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浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2024, Vol. 58 Issue (4): 790-798    DOI: 10.3785/j.issn.1008-973X.2024.04.014
    
Load scheduling and energy allocation optimization algorithm for intelligent home appliances
Didi LIU1,2(),Wenyu YANG1,Zhixian LIAO2,Quanjing ZHANG3,*(),Cong HU4
1. School of Electronic and Information Engineering, Guangxi Normal University, Guilin 541004, China
2. Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips, Guangxi Normal University, Guilin 541004, China
3. Education Information Technology Center, China West Normal University, Nanchong 637009, China
4. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin 541004, China
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Abstract  

To address the problem of high energy consumption in household electricity usage and to improve the user revenue from electricity supply and use, an energy scheduling approach was proposed for loads with electrical differences in households. Firstly, the household electrical loads were divided into elastic loads and non-elastic loads based on the transferable attributes. Then, an optimization model for load scheduling of intellectualized electrical apparatus was proposed by jointly considering distributed renewable energy resources and energy storage devices. Based on the Lyapunov optimization theory, an algorithm for time-varying electricity pricing was designed to allocate energy for multiple home appliances. The algorithm fully considered the load response and the scheduling optimization of different intelligent appliances. Theoretical performance analysis demonstrates that the proposed algorithm achieves asymptotic optimality without requiring any priori statistical information of the system. Finally, simulations were conducted to validated the user revenue improvement capability of the proposed algorithm. Compared to the allocation algorithm that did not take into account the actual needs of various home appliances and tolerable delay, the proposed algorithm can increase the user revenue by 11.2%.

Key words： intelligent appliances      schedule optimization      Lyapunov optimization      energy allocation      demand response     
Received: 14 August 2023      Published: 27 March 2024
CLC:  TM 734  
Fund:  国家自然科学基金资助项目（62061006）；广西自动检测技术与仪器重点实验室基金资助项目（YQ23203）；广西类脑计算与智能芯片重点实验室基金资助项目（BCIC-23-Z7）；青年教师科研资助项目（23kq004）.
Corresponding Authors: Quanjing ZHANG     E-mail: ldd866@gxnu.edu.cn;quanjing_zhang@163.com
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Didi LIU
Wenyu YANG
Zhixian LIAO
Quanjing ZHANG
Cong HU
Cite this article:

Didi LIU,Wenyu YANG,Zhixian LIAO,Quanjing ZHANG,Cong HU. Load scheduling and energy allocation optimization algorithm for intelligent home appliances. Journal of ZheJiang University (Engineering Science), 2024, 58(4): 790-798.

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https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2024.04.014     OR     https://www.zjujournals.com/eng/Y2024/V58/I4/790


家庭智能电器负荷调度和能量分配优化算法

为了解决家庭用电高额能耗问题和提高用户供用电收益，针对家庭中具有用电差异性的负荷进行能量调度. 根据可转移属性，将家庭用电负荷分为2个类别：弹性负荷和非弹性负荷. 联合分布式可再生能源和储能设备构建智能电器用电负荷调度优化模型，基于李雅普诺夫优化理论提出时变电价下的家庭用户多电器能量分配算法. 所提算法充分考虑了不同智能电器的用电负荷响应及调度优化问题. 理论性能分析证明，所提算法能够在不需要系统的先验统计信息的情况下使优化目标渐近最优. 对所提算法的用户收益提升能力进行仿真验证，结果表明，相较于未考虑各家用智能电器实际需求和可容忍时延的分配算法，所提算法可将用户收益提高11.2%.


关键词： 智能电器,  调度优化,  李雅普诺夫优化,  能量分配,  需求响应 
Fig.1 Schematic diagram of home intelligent electricity management system
Fig.2 Energy flow of home energy management system
Fig.3 Comparison of 100-day cumulative revenue for users with different algorithms
Fig.4 Time delay comparison of different algorithms
Fig.5 Comparison of 100-day revenue for users of different models
Fig.6 Comparison of 100-day average latency for users of different models
Fig.7 Charging and discharging characteristics of energy storage devices
Fig.8 Relationship between energy allocated by different appliances and backlog of queues
Fig.9 Comparison of 100-day cumulative revenue for users under different scenarios
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