Dynamic Knowledge Guided Transfer Optimal Scheduling for Home Energy Management System Considering User Preference

Year: 2025

Type: article

Abstract: Home energy management systems (HEMSs) have attracted considerable research interest in residential appliance management. Although optimal scheduling of home appliances has been extensively studied, these problems are fundamentally dynamic multi-objective optimization problems. This paper proposes a dynamic appliance scheduling model under time-of-use electricity pricing based on user’s preferences, to minimize energy costs and user dissatisfaction. A knee point-based manifold transfer algorithm (KPMT-DMOEA) is proposed to solve the scheduling problem. This approach leverages high-quality knee points from previous environments to generate optimized initial populations in response to environmental changes, thereby improving solution quality and convergence speed. The experimental results validate the effectiveness and feasibility of the proposed scheduling framework. By making a comparison with state-of-the-art algorithms, the experimental results demonstrate that the proposed method outperforms others and is able to efficiently generate optimal schedules for each appliance under different environments.

Source: Sustainability

DOI: 10.3390/su172310844

Author: Xi Zhang

Institution: Zhejiang Sci-Tech University

Language: English

Topic: Smart Grid Energy Management

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,896